Datasets:

mudassiruddin
/

yolo

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README.md ADDED Viewed

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+---
+license: agpl-3.0
+task_categories:
+- object-detection
+tags:
+- visdrone
+- small-object-detection
+- yolov10
+- uav
+- drone-imagery
+pretty_name: P2-Graft runs, results and weights
+---
+<div align="center">
+# P2-Graft: runs, results and weights
+### When does a stride-4 prediction level help a pretrained YOLOv10 on drone images?
+[![Code](https://img.shields.io/badge/code-GitHub-181717?logo=github)](https://github.com/Mudassiruddin7/YOLO)
+[![Paper](https://img.shields.io/badge/paper-PDF-b31b1b)](https://huggingface.co/datasets/mudassiruddin/yolo/resolve/main/paper/main.pdf)
+[![Data](https://img.shields.io/badge/data-VisDrone--DET2019-0072B2)](https://github.com/VisDrone/VisDrone-Dataset)
+[![GPU](https://img.shields.io/badge/trained%20on-RTX%20PRO%206000%20Blackwell-76b900)](#reproduce)
+<img src="https://huggingface.co/datasets/mudassiruddin/yolo/resolve/main/assets/fig_architecture.png" width="760" alt="P2-Graft: confident cells of every prediction level on a VisDrone crop">
+*Quratulain Nayeem, Fahmina Taranum, Mohammed Mudassir Uddin, Sara Rizwan*
+</div>
+This dataset repository holds everything behind the paper: per-run results, training curves, saved test predictions and the final weights of the 51 runs reported there.
+A stride-4 branch is grafted onto a pretrained YOLOv10 so that the original outputs stay unchanged at the start, and the new branch is initialised from the pretrained stride-8 weights.
+**Jump to:** [Results](#results) · [Files](#files) · [Use the weights](#use-the-weights) · [Reproduce](#reproduce)
+---
+## Results
+AP on **VisDrone test-dev** (primary), validation AP in the paper. One recipe, one GPU, last-epoch weights, gains paired by seed.
+| Setting | Baseline | P2-Graft | Gain | Seeds |
+|---|---|---|---|---|
+| YOLOv10n, 640 px, 90 epochs | 14.09 | **15.77** | **+1.68** | 3 |
+| YOLOv10n, 896 px, 90 epochs | 18.16 | **18.74** | **+0.58** | 3 |
+| YOLOv10n, 1280 px, 90 epochs | 22.45 | 22.32 | **−0.13** | 1 |
+| YOLOv10n, 640 px, 150 epochs | 14.46 | **15.63** | **+1.17** | 1 |
+| YOLOv10s, 640 px, 90 epochs | 17.46 | **18.19** | **+0.73** | 3 |
+<p align="center"><img src="https://huggingface.co/datasets/mudassiruddin/yolo/resolve/main/assets/fig_scaling.png" width="700" alt="gain by input size and accuracy against compute"></p>
+The gain is largest at 640 px and shrinks as the input grows; at equal GFLOPs a plain baseline at higher resolution is more accurate. On YOLOv10s the per-seed gains are +0.06, +0.19 and +1.94.
+<details>
+<summary><b>Validation AP against published results</b> (ours in bold)</summary>
+| Model | Input | Params (M) | AP | AP<sub>50</sub> |
+|---|---|---|---|---|
+| YOLOv8-N | 640 | 3.2 | 19.6 | 33.3 |
+| FBRT-YOLO-N | 640 | 0.9 | 20.2 | 34.4 |
+| YOLOv10-S | 640 | 7.2 | 23.8 | 39.3 |
+| FBRT-YOLO-S | 640 | 2.9 | 25.9 | 42.4 |
+| DroneScan-YOLO | 1280 | 10.23 | 35.6 | 55.3 |
+| **P2-Graft, YOLOv10n** | **640** | **2.41** | **20.64** | **35.96** |
+| **P2-Graft, YOLOv10s** | **640** | **7.58** | **23.29** | **39.86** |
+| **YOLOv10n baseline** | **1536** | **2.27** | **30.29** | **49.42** |
+Published numbers are quoted from [FBRT-YOLO](https://arxiv.org/abs/2504.20670) and [DroneScan-YOLO](https://arxiv.org/abs/2604.13278) with their own schedules; the rows in bold are 90-epoch runs.
+</details>
+<details>
+<summary><b>What matters inside the branch</b> (35 epochs, 640 px)</summary>
+<p align="center"><img src="https://huggingface.co/datasets/mudassiruddin/yolo/resolve/main/assets/fig_ablation.png" width="700" alt="variants of the branch and the YOLOv10s seeds"></p>
+The warm start, copying the pretrained stride-8 block and head into the new level, is what makes the branch useful: +0.92 test-dev AP against +0.26 for a random start.
+</details>
+<details>
+<summary><b>Qualitative examples</b> (validation crops)</summary>
+<p align="center"><img src="https://huggingface.co/datasets/mudassiruddin/yolo/resolve/main/assets/fig_qualitative.png" width="700" alt="ground truth, baseline and P2-Graft"></p>
+Green: match, red: false alarm, yellow: missed. The two crops show the largest gain in found objects.
+</details>
+## Files
+```
+README.md                         this card
+assets/                           figures of the paper
+paper/main.pdf                    the paper
+results/                          runs_summary.csv (the 51 runs), final_runs.csv (all metrics), contrasts_session_{A,B,C}.csv
+sessionA-20261104-0048/           896 px, 90 epochs, 3 seeds: model and baseline
+sessionB-20261106-1639/           1280 px, 150-epoch schedule, batch-32 control
+sessionC-20261107-0846/           YOLOv10s, 3 seeds
+  runs/<run id>/                  result.json, results.csv (training curve), args.yaml,
+                                  weights/last.pt (final weights), preds_*.npz (saved predictions)
+  results/                        leaderboard.csv, contrasts.csv (image-bootstrap intervals), all_runs.csv
+  logs/                           worker and resume logs
+```
+Run ids read `<family>-<variant>-<tag>-<input size>-e<epochs>-s<seed>`: variant `base` is the unmodified YOLOv10, `graftd` with transfer `role_ws` is P2-Graft (deeper block, warm start).
+Runs of the 35-epoch ablation and of the 640 px comparisons come from earlier sessions and are listed with their source in `results/final_runs.csv`.
+## Use the weights
+```python
+from huggingface_hub import hf_hub_download
+from ultralytics import YOLO
+path = hf_hub_download(
+    "mudassiruddin/yolo", repo_type="dataset",
+    filename="sessionB-20261106-1639/runs/v10-graftd-ws-640-e150-s0/weights/last.pt")
+model = YOLO(path)                       # P2-Graft, YOLOv10n, 640 px, 150 epochs
+model.predict("drone_image.jpg", imgsz=640, conf=0.25)
+```
+The checkpoints store the four-level architecture, so Ultralytics rebuilds it from the file.
+## Reproduce
+Code, notebook and the scripts behind every table and figure: **[github.com/Mudassiruddin7/YOLO](https://github.com/Mudassiruddin7/YOLO)**.
+All runs used one NVIDIA RTX PRO 6000 Blackwell GPU, PyTorch 2.11 and Ultralytics 8.4.150.
+## Licence and data
+The weights derive from Ultralytics YOLOv10 checkpoints and keep the AGPL-3.0 licence. VisDrone images and annotations are not included; they belong to the VisDrone project.

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paper/main.pdf ADDED Viewed

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results/contrasts_session_A.csv ADDED Viewed

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1	+ family,model,imgsz,epochs,seeds,test_dAP,test_dAP_lo,test_dAP_hi,test_dAP50,test_dAP50_lo,test_dAP50_hi,B
2	+ v10,graftd/role_ws,896,90,"0,1,2",0.5770754171951715,0.42328589963624647,0.7861623238573618,0.7476641845385501,0.4133096323047147,1.106725353777259,200

results/contrasts_session_B.csv ADDED Viewed

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+family,model,imgsz,epochs,seeds,test_dAP,test_dAP_lo,test_dAP_hi,test_dAP50,test_dAP50_lo,test_dAP50_hi,B
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results/contrasts_session_C.csv ADDED Viewed

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1	+ family,model,imgsz,epochs,seeds,test_dAP,test_dAP_lo,test_dAP_hi,test_dAP50,test_dAP50_lo,test_dAP50_hi,B
2	+ v10s,graftd/role_ws,640,90,"0,1,2",0.7327902632475336,0.49421672221197344,0.9619142063562285,1.2532865319232265,0.8533078981487534,1.616903657270395,200

results/final_runs.csv ADDED Viewed

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+run_id,group,family,variant,transfer,floor,seed,epochs,imgsz,tier,batch,val_AP,val_AP50,val_AP75,val_APs,val_APm,val_APl,val_AP_tiny,val_AP_xsmall,val_AP50_tiny,val_AP50_xsmall,val_AP50_small,val_AP50_medium,val_AP50_large,val_ARmax,val_ARtiny,val_AP50_ign,val_AP_ign,val_AP50_o2m,val_AP_o2m,test_AP,test_AP50,test_AP75,test_APs,test_APm,test_APl,test_AP_tiny,test_AP_xsmall,test_AP50_tiny,test_AP50_xsmall,test_AP50_small,test_AP50_medium,test_AP50_large,test_ARmax,test_ARtiny,test_AP50_ign,test_AP_ign,test_AP50_o2m,test_AP_o2m,val_AP50_at800,val_AP_at800,val_APs_at800,val_AP50_at960,val_AP_at960,val_APs_at960,test_AP50_at800,test_AP_at800,test_APs_at800,test_AP50_at960,test_AP_at960,test_APs_at960,val_AP50_conf05,val_AP_conf05,val_AP50_conf25,val_AP_conf25,val_AP50_maxdet100,val_AP_maxdet100,val_ultra_AP50,val_ultra_AP,params_deploy_M,params_train_M,gflops,latency_ms,throughput_b16,latency_seq,train_h,frac_transferred,frac_aligned,tide_Cls,tide_Loc,tide_Both,tide_Dupe,tide_Bkg,tide_Miss,tide_FalsePos,tide_FalseNeg,src,cond,model,train_batch,val_AP50_at1024,val_AP_at1024,val_APs_at1024,test_AP50_at1024,test_AP_at1024,test_APs_at1024
+v10-base-f640e90-s0,"YOLOv10n baseline, 640 px, 90 epochs",v10,base,role,16,0,90,640,7,32,17.931740672033747,32.06278258097437,17.267223700334313,9.252017688849538,27.789022580005817,42.22570116050743,4.419618043250228,12.712235708795905,12.270771347141677,27.973465230757157,21.368395840723824,46.621828589215966,58.79326356347272,33.52593050061234,13.3971960248701,32.694229943850736,18.175446461084224,29.170308830118735,16.78817419091301,14.033410109925896,25.660639902849212,13.84555232903382,6.272753784594386,21.90557701423715,33.03339495104062,2.6666593216680083,9.232992174748716,7.796073660189361,21.75049993952126,14.898598472802178,39.01252863383239,49.69616914479176,30.84283610540463,10.241099287187662,26.040402415165246,14.172309176968186,23.687953285871004,13.339267243016344,35.737352029469406,20.407611112281177,12.011518422867628,36.95152820360614,21.25100909144954,13.030975435705578,28.852695990689455,16.00643462437244,8.211136189571544,30.948762812855325,17.261489743437878,9.739368623028945,30.264587293978778,17.213506784661377,22.80226973618743,14.222971243016971,27.664369425552653,16.243629740439175,31.75028540701243,17.59472123325083,2.267118,2.71094,6.596608,3.2829025003593415,,True,1.2841104511419932,0.9431252299898545,0.9431252299898545,13.003470560167749,5.4868655154223305,0.9760528975887439,0.8249276052455556,2.1354570766785343,5.927731663108688,27.145138211104836,18.027612854220386,r3,n640e90,base,32,,,,,,
+v10-base-f640e90-s1,"YOLOv10n baseline, 640 px, 90 epochs",v10,base,role,16,1,90,640,8,32,17.876110416680945,31.89759585444539,17.073632432524974,9.233137172277422,27.888139797227517,37.7070567065385,4.196396690382055,12.780394674572781,12.162564131126832,27.9299841042281,21.260031584792728,46.43834609534593,50.27563580484904,33.377698024826415,13.242797330853575,32.50882066712546,18.111726732671382,29.06830444401971,16.842514879280966,14.03351062796415,25.68446923648583,13.810561613955658,6.223086262199661,22.10565141672374,31.626920675429766,2.7507107632367505,9.200215622044967,7.980250343365348,21.663203746515364,14.789363157686008,39.23138411791163,50.705127675466365,30.58906955864906,9.937379887863411,26.094526485984126,14.19607061126586,23.707036870546105,13.414670833633021,35.752723688064656,20.346566065361223,12.169536825782243,37.52584126318175,21.52243451361324,13.768478314258736,29.068649067182683,16.18844589224115,8.310016375093369,31.308860682735983,17.578620587934026,9.84416610607612,30.25207037782453,17.248747840114,22.791349179121887,14.233208109644579,27.553861779522926,16.152079684887067,31.50959983863917,17.48517567203724,2.267118,2.71094,6.596608,3.6671534999186406,,True,1.327651391029358,0.9431252299898545,0.9431252299898545,13.389982239492845,5.158518044479237,0.9471335632565712,0.871102443063748,2.1322757939815205,6.12420369730652,27.508344739614003,18.24730360447625,r4,n640e90,base,32,,,,,,
+v10-base-f640e90-s2,"YOLOv10n baseline, 640 px, 90 epochs",v10,base,role,16,2,90,640,8,32,17.456560790775125,31.343929565879197,16.979778666483732,9.061149141320179,27.12665145806425,35.952856668412316,4.2261953512783395,12.500166672791165,12.502562568927186,27.33506734440809,21.011731631051532,45.5934559444547,48.04008115620325,33.35838407146259,13.026216393552897,31.94693376017136,17.695580434250523,28.428584606078317,16.43254963839497,14.195742037700645,25.86270527436293,13.96596390878424,6.258597873875966,22.15009581438798,31.68048553282214,2.6618885763301936,9.250978463702769,7.750285138405827,21.556452889072258,14.70460714195363,39.48888721448458,46.511228081320496,30.702744565209343,10.200295127161422,26.256788702418625,14.338235715848116,24.108848922618385,13.612575050558368,35.419809435698085,20.037379345987276,12.152068817854836,36.38682645136866,20.865850103134175,13.179452237562316,29.36180170159517,16.32038322848989,8.33838973038711,31.563578716086482,17.733539263705175,9.966698578811508,29.615226787717152,16.749583339237528,21.961559369275577,13.684837996618931,26.862299699261577,15.677064950619505,31.18351972866316,17.191819029442094,2.267118,2.71094,6.596608,3.2018130004871637,,True,1.265188656449318,0.9431252299898545,0.9431252299898545,13.552307616565912,5.354236607152949,1.0091906786389657,0.8612617102491029,2.10497812781518,5.9512999492015055,27.566961523229708,18.037792348450637,r4,n640e90,base,32,,,,,,
+v10-graftd-f640e90-s0,"P2-Graft deep, warm-started, 640 px, 90 epochs",v10,graftd,role_ws,16,0,90,640,7,32,20.740187011221554,36.147073133796596,20.155389668061904,13.127973081333097,29.456747362337417,38.86445670848302,7.508931733118156,17.05891413391713,18.65042293253835,33.18470596271179,27.155517792264632,48.039747659174395,56.44876115714838,38.68071316648792,21.029922771139592,36.86209920454326,21.053058989797336,34.94912817043082,20.165350691690335,15.56125984073391,28.274645590966806,15.409197663140134,8.329937408748872,23.34468997687984,30.01978797177606,4.467299252249838,11.95688829838102,11.298182264186485,26.019805419392526,18.48662001568696,40.59543869171575,45.04194973805235,34.73954326204876,15.402321899220746,28.753945306714446,15.754392569901668,27.314313648646866,15.35050429627079,39.13217657661424,22.76149805957904,15.490935636255257,39.575123436538306,23.03973078369756,16.445840017660704,31.01240775580542,17.354387303867007,10.2849924263747,32.50725060264375,18.328661486898817,11.338209655269063,34.25971245373762,19.87942348294503,25.59652569788223,16.022143392925727,30.978784715907672,18.46728764204123,35.95811343550967,20.591619416854194,2.40684,2.939952,13.7170944,3.704310498505947,,True,1.9890600108438068,0.9431252299898545,0.9431252299898545,15.249778838886591,3.228490191467948,0.9405341502807048,1.2366723287355441,2.429610833239849,6.108251831291753,28.20936250976778,16.191460273212655,r3,n640e90,M,32,,,,,,
+v10-graftd-f640e90-s1,"P2-Graft deep, warm-started, 640 px, 90 epochs",v10,graftd,role_ws,16,1,90,640,8,32,20.584471763351424,35.784071712542875,20.037201738909033,12.915979807447576,28.56755009919198,40.239057347167915,7.079977382557019,16.85429099280706,18.03847127266531,33.220316615957174,27.073825407902604,46.26373460431342,55.09261521987116,38.647385491853825,20.779400571556923,36.54214553464881,20.906771996099756,34.575643977408156,20.116284082606565,15.800276239994847,28.547085596881505,15.538876592246769,8.217736256255998,23.50852457488549,31.949621268977,4.2848404699981915,11.786931974899554,11.344373558004378,25.899835018637994,18.425619424070085,40.535985316900415,47.74121484182856,34.93886489020145,14.975254545357544,29.060426226165028,16.005913763994347,27.581831530155576,15.495650543896936,38.337224483393044,22.44509732240175,15.282319091936749,39.02972547435621,22.993611830307167,16.25032601084661,31.20980521416018,17.522738454247747,10.187617609240567,32.61731467650716,18.4113336237072,11.314486847300401,33.829058437691955,19.717266750165948,25.128916057562428,15.869413894526746,30.489335417607787,18.33927062138017,35.41585017322216,20.21660930044884,2.40684,2.939952,13.7170944,3.6345270000310848,,True,2.7267132047812144,0.9431252299898545,0.9431252299898545,14.771434756153873,3.1726137607225624,0.9478198456191436,1.3376032810713596,2.3136082783608956,6.136263993994959,28.67137383201159,15.80640678969349,r4,n640e90,M,32,,,,,,
+v10-graftd-f640e90-s2,"P2-Graft deep, warm-started, 640 px, 90 epochs",v10,graftd,role_ws,16,2,90,640,8,32,20.59966438939691,35.94375071335947,20.218844200716525,13.326965141228019,28.968724270718578,33.28230319825561,7.46767494404168,17.36029995849398,18.398661021313988,33.774600387299145,27.53414488664307,47.32867336751007,45.19425490176182,38.22865121704166,20.5736590276354,36.67404710090001,20.910680872358054,34.69934804471954,20.172297597236415,15.948773973168839,28.827207269976284,15.757840770992226,8.414947868289742,23.632543351213258,31.688281113189348,4.473569873965545,12.067140868468417,11.448769187220693,26.117814480937913,18.597052795559467,41.03880979326181,45.72146945020658,34.84660086589045,15.094115561171353,29.328108929400678,16.151145790141825,27.750241285353024,15.674215308051053,38.55012741008464,22.53845537077554,15.589431727305495,39.041061497845924,22.788009262097773,16.35101433543224,31.569482032752124,17.689918666767422,10.470648833267553,33.05110800580084,18.668123163296396,11.47566092215213,34.03007563098785,19.774757515444257,25.187057078642088,15.76455699919728,30.644609540189304,18.24172259488251,35.83655910514149,20.430541774627805,2.40684,2.939952,13.7170944,3.7020175004727207,,True,1.0964929697910946,0.9431252299898545,0.9431252299898545,15.624183158962417,3.122475562121693,0.9836629086776938,1.2652300160987409,2.4297690701321883,6.451077851236391,27.719857197892345,16.680602918298376,r4,n640e90,M,32,,,,,,
+v10-base-f16-896-e90-s0,"YOLOv10 baseline, v10, 896 px, 90 ep",v10,base,role,16,0,90,896,1,32,23.280049504959845,39.84672089672938,23.292959743474093,14.33226951557722,33.95320359472515,46.369615378876325,7.4582319228719705,18.968374880891194,19.087338301837903,36.715878512474035,29.56482495028996,53.87141245245619,63.55967108444749,40.848956439009065,20.86339101840089,,,,,18.052231775932828,32.14618070812275,17.89194387878635,9.521888159720785,26.617546872719856,38.75220719588064,4.701795793820285,13.651028540521931,12.440747000813925,29.61787034359921,21.228881654553273,45.473764325780195,56.214261840069355,36.67271823207911,15.928210401461355,,,,,,,,,,,,,,,,,,,,,,,,,2.267118,2.71094,13.044957184,3.518355000323936,2546.456315719814,True,2.0235112576352225,0.9431252299898545,0.9431252299898545,13.65884494857319,4.012447686626601,0.9974592889619132,1.0576703456363106,2.6415273227814,5.959350488955167,28.074071182478548,15.98537307846582,A,n896e90,base,32,41.7705495710642,24.660609233155423,15.996349521456757,34.048797296537806,19.39876454624835,10.6230575150931
+v10-base-f16-896-e90-s1,"YOLOv10 baseline, v10, 896 px, 90 ep",v10,base,role,16,1,90,896,1,32,23.155402767047725,39.413715980873256,23.267541154366718,14.165227937732167,33.46322545137495,46.24219320612542,7.251136345386601,18.776318530411526,18.896604928075572,36.08411875365383,29.089589208268958,52.703869395140245,64.04362966690881,40.480929965526485,20.723614470150594,,,,,18.203219666277644,32.44836150347358,18.132780749961935,9.66041692057022,27.13566907488229,38.145204512428435,4.627730480970518,13.787497603788385,12.272525731405757,29.766260221879225,21.438990828743794,46.13373159214692,55.97065872470147,36.913293928303624,15.574311764279614,,,,,,,,,,,,,,,,,,,,,,,,,2.267118,2.71094,13.044957184,3.46101049990466,2543.206899738543,True,1.2932257536384795,,,14.77396526916312,4.0652129853090315,0.9505376892512558,1.0433978868966989,2.6128408820882854,5.64928424607745,27.81400679140397,16.298009686588507,A,n896e90,base,32,41.50809958191022,24.544957296273846,16.106824661388288,34.191827925363654,19.3573457017799,10.989702799120156
+v10-base-f16-896-e90-s2,"YOLOv10 baseline, v10, 896 px, 90 ep",v10,base,role,16,2,90,896,1,32,23.260499258111984,39.69169029336987,23.075227275190503,14.199713439457776,33.903850534802224,45.68994662524947,7.341956489604791,18.766198033981897,19.25842723409255,36.237006363260626,29.309365507539503,53.6200000822134,61.08363609479471,40.7197264236497,20.81765920464456,,,,,18.232942682319912,32.32527529496118,18.320520796149093,9.612338955937078,27.047631397886096,40.12376430997608,4.845427234538013,13.687959232450012,12.57565228540612,29.46411856526806,21.253255230432956,46.112832172338855,55.802268180641356,37.042863097968365,16.106092803656914,,,,,,,,,,,,,,,,,,,,,,,,,2.267118,2.71094,13.044957184,3.459226999893872,2191.8503305477557,True,1.669774868686994,,,14.488272995996397,3.9883913435198153,0.9854714475105908,1.0631372562709274,2.7998492619090953,5.720353670223915,27.833062181877658,16.164192854820193,A,n896e90,base,32,41.57509682561937,24.427823788724037,15.804709999623762,34.225206084768416,19.420544595958326,11.025464928015976
+v10-graftd-ws-896-e90-s0,"P2-Graft deep, warm-started, v10, 896 px, 90 ep",v10,graftd,role_ws,16,0,90,896,1,16,23.97717824782963,40.52444733530356,24.17451101913722,15.545425907280869,33.29792618593076,41.66328012280374,9.026428089219554,19.902998494003494,21.37788402400461,37.49332894856366,30.979635574449404,52.72214111407031,54.578306557366055,43.645605753314584,25.956574265965028,,,,,18.49769107746572,32.591608363003935,18.391493680369596,10.154534968280958,26.47420449141253,36.96156412665222,5.610446256466043,14.201933558756894,13.894038264252353,29.72622391779356,21.88045071090424,44.952216709753635,52.951732904689116,39.299702147675525,18.664069132162496,,,,,,,,,,,,,,,,,,,,,,,,,2.40684,2.939952,27.001110528,4.032323500268831,1232.045155690733,True,1.0195496610800425,,,14.700092763875453,2.7001626770833838,0.9826720625778904,1.492908249531773,2.6824689183907324,5.872322500595871,28.78248335776575,14.782133626123667,A,n896e90,M,16,41.422800334037994,24.59818623205047,16.93045262283646,34.11187389586576,19.503437669347246,11.148796686642468
+v10-graftd-ws-896-e90-s1,"P2-Graft deep, warm-started, v10, 896 px, 90 ep",v10,graftd,role_ws,16,1,90,896,1,16,24.177141400243883,40.903701795711925,24.09255632599902,15.895541430578108,33.50103659799623,44.16605250079344,9.209446168888281,20.318735643157197,22.151943462285704,37.6902147496477,31.37344280682791,52.85501192073257,60.201952457230234,43.680952507862905,25.88168914043574,,,,,19.09181032136211,33.648590705984944,18.972282661146476,10.50247890815891,27.17242491741649,40.1474890523653,5.452633727366202,14.761101125234008,13.705156840343328,30.68530812629881,22.48252003989714,46.071819332034,57.409608354298015,39.50367753686834,18.50270186273758,,,,,,,,,,,,,,,,,,,,,,,,,2.40684,2.939952,27.001110528,4.047027000069647,1234.6156282870236,True,1.8750037426418729,,,15.428983502990206,2.6315251484823747,0.9996408980147535,1.4406977273969233,2.6768708404162,5.700485010072704,28.602140386532653,14.782470429114078,A,n896e90,M,16,42.64902274292099,25.483404382757417,17.312997325556378,35.208146240528436,20.19515307895735,11.680207266507587
+v10-graftd-ws-896-e90-s2,"P2-Graft deep, warm-started, v10, 896 px, 90 ep",v10,graftd,role_ws,16,2,90,896,1,16,24.06320970109535,40.518122135823695,24.53881520036455,15.893609472864362,33.41242227485727,43.316516733509765,9.238239133597926,20.341176503786727,21.595811894240324,37.97147852787817,31.40071232409371,52.43910668589545,57.01109884071292,43.02344733243319,25.08746003992488,,,,,18.630118977288074,32.92261099118429,18.523714715909193,10.28724759393342,26.7391108871323,38.137555281829066,5.509730308612178,14.253446378070327,13.80573993557978,29.769614525714832,22.127053472296833,45.276017843035476,57.483633023869764,39.0669744178602,18.149838074822476,,,,,,,,,,,,,,,,,,,,,,,,,2.40684,2.939952,27.001110528,4.041699000026711,1234.7152382245831,True,0.8703992803229226,,,15.48196985259603,2.6310169834661536,0.950425306823135,1.5062226029051828,2.6700255875146013,5.71427926069709,27.996729349324816,15.463297857563497,A,n896e90,M,16,41.83348298174688,25.069985156899378,16.930166084770022,34.60664396735062,19.771581346717408,11.326119655024518
+v10-graftd-ws-896-e90-b32-s1,"P2-Graft deep, warm-started, v10, 896 px, 90 ep",v10,graftd,role_ws,16,1,90,896,2,32,25.254633458992227,42.37691375510113,25.622385012411304,17.570718706278,33.79924162408543,43.10561282725423,10.915051392539151,22.173909677715123,25.269538052801572,40.64227676682166,34.3260584887037,52.41361893105228,62.44299259834838,45.41150648357129,29.441198715704274,,,,,19.513333789087593,34.44829727260608,19.406214709742382,11.377666438681421,27.718296897985134,38.167541224747936,6.216829843910291,15.707928243815564,16.37058628143852,32.31503475121929,24.430417845575246,46.286942572574745,54.151672061325954,40.391616494992284,19.67700505091448,,,,,,,,,,,,,,,,,,,,,,,,,2.40684,2.939952,27.001110528,3.832989500097028,1240.2064385929073,True,2.3894673626290426,0.9431252299898545,0.9431252299898545,14.962025397207839,2.4726523271224465,1.0238819695812822,1.3691797860251,2.8963261606865984,5.59325001240439,29.50427436371075,13.561813973388112,B,n896e90b32,M,32,44.03104137190099,26.463758119186732,18.97926885616713,36.07000747355357,20.60177238143326,12.55837886498225
+v10-base-f16-1280-e90-s0,"YOLOv10 baseline, v10, 1280 px, 90 ep",v10,base,role,16,0,90,1280,2,8,28.43749006819445,46.92299673280106,29.260631929265422,19.212177219057434,39.96679651575573,50.812767915436794,10.789702930792549,24.69460422364762,26.08616005578496,44.38667223332712,37.10100217306596,60.2888079208851,65.50268730130703,48.012905207570576,28.364718043094754,,,,,22.447917843628005,38.6120874273782,22.559396687942364,12.784658086296938,32.670538448082134,41.6173502515303,6.4823233061405805,17.719011389672442,16.965906049943367,35.695629420528455,26.831770962644992,52.98144303175174,57.44706242314608,42.768257858839654,22.004407682737998,,,,,,,,,,,,,,,,,,,,,,,,,2.267118,2.71094,27.123712,3.372497000327712,1212.117263569358,True,2.1749845194154314,,,13.779907416986497,2.9579247271095426,0.9897799491375139,1.1501981707823319,3.2251957889572225,5.097183014383987,28.324154167747366,13.434317571976145,B,n1280e90,base,8,,,,,,
+v10-graftd-ws-1280-e90-s0,"P2-Graft deep, warm-started, v10, 1280 px, 90 ep",v10,graftd,role_ws,16,0,90,1280,2,8,29.13777083734382,47.74916910577546,30.038373912474437,20.4402926587768,39.39834900120271,45.975291264371116,12.637388950293893,25.480376156027436,28.399131349766726,45.31598034615399,38.63561915025483,59.53925657755259,61.68280989448219,49.91724028688143,33.409143926533844,,,,,22.321370315933546,38.459724084402986,22.465758302643543,13.457020693999933,31.457994222348024,38.96662455121901,7.857286276142092,18.253891210230016,19.430427559150303,36.32613519683904,27.947722344893194,51.10448432631666,54.75576051596539,44.352482993966824,24.707887813230478,,,,,,,,,,,,,,,,,,,,,,,,,2.40684,2.939952,55.6056576,3.9199435000227822,532.389389196312,True,1.04377232670784,,,13.7130580143129,2.2660888995849717,1.0584050845428123,1.4065468600343678,3.1750229466799667,4.876243534669442,29.18143535186833,12.20805486424998,B,n1280e90,M,8,,,,,,
+v10-base-f1536e90-s0,"YOLOv10n baseline, 1536 px, 90 epochs",v10,base,role,16,0,90,1536,10,32,30.292209386392148,49.418692011007145,31.238349372582352,21.517992174028034,41.38235350001245,50.379306207078535,12.453274988125811,27.27878143791972,28.732442426532582,47.98689074504751,40.46249210414376,61.94259463337291,65.00764729291203,49.853319818329815,31.784785660814663,50.59860768163957,30.850159892472597,48.32754620125079,29.745722035053983,23.891241536993245,40.825846059262865,24.331197190387577,14.849095588325486,33.6259831554182,43.784520595332324,8.27426861031071,19.997375255907645,20.65002657823057,39.0685492616988,30.26262023378511,54.20209882445408,62.275707660810056,44.566939362555715,24.986458770109273,41.662329489505886,24.2590988922544,39.576662046936235,23.217985497436146,,,,,,,,,,,,,47.0067301826068,29.09245112401021,39.01027139562819,25.279850641135283,42.40623566581993,26.890371641558126,49.430172718800094,30.39091050884794,2.267118,2.71094,39.680999424,3.2843310000316706,,True,2.0255631157424716,0.9431252299898545,0.9431252299898545,14.116430842569663,2.7086937636329225,0.9110961395530026,1.0755353587471674,3.2877283105754387,4.610556770423521,27.51182053495554,12.676309051090016,r5,n1536e90,base,32,,,,,,
+v10-base-f16-640-e150-s0,"YOLOv10 baseline, v10, 640 px, 150 ep",v10,base,role,16,0,150,640,2,32,18.36815287201223,32.7289065827306,17.76743539478555,9.998509003280704,27.9780677747437,39.27669870066083,5.046712212350976,13.58448770143165,13.82436289159022,29.412538139143813,22.812261491383058,46.432540585924585,52.6271660481655,34.01707436795052,14.529129590537018,,,,,14.459116594465577,26.402181412376848,14.249178447535416,6.649842572151081,22.42308033956793,33.23042094024766,2.977392036886869,9.816070958861033,8.617878381884536,22.890496110151997,15.683473013397265,39.586384721567065,48.72529777606817,31.22012972972323,10.675540524992563,,,,,36.22673944152719,20.571299911999837,12.6284228841197,36.80387196544802,21.226217431920784,13.719121746469359,29.94575573737975,16.62772392217184,8.780467024051546,31.522251475711087,17.6185121770195,10.151595917595774,,,,,,,,,2.267118,2.71094,6.596608,3.5433134999038884,4477.616743854449,True,1.5819779502683216,0.9431252299898545,0.9431252299898545,13.13236369378231,5.235351095894309,1.0016555280915753,0.799789651147087,2.343414742925411,6.0079213274742145,27.370103318259495,18.018674220968904,B,n640e150,base,32,,,,,,
+v10-graftd-ws-640-e150-s0,"P2-Graft deep, warm-started, v10, 640 px, 150 ep",v10,graftd,role_ws,16,0,150,640,2,32,19.85833018541036,34.72994461566852,19.49787412829523,12.371779216646464,27.858573285524635,37.52437320058519,6.929562871266808,16.127131030105634,17.419785417484206,31.65835826679065,25.776432448353987,46.44463418529174,51.64354392592608,37.917795724341865,20.39639292290438,,,,,15.629056610203138,28.058549406443493,15.476192356125381,8.264025166363053,23.005347333117026,30.92577154918647,4.274918168139085,11.760031268350357,10.909959373678719,25.46433365455903,18.201019112277507,39.978139275488445,46.56045704891435,34.22322984768966,14.999564002910695,,,,,37.93313905104468,22.173348649445096,14.929127808993762,37.872020601216114,22.06642601788917,15.06488703803103,30.852377562323074,17.300952949553153,9.923376208004422,31.871162347336945,18.10048621687094,10.893364704994234,,,,,,,,,2.40684,2.939952,13.7170944,3.855590499824757,2494.0858987168044,True,1.6797009281317392,,,15.289281994043954,3.304266432669067,0.9764264966089371,1.2719711146971235,2.2538362222567727,6.322026121978553,28.33936231502455,16.59856656021119,B,n640e150,M,32,,,,,,
+v10s-base-f16-640-e90-s0,"YOLOv10 baseline, v10s, 640 px, 90 ep",v10s,base,role,16,0,90,640,3,16,22.001350021930634,38.24692832961548,21.55475274331051,13.37495732329827,32.26326651138657,44.92548087648642,6.740269598190013,17.97026133262781,18.025492030421226,35.713672205411186,28.290047628162345,52.23345806244619,59.30530157630434,37.820147143761794,18.46209762614894,,,,,17.414245126079557,30.888806347666513,17.271687067242937,8.628286791299887,26.740362257921795,36.945658747912184,4.216626058994282,12.46643186542132,11.284576459392632,27.301986061458095,19.27529006657825,46.01570605645156,55.46604071085053,34.19373478321373,13.766989943686028,,,,,42.29028884362263,24.650450957795673,16.48341055042854,43.24713584079531,25.316929256655857,17.81660040162468,34.845895448467246,19.868530677243136,11.264801574345686,36.66579790448514,21.09207809845237,12.568828137028904,,,,,,,,,7.22187,8.074092,21.5520768,3.430163999837532,2410.333158486694,True,1.9414820830027262,0.9924216787474719,0.9924216787474719,13.771040701322121,5.518103543080571,0.9823534186820666,0.6531235627668295,2.6183161933924026,5.744232990254027,26.70356671988948,17.589315717547592,C,s640e90,base,16,,,,,,
+v10s-base-f16-640-e90-s1,"YOLOv10 baseline, v10s, 640 px, 90 ep",v10s,base,role,16,1,90,640,3,16,22.107766685747578,38.31233970488236,21.86925302977682,13.158365037101733,32.714296385124285,44.66413405217298,6.527785907037548,17.701501503007698,17.626950175283802,35.655618930148194,28.125743082513015,52.53309525435832,58.07944541735529,37.41964827156855,17.1630933961437,,,,,17.3576452986625,31.074339326984646,17.075486293471894,8.869778433162498,26.613132314440584,36.72139796370277,4.262812069457645,12.681544511460855,11.583033734556869,27.925335349015345,19.9462778517676,45.77255043896082,53.26662063230712,33.87511570149144,13.539092326767289,,,,,42.39609464627327,24.778055770978074,16.47298596341358,43.14440001342732,25.36449752691797,17.479217734298224,34.55677790607034,19.64453180846023,11.289412452492941,36.44055456779704,20.834615195726663,12.955442133769127,,,,,,,,,7.22187,8.074092,21.5520768,3.4375775003354647,2408.762113235742,True,1.2883642543686762,,,14.35327072027495,5.531305411576049,0.9975082768278298,0.6104195545098676,2.5671651557724573,5.5323058600877175,25.846076136701797,18.26174765940405,C,s640e90,base,16,,,,,,
+v10s-base-f16-640-e90-s2,"YOLOv10 baseline, v10s, 640 px, 90 ep",v10s,base,role,16,2,90,640,3,16,21.845848333288526,37.91216568306799,21.529011645002733,13.295863515169948,32.37332020679727,44.82302574684642,6.576687650373361,17.88973106066877,17.674661693716562,35.67458006366754,28.173075840674596,52.1389479319904,58.82919279575509,38.05595220655288,17.93517589792994,,,,,17.602780886234754,31.30350782909406,17.536341442599955,8.751139452156458,26.569265731254156,36.545611912834666,4.192310476007795,12.619668652114658,11.647129373898778,28.046930356516448,19.95179571616508,45.39243506797513,53.68237169979908,34.192594130936946,13.824017085077214,,,,,41.832158171413155,24.434387091347197,16.289296251224382,42.726208341622126,25.108849680815254,17.48908211775156,34.393268052732054,19.619978016561262,11.15725834673836,36.497017240773225,20.973385305356615,12.596555787893557,,,,,,,,,7.22187,8.074092,21.5520768,3.4115995003958233,2402.654212394247,True,1.4551289415359496,0.9924216787474719,0.9924216787474719,14.060241533967712,5.432810449004833,1.0167511694302718,0.6255286646076073,2.6369271318153835,5.6804120484458664,27.137339267427052,17.446330863148795,C,s640e90,base,16,,,,,,
+v10s-graftd-ws-640-e90-s0,"P2-Graft deep, warm-started, v10s, 640 px, 90 ep",v10s,graftd,role_ws,16,0,90,640,3,16,22.07740453794057,38.16371781684856,21.81232460217542,13.513888258641654,31.34009590599307,47.80027333928032,7.482851587348425,17.549957496053413,19.401307005040554,34.58117075488768,28.381583296994894,50.58453986138941,63.25965577338538,40.14469316919039,22.170150325515884,,,,,17.476634804278863,31.158202709311677,17.368291114915678,9.040267862433106,25.85292620014498,36.91526284776557,5.073964319635417,12.586532904715146,12.829302907107651,27.437124589169947,20.12596457836363,44.25396156968792,55.329484217947,35.67082721693251,16.239791981495582,,,,,41.4911810028132,24.36126491443259,16.11692526379706,42.274930772608585,24.967716913343367,16.92837303104273,33.96535625004188,19.43799056340797,10.91773556788898,35.05895336078704,20.048630463321338,11.726833512270908,,,,,,,,,7.578936,8.584704,39.7743616,4.020878499432001,1300.8103641522798,True,0.503212661743164,,,15.628171233782425,3.4583852509454545,0.9622435270463257,1.40503910018397,2.482164222949393,5.753362827423416,28.27192574750788,15.805384786191851,C,s640e90,M,16,,,,,,
+v10s-graftd-ws-640-e90-s1,"P2-Graft deep, warm-started, v10s, 640 px, 90 ep",v10s,graftd,role_ws,16,1,90,640,3,16,22.50986338153858,38.73687204320515,22.19817160264636,13.508270868953803,32.17890842671311,45.3846263148881,7.886623855109734,17.41144255406284,19.961834933473206,34.21162086416105,28.307516787750174,51.837459325591496,64.26136614411433,40.467458823480605,22.318884142759355,,,,,17.55158719643783,31.454199079239544,17.41129513906583,9.233505106397281,25.984944639712314,36.20300413251432,5.001214175354654,12.866271453637756,12.821866509782847,27.871647647108716,20.444806719655233,44.94936397900508,53.74055458588782,35.89524448335456,16.848016874196624,,,,,41.86659903714888,24.665715436460108,16.578717291947214,42.52679027707801,25.202335578686284,17.37866526817928,34.56729871857958,19.604730820969035,11.002573508755624,35.89420077198597,20.46778143691564,12.104820979749126,,,,,,,,,7.578936,8.584704,39.7743616,4.521476000263647,1301.2485032112081,True,0.5226721311277813,,,15.510398472853858,3.436811522818523,0.95432436774135,1.403638476803117,2.443588796674689,5.956945876129851,27.99580122412157,16.19085361580762,C,s640e90,M,16,,,,,,
+v10s-graftd-ws-640-e90-s2,"P2-Graft deep, warm-started, v10s, 640 px, 90 ep",v10s,graftd,role_ws,16,2,90,640,3,16,25.280400932387426,42.684812267961036,25.490479919635856,17.37356587766575,34.85454466059748,45.45239810978316,10.042725232015764,22.178013362595994,24.460346140719622,40.78787471139869,34.1778347476214,54.475773947268195,65.40930258698575,43.25167995083861,26.055437731824867,,,,,19.54482010000271,34.41411131096365,19.612469837449474,11.134452734667502,28.630035910146084,36.0274827261822,6.395388317478449,15.564690709727675,15.596461245114353,32.344237263264496,23.834827307501914,47.98942087870247,52.82904492523125,37.8052468570181,18.507940551045106,,,,,46.13217572280152,27.58435401221049,20.407903125860425,45.91632439570809,27.434616859484308,20.697904253111858,36.8576500251835,21.087557473025115,13.225336481204597,38.10796734073572,21.90596836692598,13.985322734743727,,,,,,,,,7.578936,8.584704,39.7743616,3.9428544996553683,1300.1672056554735,True,1.882469009094768,0.9924216787474719,0.9924216787474719,15.21984744431915,3.2814599117605283,1.1447923731150098,0.6682857312616335,3.0743704486941326,5.827253915667441,27.41419763302907,15.39390249024995,C,s640e90,M,16,,,,,,
+v10-base-f16-s0,base,v10,base,role,16,0,35,640,0,32,16.247553132912547,29.3856309117921,15.592509944467894,7.915552641359517,25.96926118104117,35.768049237594376,3.609427087309504,11.005488298347762,10.472608746754718,24.716693446144724,18.725216639273963,44.28090228681332,51.28528397714306,32.040617610770916,12.069650971329445,29.938012640246264,16.4659193496392,27.309318312644553,15.705218273286977,13.496800373541276,24.743502261288487,13.383179753862324,5.744585866729609,21.325285462940297,30.327363613800934,2.625705390250357,8.502962312846472,7.154816417872077,20.296857184896623,13.812369526753809,38.066263987787856,44.61644483412141,30.261543090750564,9.10423161279013,25.07724726413187,13.618489342872984,23.159651411329428,13.112942356464782,33.15712913699144,18.804211549143695,10.752852041682779,34.7532802236324,19.83837138241215,12.23264332195605,27.715534917568608,15.426849996514836,7.659293868849757,29.69379097673462,16.624152249361167,9.11588663974101,27.63713096865069,15.578610751048041,20.009138626782054,12.394608289164298,25.22453789306876,14.610019389756104,29.115079658104392,16.01545797212245,2.267118,2.71094,6.596608,3.1907499997032573,,True,0.431411654220687,0.9431252299898545,0.9431252299898545,13.476753269497188,5.3352147209708605,0.8147910081300402,1.125690248287782,1.86714182556765,6.040697026577583,27.347042355534633,18.249706019086716,r2,abl35,baseline,32,,,,,,
+v10-base-f16-s1,base,v10,base,role,16,1,35,640,0,32,16.24175422773127,29.14756061416156,15.516116986904116,8.097048445814584,25.791213449663587,34.62524489220686,3.599378122740334,11.284693837339455,10.48647184017565,25.268498446329264,19.13974412601224,43.18235538768452,46.720154355693104,32.44823531049562,11.673000546429725,29.711261275514143,16.459071263323146,26.83411138509813,15.533539294828813,13.36190324665453,24.451668484707533,13.045847356602644,5.555013391241564,21.295019015273937,31.52503536025131,2.134638367075153,8.35687310536442,6.559302872117252,20.08335930268512,13.54063415558526,37.834935045389905,45.232666215323505,30.32681563313129,8.69499801432262,24.82730481512882,13.498365489059635,23.014330336701054,12.997063319777634,,,,,,,,,,,,,27.297925655291916,15.48051240194375,19.750974278213267,12.36048135552464,24.7109319352178,14.460016752727173,28.955713235888602,16.050641666684864,2.267118,2.71094,6.596608,3.220153999791364,,True,0.44675168805652193,0.9431252299898545,0.9431252299898545,13.518465532168392,5.107884957901618,0.8623111658258296,1.1317219268444205,1.91290848913075,5.939471743949504,28.377191861085954,17.590839568807212,r2,abl35,baseline,32,,,,,,
+v10-base-f16-s2,base,v10,base,role,16,2,35,640,0,32,16.170952543371676,29.330485882154182,15.310473953664916,8.087500163951573,25.398981794011828,35.74182276944749,3.7833613943410596,11.291482973284712,10.97180609785511,25.427919667368943,19.230569345765964,42.90396602033632,46.20562299530771,32.22102299332427,12.074372288865101,29.939340410847088,16.41216156737844,26.78355762334819,15.378301146834032,13.524346693105214,24.737463708215508,13.535815849320903,5.799147304066321,21.457577084938045,29.011877160918143,2.4153214806182497,8.59359619334954,6.984522840537102,20.505529398937266,13.878875468877455,38.061513653237796,43.01809381875647,30.137793253974355,8.77608681574255,25.0786032793131,13.651311199885207,23.128505164890473,13.095705644756539,,,,,,,,,,,,,27.521847022030677,15.419153834144087,20.15636927944422,12.412296637620138,25.11406650976123,14.48865340011864,29.138793408620657,15.95647058660766,2.267118,2.71094,6.596608,3.2186915013880935,,True,0.49092553701665664,0.9431252299898545,0.9431252299898545,13.567793197207301,5.332429534742332,0.8607528795790138,1.0312657915774786,2.083649219360513,5.833835220258472,27.996246791113144,17.673715991171242,r2,abl35,baseline,32,,,,,,
+v10-graft-f16-s0,graft,v10,graft,role,16,0,35,640,0,32,17.364610163442542,30.593285484434986,16.878109844328044,9.869020713423524,25.674436685811976,38.66163582561617,4.939567821718847,13.113663858790645,13.307025552892673,26.779246894062865,21.332108940315887,42.800028386532205,51.88044453133291,34.90262489370704,16.620202928244698,31.234085761400323,17.64552625438341,29.896205720531977,17.084958930188474,13.700411572476634,24.961712865406405,13.40151587237136,6.095843542555098,21.102468224652917,30.074069183625728,3.1292751679984203,8.907496377068991,8.455860672075035,20.51548554162729,14.359598881328528,37.3184336293226,44.749783232774675,31.963785407027366,12.050097146165598,25.315171768398848,13.833579415391306,24.804054613705386,13.852547951753689,33.775352088936394,19.38709130219402,11.884016111981873,34.696355930074326,20.115769671374302,13.318021274409016,27.706693241421497,15.412185429944847,8.011097342345504,30.011730039728864,16.845268061858583,9.550942488088603,28.720398424027,16.530519979080058,19.854770643393092,12.637581209245432,25.852692983749954,15.29220550552364,30.268422693380586,17.102308622007104,2.386296,2.919344,12.6685184,3.613916000176687,,True,0.8020543307728237,0.9431252299898545,0.9431252299898545,15.58447568242305,3.2487224898403078,0.9099284689345204,1.6070266117514898,2.001054265651046,6.283458897209602,28.416615505664023,16.834189289891444,r2,abl35,"graft, random-init level",32,,,,,,
+v10-graft-f16-s1,graft,v10,graft,role,16,1,35,640,0,32,17.045192104891456,29.993003390716844,16.582456501652512,9.122025212788321,25.25240319653377,35.83187581150501,4.68504052835056,12.23911689386363,13.009119017053127,25.63693309395046,20.38601842589945,41.92237483909199,50.55837614463392,34.139556833345296,15.33818785145367,30.588760193557047,17.302679934299945,29.069532148710003,16.55663893159726,13.748860754029707,25.135907913450794,13.440009504674478,6.0757091840555475,20.91387735829037,30.508905476968344,3.3586710585809505,8.816500031165345,9.051494487987584,20.188282975706997,14.273517214232351,36.86416745786585,44.58930813382395,31.385725707057922,11.405498413183587,25.516086041721103,13.902625729886006,24.618580563428733,13.630726434222534,,,,,,,,,,,,,28.099344991434634,16.219355019666377,19.521401908723874,12.444808837779362,25.279440460164725,14.996150164570812,29.651852980078385,16.790933231937903,2.386296,2.919344,12.6685184,3.657896500953939,,True,0.8709465273221334,0.9431252299898545,0.9431252299898545,16.826850643615344,3.1831429768143735,0.9809682522694736,1.4635151549970757,1.829143942136504,6.378378190083573,27.82877878750098,17.30546278670871,r2,abl35,"graft, random-init level",32,,,,,,
+v10-graft-f16-s2,graft,v10,graft,role,16,2,35,640,0,32,17.03900547515541,30.26843141635179,16.71807186729971,9.367741565862245,25.071048838431924,37.71396029818212,4.851961404863936,12.53760954185574,13.374456950423347,26.1047315568867,20.801784219720506,41.775174984737404,51.50807103804056,34.57604388184468,15.982805880362646,30.923629281818993,17.311130450831353,29.288221755701137,16.715861028999974,13.718551741110845,24.89039659704451,13.397160144334105,6.2181065456974505,21.077727631272616,30.076259869846627,3.083885297112401,9.078858188361897,8.459071829095043,20.723901132462473,14.484605728605684,36.99069648120539,45.20845385793936,31.963281321596032,11.754490076914259,25.237132855967936,13.855291158139526,25.02018835968392,13.87109507731046,,,,,,,,,,,,,28.47227777295559,16.24891757730595,19.708066472123182,12.39334344887937,25.479662250049522,14.973070295069334,29.93664512741578,16.670194894740956,2.386296,2.919344,12.6685184,3.6888985014229547,,True,0.895849870244662,0.9431252299898545,0.9431252299898545,16.287029602155336,3.062957566682904,0.9445194889037403,1.633088800514514,1.9858611415003793,6.274243156468195,28.147410167806626,17.026159698828806,r2,abl35,"graft, random-init level",32,,,,,,
+v10-graft-key-s0,"P2-Graft, key-matched transfer",v10,graft,key,16,0,35,640,4,32,17.004752816909058,29.972734806416145,16.736647969106,9.873281188710898,24.76479121463379,33.35129235494112,5.405812398887426,13.018947006476136,13.889439468619763,26.5891707041786,21.256364756183142,40.97226430900551,47.6286451415658,34.27151002664669,17.137985233264708,30.54244443900278,17.242029665759752,28.8573497245185,16.427235767253386,13.876769214382984,25.54802683116443,13.69134947404935,6.676797126067278,21.116005370527365,28.2099734359078,3.2205256393670036,9.668656258653769,8.873352956362744,21.921911924164156,15.415877534260916,37.462716234398954,42.686945679850716,31.74534769058773,12.212433344223953,25.919560228321597,14.020412210563038,24.047142110001303,13.292517224465472,,,,,,,,,,,,,28.245890432996042,16.285991013868536,19.311104786423503,12.309467096810254,25.304782796333374,15.040149121590066,29.779225917232075,16.761293512529402,2.386296,2.919344,12.6685184,3.684941499159322,,True,0.6742821194065942,0.6652556450104584,0.6652556450104584,16.318272848521737,3.4234968535187846,0.7581347762816506,1.3369488508698062,2.0465964862645976,6.125354328619515,28.54211667873237,16.957681144236,r2,abl35,"graft, key-matched transfer",32,,,,,,
+v10-graft-key-s1,"P2-Graft, key-matched transfer",v10,graft,key,16,1,35,640,4,32,16.919516765114835,30.004992664846032,16.483787358884303,9.60665507427852,25.34860428618153,33.474845172882894,4.805074331126072,12.866452146612989,12.991690886024642,26.32438718495428,20.817337045592993,42.23090699736105,48.51698106595903,33.82734142337548,15.641404234563113,30.63643908929668,17.181247160908462,28.356904453872943,16.06082873936151,13.9571712738,25.649355938248842,13.616877063030508,6.586523711824666,21.498264659072156,29.34782284398031,3.1499539262816763,9.555941631961197,8.829247325578159,21.51188782329838,15.094572856277006,38.18817695545105,45.21964825205803,31.32560391736542,11.5657423983206,26.03911551300362,14.106690992951176,24.236595000126623,13.298101214432673,,,,,,,,,,,,,28.240282326758265,16.163283618463602,19.910693543423967,12.480191060292785,25.47578589892699,14.978146121227095,29.702983263968736,16.61153832541213,2.386296,2.919344,12.6685184,3.6242374990251847,,True,0.8764826544788149,0.6652556450104584,0.6652556450104584,16.934963602199964,3.440066477150758,0.8531363377508399,1.1026350926144879,2.0747232416556045,6.137111428220464,27.618769711391586,17.37096879448319,r2,abl35,"graft, key-matched transfer",32,,,,,,
+v10-graft-key-s2,"P2-Graft, key-matched transfer",v10,graft,key,16,2,35,640,4,32,17.310205886568912,30.56877689322441,16.914125610514514,9.794904729987781,25.834166405329228,31.806853717134224,5.212587189549594,13.059196550716164,13.9690440379075,27.128106211791252,21.624459846418254,42.293455354475554,46.31504669057351,34.89472788153883,16.589871947661457,31.176787439673138,17.572461458237225,29.56937064771102,16.80433372335242,13.97821562405637,25.777647818726535,13.689721592292384,6.834905440625909,21.33980290886187,31.10870984848379,3.4212540672306337,9.784787923109986,9.218146851281677,22.108266194762535,15.701197536981748,37.82892575828671,47.35723162252481,31.876036272786173,12.662403816679236,26.16905854811963,14.127109807463645,24.64476971260972,13.480071143354325,,,,,,,,,,,,,28.972738317657797,16.591481759882594,20.327613575396725,12.77489469951633,26.056343139236976,15.349830054677929,30.257725682210502,17.016183000692234,2.386296,2.919344,12.6685184,3.7085309995745774,,True,0.871128745145268,0.6652556450104584,0.6652556450104584,15.78304442007573,3.4793762435566826,0.8465675007483284,1.304803458824697,2.0429547558073544,6.420462298261054,28.441124096874592,16.882823765331676,r2,abl35,"graft, key-matched transfer",32,,,,,,
+v10-graft-ws-s0,"P2-Graft, warm-started level",v10,graft,role_ws,16,0,35,640,5,32,18.04595240377278,31.67211131762403,17.595812624818077,11.103692835193414,25.776647322252543,34.146910157476285,5.753778807925502,14.66205271564599,15.078800749916788,29.123274590587496,23.448533851088534,42.18517483573151,46.96699618446495,36.36061572382921,18.42881078162666,32.31130819597212,18.316224201727128,31.63878465074633,18.207882333272703,14.473333678355708,26.268455806446468,14.195238100982982,7.422546088784814,21.571312834672405,28.799595887685374,4.236418904681075,10.564692239512516,10.71565677241389,23.02234623348496,16.480761693955923,37.63747120257914,42.699472728853024,33.66513793912172,13.905262356556157,26.704034708209974,14.64525154917608,25.950412460619038,14.563526063001653,,,,,,,,,,,,,29.856947143190045,17.266226961158296,20.892950034625375,13.164629467860134,26.84227438920373,15.892184162396216,31.487703152329182,17.85325060752067,2.386296,2.919344,12.6685184,3.663837998828967,,True,0.8093536115354962,0.9431252299898545,0.9431252299898545,16.111764905217925,3.2024532670811894,0.9121430176423004,1.5943519391811591,2.1465310275199414,5.937914894753028,29.218977791286854,16.107694502239376,r3,abl35,"graft, warm start",32,,,,,,
+v10-graft-ws-s1,"P2-Graft, warm-started level",v10,graft,role_ws,16,1,35,640,9,32,18.07646176021973,31.544787211414317,17.664750179893176,11.111262966205478,25.625322726853472,34.834276618427914,6.079258629360789,14.647931641372278,15.460866904847451,29.26001894596089,23.549043396550775,41.80303170111576,48.398628708831694,36.25233207142002,18.22285994487899,32.196396490341,18.352607123270275,31.584767605408885,18.299304605538147,14.351424365354804,25.865105802655947,14.295015959861507,7.272542314125824,21.45747153372864,29.47104009261439,3.6067233982942497,10.463202043952553,9.544242082170452,22.880850189996732,16.154478541779234,37.31001819029625,44.273133857882925,33.61135188626558,13.042616286497232,26.331708883722442,14.540383647522951,25.620596458279444,14.433355517569801,,,,,,,,,,,,,29.593820244108986,17.197050081640867,20.759974019553674,13.167188701610359,26.448081709073733,15.81340485982059,31.216140871983843,17.747352639566557,2.386296,2.919344,12.6685184,4.219217000354547,,True,0.9081780472066667,0.9431252299898545,0.9431252299898545,16.27374067688743,3.0527337498680076,0.8127517717195722,1.7522132366028877,2.058606063746428,5.948255062698966,28.85125239254609,16.39273979722734,r4,abl35,"graft, warm start",32,,,,,,
+v10-graft-ws-s2,"P2-Graft, warm-started level",v10,graft,role_ws,16,2,35,640,9,32,18.041344339818874,31.869478120542645,17.495469229696642,11.116691312879631,25.66450275400317,36.28442385124446,6.215797454268667,14.596584162209151,15.888708458168738,29.335591133558054,23.74297074593505,41.86485174415414,50.58552929272984,36.44619880299642,18.169890916339266,32.54997691061753,18.33235406806406,31.003981358726957,17.81111361315762,14.332266570381524,26.04041966374014,14.10092615537018,7.265747041940425,21.6270052522868,29.296467863822755,3.5446128238481216,10.467538261016085,9.680664176462354,23.035649485956082,16.259886907273344,37.64716679301099,44.35229118960756,33.41215815223002,13.114517716244215,26.51346173696409,14.521424211575146,25.43000844428548,14.245897946404071,,,,,,,,,,,,,30.136648298143076,17.247306808917394,21.98126784392081,13.560808679419385,27.233807949215972,16.007530745195254,31.607722967297676,17.815361358288,2.386296,2.919344,12.6685184,3.571024999473593,,True,0.8283869457907147,0.9431252299898545,0.9431252299898545,15.682822438587642,3.0196526799419985,0.9690742437183459,1.583125640804397,2.1215667970914325,6.122473265810548,28.625571384407856,16.331569503830103,r4,abl35,"graft, warm start",32,,,,,,
+v10-graftd-f16-s0,"P2-Graft deep, random-init level",v10,graftd,role,16,0,35,640,9,32,17.04765715452206,30.221655312306307,16.684125621034656,9.538619029959861,25.10276185416016,36.45535871457112,4.7901480692519485,12.758257101141583,13.339991104855239,26.537465898985253,21.05214490184719,42.11486595453984,52.289988084282555,34.27285838785997,15.854710732372421,30.812362760693794,17.295069623714244,29.589410085737345,16.919829299479662,13.759825705903534,25.103913800949474,13.46003904867665,6.36954943727556,21.155561979819836,30.520526063294312,3.1207190990396105,9.289684615120434,8.65846392760216,21.208181171861895,14.740021870484195,37.613619295653905,45.05562225286056,31.78771009925904,11.444308591726106,25.46348856620016,13.898725048038155,25.146044492517927,13.987911839693451,,,,,,,,,,,,,28.513718445730802,16.2969568187402,19.624135595070396,12.366499008909,25.45236865673613,15.002286543829568,29.994375258852656,16.799980964809794,2.40684,2.939952,13.7170944,4.043175500555662,,True,0.9068146310249965,0.9431252299898545,0.9431252299898545,16.325937894357637,3.1722082431238974,0.9256442371517828,1.5209132679015447,1.8782123720906228,6.409202687605678,27.798146667891714,17.41463648784311,r4,abl35,"deep graft, random-init level",32,,,,,,
+v10-graftd-ws-s0,"P2-Graft deep, warm-started",v10,graftd,role_ws,16,0,35,640,5,32,18.529524500236693,32.603002976522774,18.2020031751236,11.335854480358387,26.733448307908247,35.5284782188923,6.560690925382899,14.804470025184555,16.44050411045849,29.406328685122052,23.945565918974214,43.67209624605767,48.358047469714634,36.981329376769914,18.787368757086803,33.292533124217954,18.83668297258521,32.63122122597852,18.79365801308494,14.506669486914792,26.38532953142962,14.395609400666284,7.404459079323557,21.773080155454934,30.153218404309595,3.793804739631385,10.635168027768678,10.24464390131046,23.530156059553914,16.70948121065615,37.926481748386905,48.535144947663944,34.05028322408773,13.847844250386881,26.90124768154989,14.714478901170683,26.303198366467345,14.6545212906868,,,,,,,,,,,,,30.823331686388812,17.705571611891386,21.52642383173349,13.506863007176678,27.512304931391807,16.243215909944126,32.570582564113174,18.428633104184247,2.40684,2.939952,13.7170944,3.6546604987961473,,True,0.7659718270434274,0.9431252299898545,0.9431252299898545,15.393528571899743,3.1479795847681444,0.9154321453432672,1.7093491949309296,2.25888385142661,6.307519320366481,28.98124734606462,16.330272020586506,r3,abl35,"deep graft, warm start",32,,,,,,
+v10-graftd-ws-s1,"P2-Graft deep, warm-started",v10,graftd,role_ws,16,1,35,640,6,32,18.42708493488852,31.902976821024588,18.144821228044524,10.988307702610653,26.198650797946282,38.35281616814427,6.271660327038836,14.324551453277277,15.924642032966311,28.310161372022474,23.060798468358573,42.767214580813196,52.28419494039813,36.91605717284351,18.425888974456022,32.55002425336527,18.703445395660605,31.830952814224624,18.488797233184943,14.353521734837463,25.81194874639341,14.227119736737304,7.181080855585097,21.35683692767133,32.31823704569645,3.3236461656678222,10.444866158714927,9.185520862821308,22.665966983242576,15.994795869350268,36.94046547792469,48.19777597013159,34.00253038220701,13.832525414394834,26.242693946593082,14.52315920332172,26.16719638742733,14.684175922480044,,,,,,,,,,,,,30.214685831608147,17.642833893674602,21.214012267125256,13.531837754562492,26.70792179512181,16.136978948392468,31.5105961543478,18.04427126119792,2.40684,2.939952,13.7170944,3.6451890009630006,,True,0.8394761771625943,0.9431252299898545,0.9431252299898545,15.456768306335146,3.0137242210630255,0.8788545780848587,1.9513375779385775,1.996873165258247,6.168862579259265,29.185976127557385,16.241962089225066,r3,abl35,"deep graft, warm start",32,,,,,,
+v10-graftd-ws-s2,"P2-Graft deep, warm-started",v10,graftd,role_ws,16,2,35,640,6,32,18.468807575859252,32.339018838236946,17.93152127948127,11.270183893660109,26.56756787200058,33.7444925068988,5.920007360336328,14.969908067845578,15.566990873889438,29.85371238195097,23.9542996980008,43.127726484544894,47.50409122415468,36.56147069317756,17.842469101039864,33.05250483972099,18.77478295720586,32.34518310014612,18.62720851750104,14.687708869179003,26.521569443916736,14.6113697085929,7.560489172557511,21.875859311828794,28.648121126242447,3.725309947134953,10.880798099534811,9.936335288305084,23.75910668487068,16.866425420066058,37.83411102977746,45.36609079342198,33.5040367365054,13.363042701746242,26.944035868965937,14.853697043159968,26.212913509367585,14.653347923008214,,,,,,,,,,,,,30.45066845349166,17.642311731738015,21.408543420859303,13.480150001876948,27.095679545870492,16.170245127333384,31.945723817882737,18.18347147571304,2.40684,2.939952,13.7170944,3.6597905000235187,,True,0.8302689104610019,0.9431252299898545,0.9431252299898545,16.117800699280117,2.976052011275762,0.8972179393553219,1.5339908817736116,2.272669003223946,6.341825507720053,28.750090072654146,16.47189200711805,r3,abl35,"deep graft, warm start",32,,,,,,
+v10-graftd3-ws-s0,"P2-Graft 3x deep, warm-started",v10,graftd3,role_ws,16,0,35,640,9,32,18.29624846916443,32.10394870507943,17.858627818126884,11.529369191064825,26.253692759177316,33.63349902254707,6.112008060926366,15.178879604998036,15.52931203905554,30.025585927471855,24.168143748688145,42.4810645659375,47.09138776853167,36.976696990553606,18.686785303678413,32.66972593375706,18.53338577489841,32.314606799842004,18.621016663043687,14.659525513013364,26.549389632907396,14.552986889968494,7.565189604609074,22.070998104130858,29.593325972789035,3.6606525150029676,10.946943686922195,9.659182695081993,24.097378868490875,16.892264556922775,38.27960062253676,44.5014059141633,34.08319655149717,13.76203015121879,27.0686203493358,14.876851142378234,26.436516825104068,14.80857905039811,,,,,,,,,,,,,30.194039129623402,17.433039377404793,21.427785079760156,13.454836949347623,27.308155341157015,16.139280663713652,31.879872630860856,18.161987083826173,2.427384,2.96056,14.7656704,3.7325590001273667,,True,0.8999860511223475,0.9431252299898545,0.9431252299898545,16.042742466176833,2.9255596530659744,0.8125553934254413,1.638868010005183,2.023113384560517,6.019505784013276,29.183180007791854,16.088522380082807,r4,abl35,"3x deep graft, warm start",32,,,,,,
+v10-inj16-f16-s0,detail injection (16 ch),v10,inj16,role,16,0,35,640,5,32,17.382005586374873,30.93601303202156,16.691637883403747,8.585799480234323,26.955937079023514,46.62340148138944,3.840315202081046,11.904111136552043,11.062970043158861,26.411670478459538,20.023015374344137,45.38009210906819,61.36823211073757,32.91701988241006,12.519432335975292,31.490962711843167,17.597980633056228,27.753843937735546,16.193727538132368,14.067326407518394,25.629455586455975,13.858824460320793,5.885797488670013,21.885648215179224,34.53119814079606,2.485345052715444,8.786693734918291,7.297769635052581,21.03223528338917,14.172526872062582,39.189246075996685,50.901829480784954,30.762874103211978,9.592895901291001,26.01533456722925,14.210470603694006,23.351763309400862,13.31051452699256,,,,,,,,,,,,,29.195942752938443,16.71031341482956,21.20729078279455,13.391508588508675,26.872368045838467,15.789608290069356,30.62894281312246,17.009310454534212,2.297534,2.767484,6.8585344,3.239802999814856,,True,0.482413391802046,0.9860960069291093,0.9860960069291093,13.234205183757883,5.567660651352188,0.9395313845303193,0.8338335116705089,2.0104405674725747,5.980967919789055,27.57883845312696,18.26084095684872,r3,abl35,detail injection 16,32,,,,,,
+v10-inj16-f16-s1,detail injection (16 ch),v10,inj16,role,16,1,35,640,11,32,17.116267847049663,30.827195136399922,16.20011675615865,8.61928433306821,26.56095541244492,44.18614087923366,3.8431353910310566,11.982409243969409,11.475885989244453,26.511044399336658,20.12421954502842,45.30438771196902,58.95371767585586,33.1234200668815,12.415397236877249,31.439542722770987,17.355531754486808,28.02412844520053,16.112329518071462,13.999155176614767,25.53629914838551,13.769066975955349,5.923090687251221,21.80458114122601,34.136171413294605,2.700287907267759,8.740457216606453,7.624392887542046,20.831740779466884,14.225208311900502,39.07539296465912,49.78265130996566,30.83445274341275,9.363917763343,25.906067592402458,14.134109541620765,23.614305356701347,13.45746457391547,,,,,,,,,,,,,28.896564105415845,16.37478761657515,21.17136823264604,13.183423821436458,26.225006292217916,15.317952917179548,30.701421599708578,16.902274159477706,2.297534,2.767484,6.8585344,3.264193997893017,,True,0.5142522160874473,0.9860960069291093,0.9860960069291093,13.187670314113966,5.294563515269473,0.9899400941520469,0.8164740881567099,2.125976128200584,6.011230943595272,27.984686051718896,17.86371698359404,r5,abl35,detail injection 16,32,,,,,,
+v10-inj16-f16-s2,detail injection (16 ch),v10,inj16,role,16,2,35,640,11,32,16.976521491532587,30.719707059306618,16.03043734607976,8.496615528719662,26.008683041372414,41.53802267478693,3.9003422818969957,11.824359454185064,11.575618710941487,26.21284895857931,19.97567795870716,44.773548594771235,55.57899850960022,32.952283583580396,12.797161621253483,31.347638047720533,17.221233415898446,27.77490354901345,15.837413198801228,14.159832124205469,25.830025560351977,13.945529897757378,5.984532692927579,21.984276283684604,33.531755852936755,2.5345499701085155,8.879471463138563,7.404803186103852,21.12748765302066,14.30389161623471,39.34402728835783,48.67892659270708,30.75135870349499,9.263087767027072,26.212198063432563,14.302209092581203,23.69370576357609,13.352993180731437,,,,,,,,,,,,,29.011074990345243,16.289522682884346,21.468848814512643,13.161809794888718,26.252359727455648,15.19900338118491,30.53974453607099,16.751563775658596,2.297534,2.767484,6.8585344,3.2529020008951193,,True,0.48872511784235634,0.9860960069291093,0.9860960069291093,13.239616289847852,5.550017549474262,0.9984252395265578,0.8791413148613643,2.0979702728779017,5.7332515956664025,27.894154326832002,17.849068021785328,r5,abl35,detail injection 16,32,,,,,,
+v10-inj8-f16-s0,detail injection (8 ch),v10,inj8,role,16,0,35,640,11,32,16.411476627582644,29.39497282651793,15.636180507752709,8.064690791337036,25.922290367121853,36.50232714319604,3.5826443454172185,11.231374137399117,10.555682841811555,24.812041495451275,18.85271697679207,43.924311137702986,50.650178163283144,31.902426044208564,12.420088725138417,29.920975980195834,16.61631487099561,26.623180783439476,15.38570500530656,13.578191077485249,24.90094581711887,13.381830883530748,5.733917624066528,21.274875661978275,31.683681427755072,2.7008504386305208,8.47338137169471,7.600808154739794,20.37549034337988,13.881583483391443,37.98529316104029,48.63181651186061,30.421137585260023,9.419406711035693,25.26178325644773,13.707899732645496,22.99506014462543,13.052726745472462,,,,,,,,,,,,,27.61717866508384,15.732099945841501,20.05359811776146,12.514996327411994,25.23379906410791,14.749645778567192,29.142860447426568,16.12671692878869,2.28207,2.7387,6.7256768,3.277138497651322,,True,0.4851263664166133,0.9431252299898545,0.9431252299898545,13.995734422419414,5.259756630501823,0.8111865890859811,0.9394370115233137,1.9611719912642407,5.98609258534702,26.94166083684841,18.530245076913115,r5,abl35,detail injection 8,32,,,,,,
+v10-inj32-f16-s0,detail injection (32 ch),v10,inj32,role,16,0,35,640,11,32,17.124956664604543,30.864841306507767,16.521104661159868,8.610963621470672,26.431468185117584,40.7989558930469,3.8004607419427896,11.951803613095228,11.408259631800004,26.509153693160297,20.243266812327146,44.79541024003131,53.87574664447795,32.82990500592034,12.644559202303093,31.433410399983035,17.339668997570563,27.976112320697638,16.045832406781706,14.299332907378984,25.974931189070855,14.094665384423147,6.016772818216406,22.213014266590196,35.32536422133028,2.6261067283689288,8.929067799823558,7.457560361100407,21.314584910726552,14.392107269499302,39.691412251683964,50.41380071648275,30.771209370976454,9.693207518726489,26.35607225068609,14.442342281622746,23.95178897858441,13.628399681855777,,,,,,,,,,,,,29.068883560990717,16.45006244469265,21.38811239559478,13.238787469094968,26.486488449231217,15.400696266591437,30.52290105099776,16.824613950868866,2.329998,2.828124,7.135616,3.2640785011608386,,True,0.46923628707726794,0.9860960069291093,0.9860960069291093,13.590195801974659,5.475696755961053,0.9148737354918737,0.8230645014918707,2.0512552423311234,5.933351160259392,27.749020079630846,17.953925812426704,r5,abl35,detail injection 32,32,,,,,,
+v10-assist32-f16-s0,P2-assisted P3 (32 ch),v10,assist32,role,16,0,35,640,5,32,17.819584085247985,31.825100194035098,17.210340238901246,9.068860714157378,27.30319048820848,46.99776487777834,4.381897492089588,12.453910099289043,12.413030729957462,27.402724428686575,21.086537357852293,45.93572174146994,63.0336787631127,33.73158809509064,13.372395828085281,32.37984829709948,18.03527124118985,28.747107134943906,16.547085661053195,14.494366425445737,26.175786789859618,14.306562568365555,6.216874466215393,22.39631898671042,35.06557366532712,2.832428179213305,9.18433328613438,7.8806170988641675,21.39857830056063,14.595350620235937,39.56996544145021,52.18783453062594,31.253995663413203,10.007645118010691,26.56556220955358,14.641220194832142,23.988524887707623,13.739653332763949,,,,,,,,,,,,,29.964462036666923,17.120841669383175,21.97628174913869,13.680293372867888,27.42436992049423,16.07886854165759,31.377598881234466,17.367421397522023,2.370126,2.868444,8.8264448,3.365164498973172,,True,0.50160701599386,0.9860960069291093,0.9860960069291093,13.469789841359304,5.217576320325126,0.941041684375552,0.7879999805374531,2.102692973518945,6.0482647572241355,27.580840400024304,17.995044327085797,r3,abl35,P2-assisted P3,32,,,,,,
+v10-inj16-f640e90-s0,"detail injection (16 ch), 640 px, 90 epochs",v10,inj16,role,16,0,90,640,10,32,18.314793318568576,32.89922268984311,17.160521646153164,9.72556196339105,27.896019755999347,41.043741867472825,4.795302815766026,13.253329827557891,13.574032953706014,29.15109043586265,22.52561717123657,46.698070740868175,58.76391597166395,34.05903413865786,14.07917345877391,33.53061010514363,18.55618706330302,29.975491968428177,17.250472875797996,14.431746395360994,26.292211930475908,14.172447711963567,6.393150212506354,22.25153521111222,34.90680626568907,2.9662892940015584,9.398396637177342,8.349551497599156,22.197283624480722,15.248089990221878,39.54559514505313,52.001121014541155,31.303773278521028,10.548070664299368,26.684608170547662,14.573979242701984,24.015775623697984,13.656438630194184,36.939430838499106,21.004844798594252,13.098454194651834,38.23114776631918,22.05246178495229,14.206324350165827,29.77179808474762,16.670561741727617,8.530947571364463,31.86695372294158,17.951486300476798,10.217216891986837,31.03243776329802,17.599405075741576,23.713527088687922,14.644550529438114,28.548277722941428,16.636522431850064,32.73527374521018,18.08711406153536,2.297534,2.767484,6.8585344,3.2549050010857172,,True,1.4081377771165635,0.9860960069291093,0.9860960069291093,13.109891112574218,5.468543623049619,0.9956014237258373,0.8444672862481539,2.1926013038115,5.951766495464419,27.595826815107394,17.954132548289998,r5,inj90_640,inj16,32,,,,,,
+v10-inj16-f640e90-s1,"detail injection (16 ch), 640 px, 90 epochs",v10,inj16,role,16,1,90,640,10,32,18.168506524838293,32.46456900510446,17.23410429811085,9.545579327190106,27.988973242292857,38.764510671047645,4.383787183939234,13.099727950360899,12.632554563780493,28.380753578258723,21.805401101674395,46.76666126800068,53.78103589775712,33.647331951921394,13.90857378696003,33.14131769974062,18.43853218210978,29.499666729853725,17.153468179745406,14.355050160495633,26.214011071967256,13.970906449245671,6.471605161295489,22.30889384860139,32.598735804853966,2.8990689669555136,9.550799204681205,8.24284137437564,22.318595206638662,15.245663717313326,39.873158485386526,48.60416853732337,30.9634128962408,10.783585066141317,26.63691548930461,14.516873300872751,23.949425861265663,13.559451347743732,36.75697223775398,20.914543020285993,12.728404739739762,37.502730983911434,21.577064067307877,13.586806917526964,29.642236995410148,16.50663096085135,8.55639288924247,31.610836830430504,17.724329392328407,10.181135509329762,30.756197382835325,17.496261120289955,23.3817318466088,14.538845804372972,28.23451287230968,16.49233491515995,32.33947571053173,17.938652307431,2.297534,2.767484,6.8585344,3.263443501055008,,True,0.9991749967469109,0.9860960069291093,0.9860960069291093,12.850341566109357,5.46821319106521,1.009343256579669,0.7387084914341315,2.3156277006755133,6.016371028730099,27.04038148994504,18.310188226763827,r5,inj90_640,inj16,32,,,,,,
+v10-inj16-f896e90-s0,"detail injection (16 ch), 896 px, 90 epochs",v10,inj16,role,16,0,90,896,10,32,23.590616557437453,40.42063923266756,23.460850235360187,14.563076935712097,34.305878395398466,46.14979641892551,7.740959297187831,19.17758813013534,20.04100756093402,37.08046712128825,30.080162620943128,54.336238392513216,65.22331979296891,41.25141644537062,21.401354236228446,41.35431651658968,23.99437264342459,38.36053991847888,22.766397955687935,18.331522893935492,32.452580217735246,18.18413088761484,9.629349745392911,27.003386936753177,39.50362065829371,4.804140970921482,13.792214492255336,12.657905985609826,29.674662942273205,21.35178238996673,45.7999703945085,54.38092980626629,37.19655883050084,15.887150527998225,33.07583986637997,18.581572710345,30.348596351936152,17.506475145594237,,,,,,,,,,,,,38.29709824737938,22.68335707254449,30.259881089070834,19.163926559565997,34.72098515188308,21.09834006818007,40.3381123463614,23.30665109358907,2.297534,2.767484,13.558332928,3.268094500526786,,True,1.9310362188021342,0.9860960069291093,0.9860960069291093,14.296724355573687,3.9940264852887566,1.0396752803089484,0.9558170070497951,2.757667724028053,5.509007826170929,27.99520235149086,15.710400709723658,r5,inj90_896,inj16,32,42.55573654147321,25.03799210413778,16.35572820718286,34.48924676495979,19.675162460533244,10.874374434582599
+v10-inj16-f1280e90-s0,"detail injection (16 ch), 1280 px, 90 epochs",v10,inj16,role,16,0,90,1280,10,32,28.699728254707306,47.40353637948561,29.205488782170498,19.811837852680362,39.84416387680024,47.49515059143142,11.46402909627381,25.225345424491387,27.227042762386617,45.30659073415484,38.19113315870436,60.543666765140195,60.15030436269762,47.343162153615474,29.562593789251533,48.51078448308076,29.207688200587555,45.71728767953452,27.82013853547841,22.212771434790916,38.302305775844566,22.27597109828467,13.050283525920126,31.93477755916377,42.379496454426665,7.198896640336097,18.049743433723407,18.407463945747953,36.5392394955903,27.621430444759866,51.720332908656154,57.804614857119965,42.54745037104916,22.32984488936141,39.129988031238454,22.565997061696226,36.195415392364325,21.262371298864984,,,,,,,,,,,,,45.11575413845366,27.597442331757073,36.62764178193657,23.64027144916476,40.57417835977263,25.57619607852336,47.13969571950128,28.449653579444657,2.297534,2.767484,28.1714176,3.3594399992580293,,True,2.994976633588473,0.9860960069291093,0.9860960069291093,14.27127300736457,3.010852082917566,1.0006352205099418,1.0020863589196054,3.118631970586705,5.210906402431682,27.34877502659603,13.9193576907049,r5,inj90_1280,inj16,32,,,,,,

results/runs_summary.csv ADDED Viewed

	@@ -0,0 +1,52 @@

+run_id,cond,model,family,variant,transfer,seed,epochs,imgsz,train_batch,params_deploy_M,gflops,val_AP,val_AP50,val_APs,test_AP,test_AP50,test_APs,latency_ms,throughput_b16,src
+v10-base-f640e90-s0,n640e90,base,v10,base,role,0,90,640,32,2.267,6.597,17.932,32.063,9.252,14.033,25.661,6.273,3.283,,r3
+v10-base-f640e90-s1,n640e90,base,v10,base,role,1,90,640,32,2.267,6.597,17.876,31.898,9.233,14.034,25.684,6.223,3.667,,r4
+v10-base-f640e90-s2,n640e90,base,v10,base,role,2,90,640,32,2.267,6.597,17.457,31.344,9.061,14.196,25.863,6.259,3.202,,r4
+v10-graftd-f640e90-s0,n640e90,M,v10,graftd,role_ws,0,90,640,32,2.407,13.717,20.74,36.147,13.128,15.561,28.275,8.33,3.704,,r3
+v10-graftd-f640e90-s1,n640e90,M,v10,graftd,role_ws,1,90,640,32,2.407,13.717,20.584,35.784,12.916,15.8,28.547,8.218,3.635,,r4
+v10-graftd-f640e90-s2,n640e90,M,v10,graftd,role_ws,2,90,640,32,2.407,13.717,20.6,35.944,13.327,15.949,28.827,8.415,3.702,,r4
+v10-base-f16-896-e90-s0,n896e90,base,v10,base,role,0,90,896,32,2.267,13.045,23.28,39.847,14.332,18.052,32.146,9.522,3.518,2546.456,A
+v10-base-f16-896-e90-s1,n896e90,base,v10,base,role,1,90,896,32,2.267,13.045,23.155,39.414,14.165,18.203,32.448,9.66,3.461,2543.207,A
+v10-base-f16-896-e90-s2,n896e90,base,v10,base,role,2,90,896,32,2.267,13.045,23.26,39.692,14.2,18.233,32.325,9.612,3.459,2191.85,A
+v10-graftd-ws-896-e90-s0,n896e90,M,v10,graftd,role_ws,0,90,896,16,2.407,27.001,23.977,40.524,15.545,18.498,32.592,10.155,4.032,1232.045,A
+v10-graftd-ws-896-e90-s1,n896e90,M,v10,graftd,role_ws,1,90,896,16,2.407,27.001,24.177,40.904,15.896,19.092,33.649,10.502,4.047,1234.616,A
+v10-graftd-ws-896-e90-s2,n896e90,M,v10,graftd,role_ws,2,90,896,16,2.407,27.001,24.063,40.518,15.894,18.63,32.923,10.287,4.042,1234.715,A
+v10-graftd-ws-896-e90-b32-s1,n896e90b32,M,v10,graftd,role_ws,1,90,896,32,2.407,27.001,25.255,42.377,17.571,19.513,34.448,11.378,3.833,1240.206,B
+v10-base-f16-1280-e90-s0,n1280e90,base,v10,base,role,0,90,1280,8,2.267,27.124,28.437,46.923,19.212,22.448,38.612,12.785,3.372,1212.117,B
+v10-graftd-ws-1280-e90-s0,n1280e90,M,v10,graftd,role_ws,0,90,1280,8,2.407,55.606,29.138,47.749,20.44,22.321,38.46,13.457,3.92,532.389,B
+v10-base-f1536e90-s0,n1536e90,base,v10,base,role,0,90,1536,32,2.267,39.681,30.292,49.419,21.518,23.891,40.826,14.849,3.284,,r5
+v10-base-f16-640-e150-s0,n640e150,base,v10,base,role,0,150,640,32,2.267,6.597,18.368,32.729,9.999,14.459,26.402,6.65,3.543,4477.617,B
+v10-graftd-ws-640-e150-s0,n640e150,M,v10,graftd,role_ws,0,150,640,32,2.407,13.717,19.858,34.73,12.372,15.629,28.059,8.264,3.856,2494.086,B
+v10s-base-f16-640-e90-s0,s640e90,base,v10s,base,role,0,90,640,16,7.222,21.552,22.001,38.247,13.375,17.414,30.889,8.628,3.43,2410.333,C
+v10s-base-f16-640-e90-s1,s640e90,base,v10s,base,role,1,90,640,16,7.222,21.552,22.108,38.312,13.158,17.358,31.074,8.87,3.438,2408.762,C
+v10s-base-f16-640-e90-s2,s640e90,base,v10s,base,role,2,90,640,16,7.222,21.552,21.846,37.912,13.296,17.603,31.304,8.751,3.412,2402.654,C
+v10s-graftd-ws-640-e90-s0,s640e90,M,v10s,graftd,role_ws,0,90,640,16,7.579,39.774,22.077,38.164,13.514,17.477,31.158,9.04,4.021,1300.81,C
+v10s-graftd-ws-640-e90-s1,s640e90,M,v10s,graftd,role_ws,1,90,640,16,7.579,39.774,22.51,38.737,13.508,17.552,31.454,9.234,4.521,1301.249,C
+v10s-graftd-ws-640-e90-s2,s640e90,M,v10s,graftd,role_ws,2,90,640,16,7.579,39.774,25.28,42.685,17.374,19.545,34.414,11.134,3.943,1300.167,C
+v10-base-f16-s0,abl35,baseline,v10,base,role,0,35,640,32,2.267,6.597,16.248,29.386,7.916,13.497,24.744,5.745,3.191,,r2
+v10-base-f16-s1,abl35,baseline,v10,base,role,1,35,640,32,2.267,6.597,16.242,29.148,8.097,13.362,24.452,5.555,3.22,,r2
+v10-base-f16-s2,abl35,baseline,v10,base,role,2,35,640,32,2.267,6.597,16.171,29.33,8.088,13.524,24.737,5.799,3.219,,r2
+v10-graft-f16-s0,abl35,"graft, random-init level",v10,graft,role,0,35,640,32,2.386,12.669,17.365,30.593,9.869,13.7,24.962,6.096,3.614,,r2
+v10-graft-f16-s1,abl35,"graft, random-init level",v10,graft,role,1,35,640,32,2.386,12.669,17.045,29.993,9.122,13.749,25.136,6.076,3.658,,r2
+v10-graft-f16-s2,abl35,"graft, random-init level",v10,graft,role,2,35,640,32,2.386,12.669,17.039,30.268,9.368,13.719,24.89,6.218,3.689,,r2
+v10-graft-key-s0,abl35,"graft, key-matched transfer",v10,graft,key,0,35,640,32,2.386,12.669,17.005,29.973,9.873,13.877,25.548,6.677,3.685,,r2
+v10-graft-key-s1,abl35,"graft, key-matched transfer",v10,graft,key,1,35,640,32,2.386,12.669,16.92,30.005,9.607,13.957,25.649,6.587,3.624,,r2
+v10-graft-key-s2,abl35,"graft, key-matched transfer",v10,graft,key,2,35,640,32,2.386,12.669,17.31,30.569,9.795,13.978,25.778,6.835,3.709,,r2
+v10-graft-ws-s0,abl35,"graft, warm start",v10,graft,role_ws,0,35,640,32,2.386,12.669,18.046,31.672,11.104,14.473,26.268,7.423,3.664,,r3
+v10-graft-ws-s1,abl35,"graft, warm start",v10,graft,role_ws,1,35,640,32,2.386,12.669,18.076,31.545,11.111,14.351,25.865,7.273,4.219,,r4
+v10-graft-ws-s2,abl35,"graft, warm start",v10,graft,role_ws,2,35,640,32,2.386,12.669,18.041,31.869,11.117,14.332,26.04,7.266,3.571,,r4
+v10-graftd-f16-s0,abl35,"deep graft, random-init level",v10,graftd,role,0,35,640,32,2.407,13.717,17.048,30.222,9.539,13.76,25.104,6.37,4.043,,r4
+v10-graftd-ws-s0,abl35,"deep graft, warm start",v10,graftd,role_ws,0,35,640,32,2.407,13.717,18.53,32.603,11.336,14.507,26.385,7.404,3.655,,r3
+v10-graftd-ws-s1,abl35,"deep graft, warm start",v10,graftd,role_ws,1,35,640,32,2.407,13.717,18.427,31.903,10.988,14.354,25.812,7.181,3.645,,r3
+v10-graftd-ws-s2,abl35,"deep graft, warm start",v10,graftd,role_ws,2,35,640,32,2.407,13.717,18.469,32.339,11.27,14.688,26.522,7.56,3.66,,r3
+v10-graftd3-ws-s0,abl35,"3x deep graft, warm start",v10,graftd3,role_ws,0,35,640,32,2.427,14.766,18.296,32.104,11.529,14.66,26.549,7.565,3.733,,r4
+v10-inj16-f16-s0,abl35,detail injection 16,v10,inj16,role,0,35,640,32,2.298,6.859,17.382,30.936,8.586,14.067,25.629,5.886,3.24,,r3
+v10-inj16-f16-s1,abl35,detail injection 16,v10,inj16,role,1,35,640,32,2.298,6.859,17.116,30.827,8.619,13.999,25.536,5.923,3.264,,r5
+v10-inj16-f16-s2,abl35,detail injection 16,v10,inj16,role,2,35,640,32,2.298,6.859,16.977,30.72,8.497,14.16,25.83,5.985,3.253,,r5
+v10-inj8-f16-s0,abl35,detail injection 8,v10,inj8,role,0,35,640,32,2.282,6.726,16.411,29.395,8.065,13.578,24.901,5.734,3.277,,r5
+v10-inj32-f16-s0,abl35,detail injection 32,v10,inj32,role,0,35,640,32,2.33,7.136,17.125,30.865,8.611,14.299,25.975,6.017,3.264,,r5
+v10-assist32-f16-s0,abl35,P2-assisted P3,v10,assist32,role,0,35,640,32,2.37,8.826,17.82,31.825,9.069,14.494,26.176,6.217,3.365,,r3
+v10-inj16-f640e90-s0,inj90_640,inj16,v10,inj16,role,0,90,640,32,2.298,6.859,18.315,32.899,9.726,14.432,26.292,6.393,3.255,,r5
+v10-inj16-f640e90-s1,inj90_640,inj16,v10,inj16,role,1,90,640,32,2.298,6.859,18.169,32.465,9.546,14.355,26.214,6.472,3.263,,r5
+v10-inj16-f896e90-s0,inj90_896,inj16,v10,inj16,role,0,90,896,32,2.298,13.558,23.591,40.421,14.563,18.332,32.453,9.629,3.268,,r5
+v10-inj16-f1280e90-s0,inj90_1280,inj16,v10,inj16,role,0,90,1280,32,2.298,28.171,28.7,47.404,19.812,22.213,38.302,13.05,3.359,,r5

sessionA-20261103-0052/START.txt DELETED Viewed

	@@ -1 +0,0 @@
1	- started 2026-11-03 00:57:02

sessionA-20261103-0052/calibration.json DELETED Viewed

@@ -1,7 +0,0 @@
-{
- "base": 18.47635507583618,
- "base_startup_s": 9.26948881149292,
- "graft": 45.690016746520996,
- "graft_startup_s": 5.562558889389038,
- "s_per_epoch": 45.690016746520996
-}

sessionA-20261103-0052/logs/autopilot.log DELETED Viewed

@@ -1,39 +0,0 @@
-[00:52:16] [autopilot] environment check / repair ...
-[00:52:25] [autopilot] environment check / repair: ok (10s)
-[00:52:25] [autopilot] Hugging Face access (results are pushed there during the run) ...
-[00:52:26] [autopilot] Hugging Face access (results are pushed there during the run): ok (1s)
-[00:52:26] [autopilot] data (download, convert, pre-resize) ...
-[00:53:07] extracting VisDrone2019-DET-train.zip ...
-[00:53:32] prepared train @ 640px: 6471 images
-[00:53:35] extracting VisDrone2019-DET-val.zip ...
-[00:53:39] prepared val @ 640px: 548 images
-[00:53:48] extracting VisDrone2019-DET-test-dev.zip ...
-[00:53:54] prepared test-dev @ 640px: 1610 images
-[00:54:14] prepared train @ 896px: 6471 images
-[00:54:17] prepared val @ 896px: 548 images
-[00:54:21] prepared test-dev @ 896px: 1610 images
-[00:54:24] prepared val @ 1024px: 548 images
-[00:54:31] prepared test-dev @ 1024px: 1610 images
-[00:54:31] [autopilot] data (download, convert, pre-resize): ok (124s)
-[00:54:31] [autopilot] smoke test (tiny end-to-end run of every model type on this machine) ...
-[00:55:48] [autopilot] smoke test (tiny end-to-end run of every model type on this machine): ok (78s)
-[00:55:48] [autopilot] calibration (seconds per epoch on this machine) ...
-[00:56:53] [autopilot] calibration (seconds per epoch on this machine): ok (65s)
-[00:56:53] [autopilot] shared inputs (checkpoints) ...
-[00:56:55] [autopilot] shared inputs (checkpoints): ok (2s)
-[00:56:55] [autopilot] launch the background worker ...
-[00:56:55] [autopilot] launch the background worker: ok (0s)
-[00:56:55] [autopilot] environment check / repair ...
-[00:57:02] [autopilot] environment check / repair: ok (7s)
-[00:57:02] [autopilot] Hugging Face access (results are pushed there during the run) ...
-[00:57:03] [autopilot] Hugging Face access (results are pushed there during the run): ok (1s)
-[00:57:03] [autopilot] data (download, convert, pre-resize) ...
-[00:57:03] [autopilot] data (download, convert, pre-resize): ok (0s)
-[00:57:03] [autopilot] smoke test (tiny end-to-end run of every model type on this machine) ...
-[00:58:39] [autopilot] smoke test (tiny end-to-end run of every model type on this machine): ok (96s)
-[00:58:39] [autopilot] calibration (seconds per epoch on this machine) ...
-[00:58:39] [autopilot] calibration (seconds per epoch on this machine): ok (0s)
-[00:58:39] [autopilot] shared inputs (checkpoints) ...
-[00:58:39] [autopilot] shared inputs (checkpoints): ok (0s)
-[00:58:39] [autopilot] launch the background worker ...
-[00:58:39] [autopilot] launch the background worker: ok (0s)

sessionA-20261103-0052/logs/calibrate.log DELETED Viewed

@@ -1,156 +0,0 @@
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.198 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=32, bgr=0.0, box=7.5, cache=ram, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s640.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=3, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=0.1, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-base.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=calib-base, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=13, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/calib-base, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=6, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23        [16, 19, 22]  1    865228  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256]]
-v10-base summary: 223 layers, 2,710,940 parameters, 2,710,924 gradients, 8.5 GFLOPs
-Freezing layer 'model.23.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 844.3±375.7 MB/s, size: 95.5 KB)
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000137_02220_d_0000163.jpg: 1 duplicate labels removed
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000140_00118_d_0000002.jpg: 1 duplicate labels removed
-[34m[1mtrain: [0mNew cache created: /home/marimo/graft_p2_work/data/train_s640/labels.cache
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 337.8±118.6 MB/s, size: 84.3 KB)
-[34m[1mval: [0mNew cache created: /home/marimo/graft_p2_work/data/val_s640/labels.cache
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 95 weight(decay=0.0), 108 weight(decay=0.0005), 107 bias(decay=0.0)
-WARNING ⚠️ Dataset images contain up to 902 objects (train=902, val=317), but max_det=300. This mismatch can cap recall and produce invalid validation metrics. Raising it may increase validation cost but cannot increase model or export capacity, which may cap recall. Setting max_det=902 to match the observed maximum.
-Using 647 train, 548 val images for fraction=0.1 at imgsz=640
-Using 6 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/calib-base[0m
-Starting training for 3 epochs...
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all        548      38759      0.118     0.0586     0.0212     0.0128
-3 epochs completed in 0.006 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-base/weights/last.pt, 5.7MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-base/weights/best.pt, 5.7MB
-Validating /home/marimo/graft_p2_work/runs/calib-base/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-base summary (fused): 99 layers, 2,267,118 parameters, 0 gradients, 6.6 GFLOPs
-                   all        548      38759      0.118     0.0587     0.0212     0.0128
-Speed: 0.0ms preprocess, 3.3ms inference, 0.0ms loss, 0.6ms postprocess per image
-[00:56:27] [calib-base] trained 3 epochs in 0h00m
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.198 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=32, bgr=0.0, box=7.5, cache=ram, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s640.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=3, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=0.1, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-graft.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=calib-graft, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=13, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/calib-graft, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=6, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23                  16  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 24             [-1, 2]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 25                  -1  1     31104  ultralytics.nn.modules.block.C2f             [96, 64, 1]
- 26    [16, 19, 22, 25]  1   1042528  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256, 64]]
-v10-graft summary: 261 layers, 2,919,344 parameters, 2,919,328 gradients, 19.2 GFLOPs
-Freezing layer 'model.26.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 1519.2±377.2 MB/s, size: 101.2 KB)
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000137_02220_d_0000163.jpg: 1 duplicate labels removed
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000140_00118_d_0000002.jpg: 1 duplicate labels removed
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 339.2±133.1 MB/s, size: 86.9 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 111 weight(decay=0.0), 128 weight(decay=0.0005), 127 bias(decay=0.0)
-WARNING ⚠️ Dataset images contain up to 902 objects (train=902, val=317), but max_det=300. This mismatch can cap recall and produce invalid validation metrics. Raising it may increase validation cost but cannot increase model or export capacity, which may cap recall. Setting max_det=902 to match the observed maximum.
-Using 647 train, 548 val images for fraction=0.1 at imgsz=640
-Using 6 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/calib-graft[0m
-Starting training for 3 epochs...
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all        548      38759     0.0826     0.0571     0.0179     0.0118
-3 epochs completed in 0.005 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-graft/weights/last.pt, 6.3MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-graft/weights/best.pt, 6.3MB
-Validating /home/marimo/graft_p2_work/runs/calib-graft/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-graft summary (fused): 113 layers, 2,386,296 parameters, 0 gradients, 12.7 GFLOPs
-                   all        548      38759     0.0825     0.0571     0.0179     0.0118
-Speed: 0.0ms preprocess, 0.7ms inference, 0.0ms loss, 0.6ms postprocess per image
-[00:56:52] [calib-graft] trained 3 epochs in 0h00m
-RESULT_JSON {"base": 18.47635507583618, "base_startup_s": 9.26948881149292, "graft": 45.690016746520996, "graft_startup_s": 5.562558889389038, "s_per_epoch": 45.690016746520996}

sessionA-20261103-0052/logs/smoke.log DELETED Viewed

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sessionA-20261103-0052/logs/worker.log DELETED Viewed

@@ -1,30 +0,0 @@
-[00:56:57] worker started: 6 runs queued, 3 parallel, deadline in 9h59m
-[00:56:57] worker started: 6 runs queued, 3 parallel, deadline in 9h59m
-[00:56:57] started v10-graftd-ws-896-e90-s0 (est 2h39m)
-[00:56:57] started v10-graftd-ws-896-e90-s0 (est 2h39m)
-[00:57:57] started v10-base-f16-896-e90-s0 (est 2h40m)
-[00:57:57] started v10-base-f16-896-e90-s0 (est 2h40m)
-[00:58:57] started v10-graftd-ws-896-e90-s1 (est 3h27m)
-[00:58:57] started v10-graftd-ws-896-e90-s1 (est 3h27m)
-[01:17:00] hugging face sync: uploaded (0 finished runs)
-[01:17:00] hugging face sync: uploaded (0 finished runs)
-[01:37:04] hugging face sync: uploaded (0 finished runs)
-[01:37:04] hugging face sync: uploaded (0 finished runs)
-[01:57:07] hugging face sync: uploaded (0 finished runs)
-[01:57:07] hugging face sync: uploaded (0 finished runs)
-[02:17:10] hugging face sync: uploaded (0 finished runs)
-[02:17:10] hugging face sync: uploaded (0 finished runs)
-[02:37:44] hugging face sync: uploaded (0 finished runs)
-[02:37:44] hugging face sync: uploaded (0 finished runs)
-[02:57:47] hugging face sync: uploaded (0 finished runs)
-[02:57:47] hugging face sync: uploaded (0 finished runs)
-[03:02:37] run v10-base-f16-896-e90-s0 finished (ok=True, 2h04m), runtime ratio now 0.97
-[03:02:37] run v10-base-f16-896-e90-s0 finished (ok=True, 2h04m), runtime ratio now 0.97
-[03:02:37] started v10-base-f16-896-e90-s1 (est 2h55m)
-[03:02:37] started v10-base-f16-896-e90-s1 (est 2h55m)
-[03:03:13] hugging face sync: uploaded (1 finished runs)
-[03:03:13] hugging face sync: uploaded (1 finished runs)
-[03:23:12] hugging face sync: uploaded (1 finished runs)
-[03:23:12] hugging face sync: uploaded (1 finished runs)
-[03:43:16] hugging face sync: uploaded (1 finished runs)
-[03:43:16] hugging face sync: uploaded (1 finished runs)

sessionA-20261103-0052/plan.json DELETED Viewed

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-{
- "work": "/home/marimo/graft_p2_work",
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- "notebook_file": "/marimo/notebook.py"
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sessionA-20261103-0052/results/all_runs.csv DELETED Viewed

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sessionA-20261103-0052/results/leaderboard.csv DELETED Viewed

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sessionA-20261103-0052/results/leaderboard.md DELETED Viewed

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-| label | family | imgsz | ep | n | test AP | d test (sd; pairs; same sign) | d frontier | val AP | d val | test AP50 | GFLOPs | img/s b16 | ms b1 |
-|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
-| YOLOv10 baseline, v10, 896 px, 90 ep | v10 | 896 | 90 | 1 | 18.05 | - | - | 23.28 | - | 32.15 | 13.0 | 957 | 5.44 |

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sessionA-20261103-0052/runs/v10-graftd-ws-896-e90-s0/state.json DELETED Viewed

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sessionA-20261103-0052/runs/v10-graftd-ws-896-e90-s1/args.yaml DELETED Viewed

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sessionA-20261103-0052/runs/v10-graftd-ws-896-e90-s1/state.json DELETED Viewed

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-{
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sessionA-20261103-0052/status.json DELETED Viewed

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-{
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- "queue_left": [
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sessionA-20261103-1538/START.txt DELETED Viewed

	@@ -1 +0,0 @@
1	- started 2026-11-03 15:38:08

sessionA-20261103-1538/calibration.json DELETED Viewed

@@ -1,7 +0,0 @@
-{
- "base": 19.367129802703857,
- "base_startup_s": 9.386327743530273,
- "graft": 45.87700128555298,
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sessionA-20261103-1538/logs/autopilot.log DELETED Viewed

@@ -1,25 +0,0 @@
-[15:37:57] [autopilot] environment check / repair ...
-[15:38:07] [autopilot] environment check / repair: ok (10s)
-[15:38:07] [autopilot] Hugging Face access (results are pushed there during the run) ...
-[15:38:11] [autopilot] Hugging Face access (results are pushed there during the run): ok (4s)
-[15:38:11] [autopilot] data (download, convert, pre-resize) ...
-[15:38:50] extracting VisDrone2019-DET-train.zip ...
-[15:39:17] prepared train @ 640px: 6471 images
-[15:39:20] extracting VisDrone2019-DET-val.zip ...
-[15:39:23] prepared val @ 640px: 548 images
-[15:39:32] extracting VisDrone2019-DET-test-dev.zip ...
-[15:39:38] prepared test-dev @ 640px: 1610 images
-[15:39:59] prepared train @ 896px: 6471 images
-[15:40:01] prepared val @ 896px: 548 images
-[15:40:05] prepared test-dev @ 896px: 1610 images
-[15:40:07] prepared val @ 1024px: 548 images
-[15:40:15] prepared test-dev @ 1024px: 1610 images
-[15:40:15] [autopilot] data (download, convert, pre-resize): ok (123s)
-[15:40:15] [autopilot] smoke test (tiny end-to-end run of every model type on this machine) ...
-[15:41:35] [autopilot] smoke test (tiny end-to-end run of every model type on this machine): ok (81s)
-[15:41:35] [autopilot] calibration (seconds per epoch on this machine) ...
-[15:42:42] [autopilot] calibration (seconds per epoch on this machine): ok (66s)
-[15:42:42] [autopilot] shared inputs (checkpoints) ...
-[15:42:43] [autopilot] shared inputs (checkpoints): ok (2s)
-[15:42:43] [autopilot] launch the background worker ...
-[15:42:43] [autopilot] launch the background worker: ok (0s)

sessionA-20261103-1538/logs/calibrate.log DELETED Viewed

@@ -1,156 +0,0 @@
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=32, bgr=0.0, box=7.5, cache=ram, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s640.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=3, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=0.1, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-base.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=calib-base, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=13, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/calib-base, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=6, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23        [16, 19, 22]  1    865228  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256]]
-v10-base summary: 223 layers, 2,710,940 parameters, 2,710,924 gradients, 8.5 GFLOPs
-Freezing layer 'model.23.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 771.9±551.8 MB/s, size: 95.5 KB)
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000137_02220_d_0000163.jpg: 1 duplicate labels removed
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000140_00118_d_0000002.jpg: 1 duplicate labels removed
-[34m[1mtrain: [0mNew cache created: /home/marimo/graft_p2_work/data/train_s640/labels.cache
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 1011.8±339.8 MB/s, size: 84.3 KB)
-[34m[1mval: [0mNew cache created: /home/marimo/graft_p2_work/data/val_s640/labels.cache
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 95 weight(decay=0.0), 108 weight(decay=0.0005), 107 bias(decay=0.0)
-WARNING ⚠️ Dataset images contain up to 902 objects (train=902, val=317), but max_det=300. This mismatch can cap recall and produce invalid validation metrics. Raising it may increase validation cost but cannot increase model or export capacity, which may cap recall. Setting max_det=902 to match the observed maximum.
-Using 647 train, 548 val images for fraction=0.1 at imgsz=640
-Using 6 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/calib-base[0m
-Starting training for 3 epochs...
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all        548      38759      0.118     0.0586     0.0212     0.0128
-3 epochs completed in 0.006 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-base/weights/last.pt, 5.7MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-base/weights/best.pt, 5.7MB
-Validating /home/marimo/graft_p2_work/runs/calib-base/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-base summary (fused): 99 layers, 2,267,118 parameters, 0 gradients, 6.6 GFLOPs
-                   all        548      38759      0.118     0.0587     0.0212     0.0128
-Speed: 0.0ms preprocess, 3.3ms inference, 0.0ms loss, 0.6ms postprocess per image
-[15:42:15] [calib-base] trained 3 epochs in 0h00m
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=32, bgr=0.0, box=7.5, cache=ram, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s640.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=3, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=0.1, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-graft.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=calib-graft, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=13, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/calib-graft, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=6, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23                  16  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 24             [-1, 2]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 25                  -1  1     31104  ultralytics.nn.modules.block.C2f             [96, 64, 1]
- 26    [16, 19, 22, 25]  1   1042528  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256, 64]]
-v10-graft summary: 261 layers, 2,919,344 parameters, 2,919,328 gradients, 19.2 GFLOPs
-Freezing layer 'model.26.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 487.0±135.0 MB/s, size: 101.2 KB)
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000137_02220_d_0000163.jpg: 1 duplicate labels removed
-[34m[1mtrain: [0m/home/marimo/graft_p2_work/data/train_s640/images/0000140_00118_d_0000002.jpg: 1 duplicate labels removed
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 160.6±209.2 MB/s, size: 86.9 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 111 weight(decay=0.0), 128 weight(decay=0.0005), 127 bias(decay=0.0)
-WARNING ⚠️ Dataset images contain up to 902 objects (train=902, val=317), but max_det=300. This mismatch can cap recall and produce invalid validation metrics. Raising it may increase validation cost but cannot increase model or export capacity, which may cap recall. Setting max_det=902 to match the observed maximum.
-Using 647 train, 548 val images for fraction=0.1 at imgsz=640
-Using 6 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/calib-graft[0m
-Starting training for 3 epochs...
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all        548      38759     0.0826     0.0571     0.0179     0.0118
-3 epochs completed in 0.005 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-graft/weights/last.pt, 6.3MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/calib-graft/weights/best.pt, 6.3MB
-Validating /home/marimo/graft_p2_work/runs/calib-graft/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-graft summary (fused): 113 layers, 2,386,296 parameters, 0 gradients, 12.7 GFLOPs
-                   all        548      38759     0.0825     0.0571     0.0179     0.0118
-Speed: 0.0ms preprocess, 0.7ms inference, 0.0ms loss, 0.6ms postprocess per image
-[15:42:41] [calib-graft] trained 3 epochs in 0h00m
-RESULT_JSON {"base": 19.367129802703857, "base_startup_s": 9.386327743530273, "graft": 45.87700128555298, "graft_startup_s": 5.580351114273071, "s_per_epoch": 45.87700128555298}

sessionA-20261103-1538/logs/smoke.log DELETED Viewed

@@ -1,452 +0,0 @@
-WARNING ⚠️ user config directory '/home/marimo/graft_p2_work/ultralytics_cfg/Ultralytics' is not writable, using '/tmp/Ultralytics'. Set YOLO_CONFIG_DIR to override.
-Creating new Ultralytics Settings v0.0.8 file ✅
-View Ultralytics Settings with 'yolo settings' or at '/tmp/Ultralytics/settings.json'
-Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/usage/settings.
-[15:40:25] prepared train @ 320px: 48 images
-[15:40:25] prepared val @ 320px: 48 images
-[15:40:25] prepared train @ 320px: 48 images
-[15:40:25] prepared val @ 320px: 48 images
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s320_lim48.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=1, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=320, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-base.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=smoke-base, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=11, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/smoke-base, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23        [16, 19, 22]  1    865228  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256]]
-v10-base summary: 223 layers, 2,710,940 parameters, 2,710,924 gradients, 8.5 GFLOPs
-Freezing layer 'model.23.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mdownloading yolo26n.pt for AMP checks (one-time, not used for training)...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 135.3±45.0 MB/s, size: 20.4 KB)
-[34m[1mtrain: [0mNew cache created: /home/marimo/graft_p2_work/data/train_s320_lim48/labels.cache
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 506.9±80.1 MB/s, size: 25.8 KB)
-[34m[1mval: [0mNew cache created: /home/marimo/graft_p2_work/data/val_s320_lim48/labels.cache
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 95 weight(decay=0.0), 108 weight(decay=0.0005), 107 bias(decay=0.0)
-Using 48 train, 48 val images for fraction=1.0 at imgsz=320
-Using 0 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/smoke-base[0m
-Starting training for 1 epochs...
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all         48       2255   6.83e-05    0.00358   3.21e-06   3.21e-07
-1 epochs completed in 0.003 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-base/weights/last.pt, 5.7MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-base/weights/best.pt, 5.7MB
-Validating /home/marimo/graft_p2_work/runs/smoke-base/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-base summary (fused): 99 layers, 2,267,118 parameters, 0 gradients, 6.6 GFLOPs
-                   all         48       2255   6.85e-05    0.00358   3.12e-06   3.12e-07
-Speed: 0.0ms preprocess, 15.4ms inference, 0.0ms loss, 0.3ms postprocess per image
-[15:40:44] [smoke-base] trained 1 epochs in 0h00m
-[15:40:44] prepared val @ 320px: 48 images
-[15:40:44] [smoke-base] val@320: AP50=0.00 AP=0.00
-v10-base summary (fused): 101 layers, 2,267,118 parameters, 0 gradients, 6.6 GFLOPs
-[15:40:48] prepared train @ 320px: 48 images
-[15:40:48] prepared val @ 320px: 48 images
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s320_lim48.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=1, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=320, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-graft.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=smoke-graft-role_ws, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=11, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/smoke-graft-role_ws, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23                  16  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 24             [-1, 2]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 25                  -1  1     31104  ultralytics.nn.modules.block.C2f             [96, 64, 1]
- 26    [16, 19, 22, 25]  1   1042528  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256, 64]]
-v10-graft summary: 261 layers, 2,919,344 parameters, 2,919,328 gradients, 19.2 GFLOPs
-Freezing layer 'model.26.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 138.2±39.5 MB/s, size: 22.4 KB)
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 611.0±163.9 MB/s, size: 26.5 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 111 weight(decay=0.0), 128 weight(decay=0.0005), 127 bias(decay=0.0)
-Using 48 train, 48 val images for fraction=1.0 at imgsz=320
-Using 0 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/smoke-graft-role_ws[0m
-Starting training for 1 epochs...
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all         48       2255   6.77e-05    0.00358   1.03e-05   1.03e-06
-1 epochs completed in 0.000 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-graft-role_ws/weights/last.pt, 6.2MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-graft-role_ws/weights/best.pt, 6.2MB
-Validating /home/marimo/graft_p2_work/runs/smoke-graft-role_ws/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-graft summary (fused): 113 layers, 2,386,296 parameters, 0 gradients, 12.7 GFLOPs
-                   all         48       2255   6.78e-05    0.00358   1.02e-05   1.02e-06
-Speed: 0.0ms preprocess, 2.6ms inference, 0.0ms loss, 0.3ms postprocess per image
-[15:40:51] [smoke-graft-role_ws] trained 1 epochs in 0h00m
-[15:40:52] prepared val @ 320px: 48 images
-[15:40:52] [smoke-graft-role_ws] val@320: AP50=0.00 AP=0.00
-v10-graft summary (fused): 115 layers, 2,386,296 parameters, 0 gradients, 12.7 GFLOPs
-[15:40:56] prepared train @ 320px: 48 images
-[15:40:56] prepared val @ 320px: 48 images
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s320_lim48.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=1, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=320, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-inj16.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=smoke-inj16, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=11, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/smoke-inj16, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23                   2  1      4640  ultralytics.nn.modules.conv.Conv             [32, 16, 3, 2]
- 24            [16, -1]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 25        [24, 19, 22]  1    917132  ultralytics.nn.modules.head.v10Detect        [10, [80, 128, 256]]
-v10-inj16 summary: 226 layers, 2,767,484 parameters, 2,767,468 gradients, 8.9 GFLOPs
-Freezing layer 'model.25.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 421.1±266.2 MB/s, size: 22.4 KB)
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 467.3±145.0 MB/s, size: 26.5 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 96 weight(decay=0.0), 109 weight(decay=0.0005), 108 bias(decay=0.0)
-Using 48 train, 48 val images for fraction=1.0 at imgsz=320
-Using 0 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/smoke-inj16[0m
-Starting training for 1 epochs...
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all         48       2255       0.29     0.0605     0.0391     0.0199
-1 epochs completed in 0.001 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-inj16/weights/last.pt, 5.8MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-inj16/weights/best.pt, 5.8MB
-Validating /home/marimo/graft_p2_work/runs/smoke-inj16/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-inj16 summary (fused): 101 layers, 2,297,534 parameters, 0 gradients, 6.9 GFLOPs
-                   all         48       2255       0.29     0.0605     0.0391     0.0199
-Speed: 0.0ms preprocess, 7.3ms inference, 0.0ms loss, 0.6ms postprocess per image
-[15:41:01] [smoke-inj16] trained 1 epochs in 0h00m
-[15:41:01] prepared val @ 320px: 48 images
-[15:41:01] [smoke-inj16] val@320: AP50=3.28 AP=1.67
-v10-inj16 summary (fused): 103 layers, 2,297,534 parameters, 0 gradients, 6.9 GFLOPs
-[15:41:05] prepared train @ 320px: 48 images
-[15:41:05] prepared val @ 320px: 48 images
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s320_lim48.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=1, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=320, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10-graftd.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=smoke-graftd-role_ws, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=11, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10n.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/smoke-graftd-role_ws, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='n'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]
-  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]
-  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]
-  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]
-  5                  -1  1      9856  ultralytics.nn.modules.block.SCDown          [64, 128, 3, 2]
-  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  7                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]
-  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]
- 10                  -1  1    249728  ultralytics.nn.modules.block.PSA             [256, 256]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]
- 17                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]
- 20                  -1  1     18048  ultralytics.nn.modules.block.SCDown          [128, 128, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1    282624  ultralytics.nn.modules.block.C2fCIB          [384, 256, 1, True, True]
- 23                  16  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 24             [-1, 2]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 25                  -1  2     51712  ultralytics.nn.modules.block.C2f             [96, 64, 2]
- 26    [16, 19, 22, 25]  1   1042528  ultralytics.nn.modules.head.v10Detect        [10, [64, 128, 256, 64]]
-v10-graftd summary: 265 layers, 2,939,952 parameters, 2,939,936 gradients, 20.3 GFLOPs
-Freezing layer 'model.26.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 460.6±187.7 MB/s, size: 22.4 KB)
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 670.4±112.4 MB/s, size: 26.5 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 113 weight(decay=0.0), 130 weight(decay=0.0005), 129 bias(decay=0.0)
-Using 48 train, 48 val images for fraction=1.0 at imgsz=320
-Using 0 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/smoke-graftd-role_ws[0m
-Starting training for 1 epochs...
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all         48       2255   6.65e-05    0.00358   1.48e-05   1.48e-06
-1 epochs completed in 0.000 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-graftd-role_ws/weights/last.pt, 6.2MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-graftd-role_ws/weights/best.pt, 6.2MB
-Validating /home/marimo/graft_p2_work/runs/smoke-graftd-role_ws/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10-graftd summary (fused): 115 layers, 2,406,840 parameters, 0 gradients, 13.7 GFLOPs
-                   all         48       2255   6.66e-05    0.00358   1.56e-05   1.56e-06
-Speed: 0.0ms preprocess, 0.3ms inference, 0.0ms loss, 0.4ms postprocess per image
-[15:41:07] [smoke-graftd-role_ws] trained 1 epochs in 0h00m
-[15:41:08] prepared val @ 320px: 48 images
-[15:41:08] [smoke-graftd-role_ws] val@320: AP50=0.00 AP=0.00
-v10-graftd summary (fused): 117 layers, 2,406,840 parameters, 0 gradients, 13.7 GFLOPs
-[15:41:12] prepared train @ 320px: 48 images
-[15:41:12] prepared val @ 320px: 48 images
-WARNING ⚠️ no model scale passed. Assuming scale='s'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s320_lim48.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=1, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=320, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10s-base.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=smoke-base-v10s, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=11, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10s.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/smoke-base-v10s, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='s'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       928  ultralytics.nn.modules.conv.Conv             [3, 32, 3, 2]
-  1                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  2                  -1  1     29056  ultralytics.nn.modules.block.C2f             [64, 64, 1, True]
-  3                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]
-  4                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  5                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  6                  -1  2    788480  ultralytics.nn.modules.block.C2f             [256, 256, 2, True]
-  7                  -1  1    137728  ultralytics.nn.modules.block.SCDown          [256, 512, 3, 2]
-  8                  -1  1    958464  ultralytics.nn.modules.block.C2fCIB          [512, 512, 1, True, True]
-  9                  -1  1    656896  ultralytics.nn.modules.block.SPPF            [512, 512, 5]
- 10                  -1  1    990976  ultralytics.nn.modules.block.PSA             [512, 512]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    591360  ultralytics.nn.modules.block.C2f             [768, 256, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 17                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]
- 20                  -1  1     68864  ultralytics.nn.modules.block.SCDown          [256, 256, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1   1089536  ultralytics.nn.modules.block.C2fCIB          [768, 512, 1, True, True]
- 23        [16, 19, 22]  1   1646540  ultralytics.nn.modules.head.v10Detect        [10, [128, 256, 512]]
-v10s-base summary: 234 layers, 8,074,092 parameters, 8,074,076 gradients, 24.9 GFLOPs
-Freezing layer 'model.23.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 498.2±191.9 MB/s, size: 22.4 KB)
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 590.7±103.1 MB/s, size: 26.5 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 99 weight(decay=0.0), 112 weight(decay=0.0005), 111 bias(decay=0.0)
-Using 48 train, 48 val images for fraction=1.0 at imgsz=320
-Using 0 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/smoke-base-v10s[0m
-Starting training for 1 epochs...
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all         48       2255      0.663      0.057     0.0647     0.0409
-1 epochs completed in 0.001 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-base-v10s/weights/last.pt, 16.5MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-base-v10s/weights/best.pt, 16.5MB
-Validating /home/marimo/graft_p2_work/runs/smoke-base-v10s/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10s-base summary (fused): 103 layers, 7,221,870 parameters, 0 gradients, 21.6 GFLOPs
-                   all         48       2255      0.646      0.057     0.0646      0.041
-Speed: 0.0ms preprocess, 12.2ms inference, 0.0ms loss, 0.6ms postprocess per image
-[15:41:20] [smoke-base-v10s] trained 1 epochs in 0h00m
-[15:41:20] prepared val @ 320px: 48 images
-[15:41:21] [smoke-base-v10s] val@320: AP50=7.68 AP=5.13
-v10s-base summary (fused): 105 layers, 7,221,870 parameters, 0 gradients, 21.6 GFLOPs
-[15:41:25] prepared train @ 320px: 48 images
-[15:41:25] prepared val @ 320px: 48 images
-WARNING ⚠️ no model scale passed. Assuming scale='s'.
-New https://pypi.org/project/ultralytics/8.4.201 available 😃 Update with 'pip install -U ultralytics'
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-[34m[1mengine/trainer: [0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, channels_last=None, classes=None, close_mosaic=1, cls=0.5, cls_pw=0.0, cls_remap=True, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/marimo/graft_p2_work/cfg/visdrone_s320_lim48.yaml, degrees=0.0, deterministic=False, device=0, dfl=1.5, dgrad=0.5, dis=6.0, distill_model=None, dlam=1.0, dlog=1.0, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=1, erasing=0.4, exist_ok=True, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=320, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=/home/marimo/graft_p2_work/cfg/v10s-graftd.yaml, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=smoke-graftd-role_ws-v10s, nbs=64, nms=None, opset=None, optimize=False, optimizer=SGD, overlap_mask=True, patience=11, perspective=0.0, plots=False, pose=12.0, pretrained=/home/marimo/graft_p2_work/weights/yolov10s.pt, profile=False, project=/home/marimo/graft_p2_work/runs, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/home/marimo/graft_p2_work/runs/smoke-graftd-role_ws-v10s, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=False, verbose=False, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
-Overriding model.yaml nc=80 with nc=10
-WARNING ⚠️ no model scale passed. Assuming scale='s'.
-                   from  n    params  module                                       arguments
-  0                  -1  1       928  ultralytics.nn.modules.conv.Conv             [3, 32, 3, 2]
-  1                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]
-  2                  -1  1     29056  ultralytics.nn.modules.block.C2f             [64, 64, 1, True]
-  3                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]
-  4                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]
-  5                  -1  1     36096  ultralytics.nn.modules.block.SCDown          [128, 256, 3, 2]
-  6                  -1  2    788480  ultralytics.nn.modules.block.C2f             [256, 256, 2, True]
-  7                  -1  1    137728  ultralytics.nn.modules.block.SCDown          [256, 512, 3, 2]
-  8                  -1  1    958464  ultralytics.nn.modules.block.C2fCIB          [512, 512, 1, True, True]
-  9                  -1  1    656896  ultralytics.nn.modules.block.SPPF            [512, 512, 5]
- 10                  -1  1    990976  ultralytics.nn.modules.block.PSA             [512, 512]
- 11                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 12             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 13                  -1  1    591360  ultralytics.nn.modules.block.C2f             [768, 256, 1]
- 14                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 15             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 16                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]
- 17                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]
- 18            [-1, 13]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 19                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]
- 20                  -1  1     68864  ultralytics.nn.modules.block.SCDown          [256, 256, 3, 2]
- 21            [-1, 10]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 22                  -1  1   1089536  ultralytics.nn.modules.block.C2fCIB          [768, 512, 1, True, True]
- 23                  16  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']
- 24             [-1, 2]  1         0  ultralytics.nn.modules.conv.Concat           [1]
- 25                  -1  2    205824  ultralytics.nn.modules.block.C2f             [192, 128, 2]
- 26    [16, 19, 22, 25]  1   1951328  ultralytics.nn.modules.head.v10Detect        [10, [128, 256, 512, 128]]
-v10s-graftd summary: 276 layers, 8,584,704 parameters, 8,584,688 gradients, 51.2 GFLOPs
-Freezing layer 'model.26.dfl.conv.weight'
-[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks...
-[34m[1mAMP: [0mchecks passed ✅
-[34m[1mtrain: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 471.8±165.2 MB/s, size: 22.4 KB)
-[34m[1mval: [0mFast image access ✅ (ping: 0.0±0.0 ms, read: 481.0±53.7 MB/s, size: 26.5 KB)
-[34m[1moptimizer:[0m SGD(lr=0.01, momentum=0.937) with parameter groups 117 weight(decay=0.0), 134 weight(decay=0.0005), 133 bias(decay=0.0)
-Using 48 train, 48 val images for fraction=1.0 at imgsz=320
-Using 0 dataloader workers
-Logging results to [1m/home/marimo/graft_p2_work/runs/smoke-graftd-role_ws-v10s[0m
-Starting training for 1 epochs...
-Closing dataloader mosaic
-      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
-                   all         48       2255    0.00172   0.000519   1.46e-05   2.37e-06
-1 epochs completed in 0.000 hours.
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-graftd-role_ws-v10s/weights/last.pt, 17.6MB
-Optimizer stripped from /home/marimo/graft_p2_work/runs/smoke-graftd-role_ws-v10s/weights/best.pt, 17.6MB
-Validating /home/marimo/graft_p2_work/runs/smoke-graftd-role_ws-v10s/weights/best.pt...
-Ultralytics 8.4.150 🚀 Python-3.13.11 torch-2.11.0+cu130 CUDA:0 (NVIDIA RTX PRO 6000 Blackwell Server Edition, 97252MiB)
-v10s-graftd summary (fused): 119 layers, 7,578,936 parameters, 0 gradients, 39.8 GFLOPs
-                   all         48       2255    0.00173   0.000519   1.44e-05   2.32e-06
-Speed: 0.0ms preprocess, 3.1ms inference, 0.0ms loss, 6.2ms postprocess per image
-[15:41:29] [smoke-graftd-role_ws-v10s] trained 1 epochs in 0h00m
-[15:41:29] prepared val @ 320px: 48 images
-[15:41:29] [smoke-graftd-role_ws-v10s] val@320: AP50=0.20 AP=0.17
-v10s-graftd summary (fused): 121 layers, 7,578,936 parameters, 0 gradients, 39.8 GFLOPs
-loading annotations into memory...
-Done (t=0.00s)
-creating index...
-index created!
-Loading and preparing results...
-DONE (t=0.00s)
-creating index...
-index created!
-Running per image evaluation...
-Evaluate annotation type *bbox*
-DONE (t=0.70s).
-Accumulating evaluation results...
-DONE (t=0.06s).
-RESULT_JSON [{"step": "environment", "ok": true, "seconds": 4.3, "detail": {"python": "3.13.11", "torch": "2.11.0+cu130", "ultralytics": "8.4.150", "cuda_available": true, "gpu": "NVIDIA RTX PRO 6000 Blackwell Server Edition"}}, {"step": "exactness of the grafted / injected variants (random inputs, real COCO checkpoint)", "ok": true, "seconds": 4.4, "detail": {"graft": {"max_feature_diff": 0.0, "max_head_diff": 0.0}, "graftd": {"max_feature_diff": 0.0, "max_head_diff": 0.0}, "inj16": {"max_feature_diff": 0.0, "max_head_diff": 0.0}, "graftd (v10s)": {"max_feature_diff": 0.0, "max_head_diff": 0.0}}}, {"step": "prepare train subset (48 images @ 320px)", "ok": true, "seconds": 0.3, "detail": true}, {"step": "prepare val subset (48 images @ 320px)", "ok": true, "seconds": 0.1, "detail": true}, {"step": "train + evaluate base (1 epoch, tiny)", "ok": true, "seconds": 23.0, "detail": {"run_one_ok": true, "AP50": 0.0, "n_dets": 17280, "tide_ok": true}}, {"step": "train + evaluate graft-role_ws (1 epoch, tiny)", "ok": true, "seconds": 7.5, "detail": {"run_one_ok": true, "AP50": 0.0, "n_dets": 17280, "tide_ok": true}}, {"step": "train + evaluate inj16 (1 epoch, tiny)", "ok": true, "seconds": 9.1, "detail": {"run_one_ok": true, "AP50": 3.2788754041923314, "n_dets": 24000, "tide_ok": true}}, {"step": "train + evaluate graftd-role_ws (1 epoch, tiny)", "ok": true, "seconds": 6.7, "detail": {"run_one_ok": true, "AP50": 0.0, "n_dets": 17280, "tide_ok": true}}, {"step": "train + evaluate base-v10s (1 epoch, tiny)", "ok": true, "seconds": 13.3, "detail": {"run_one_ok": true, "AP50": 7.677161765872734, "n_dets": 24000, "tide_ok": true}}, {"step": "train + evaluate graftd-role_ws-v10s (1 epoch, tiny)", "ok": true, "seconds": 8.4, "detail": {"run_one_ok": true, "AP50": 0.2014301795336179, "n_dets": 24000, "tide_ok": true}}, {"step": "evaluator self-test on synthetic detections (bootstrap accumulation == pycocotools == faster-coco-eval)", "ok": true, "seconds": 1.0, "detail": {"bootstrap_AP": 11.23832118325774, "pycocotools_AP": 11.238321183257742, "faster_AP": 11.238321183257742, "bootstrap_AP50": 35.944967410697565, "pycocotools_AP50": 35.944967410697565, "faster_AP50": 35.944967410697565, "resampled_AP": [12.29231357685496, 11.689935919855124, 11.499674455804522], "n_dets": 3024, "agree": true}}]

sessionA-20261103-1538/logs/worker.log DELETED Viewed

@@ -1,46 +0,0 @@
-[15:42:45] worker started: 6 runs queued, 3 parallel, deadline in 9h59m
-[15:42:45] worker started: 6 runs queued, 3 parallel, deadline in 9h59m
-[15:42:45] started v10-graftd-ws-896-e90-s0 (est 2h40m)
-[15:42:45] started v10-graftd-ws-896-e90-s0 (est 2h40m)
-[15:43:45] started v10-base-f16-896-e90-s0 (est 2h41m)
-[15:43:45] started v10-base-f16-896-e90-s0 (est 2h41m)
-[15:44:45] started v10-graftd-ws-896-e90-s1 (est 3h28m)
-[15:44:45] started v10-graftd-ws-896-e90-s1 (est 3h28m)
-[15:52:51] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[15:52:51] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:02:53] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:02:53] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:12:55] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:12:55] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:22:53] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:22:53] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:32:56] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:32:56] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:42:59] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:42:59] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:53:04] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[16:53:04] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:03:09] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:03:09] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:13:16] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:13:16] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:23:14] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:23:14] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:33:17] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:33:17] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:43:20] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:43:20] hugging face sync: UPLOADED BUT NOT VERIFIED, missing on the hub: ['sessionA-20261103-1538/results/leaderboard.csv']
-[17:47:40] run v10-base-f16-896-e90-s0 finished (ok=True, 2h03m), runtime ratio now 0.97
-[17:47:40] run v10-base-f16-896-e90-s0 finished (ok=True, 2h03m), runtime ratio now 0.97
-[17:47:40] started v10-base-f16-896-e90-s1 (est 2h56m)
-[17:47:40] started v10-base-f16-896-e90-s1 (est 2h56m)
-[17:47:45] hugging face sync: uploaded and verified on the hub (1 finished runs, 29 files)
-[17:47:45] hugging face sync: uploaded and verified on the hub (1 finished runs, 29 files)
-[17:57:44] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[17:57:44] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[18:07:48] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[18:07:48] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[18:17:53] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[18:17:53] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[18:27:58] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)
-[18:27:58] hugging face sync: uploaded and verified on the hub (1 finished runs, 33 files)

sessionA-20261103-1538/plan.json DELETED Viewed

@@ -1,121 +0,0 @@
-{
- "work": "/home/marimo/graft_p2_work",
- "specs": [
-  {
-   "run_id": "v10-graftd-ws-896-e90-s0",
-   "group": "P2-Graft deep, warm-started, v10, 896 px, 90 ep",
-   "family": "v10",
-   "variant": "graftd",
-   "transfer": "role_ws",
-   "seed": 0,
-   "epochs": 90,
-   "imgsz": 896,
-   "floor": 16,
-   "batch": 16,
-   "tier": 1,
-   "eval_sizes": [
-    1024
-   ],
-   "notes": "C1"
-  },
-  {
-   "run_id": "v10-base-f16-896-e90-s0",
-   "group": "YOLOv10 baseline, v10, 896 px, 90 ep",
-   "family": "v10",
-   "variant": "base",
-   "transfer": "role",
-   "seed": 0,
-   "epochs": 90,
-   "imgsz": 896,
-   "floor": 16,
-   "batch": 32,
-   "tier": 1,
-   "eval_sizes": [
-    1024
-   ],
-   "notes": "C1"
-  },
-  {
-   "run_id": "v10-graftd-ws-896-e90-s1",
-   "group": "P2-Graft deep, warm-started, v10, 896 px, 90 ep",
-   "family": "v10",
-   "variant": "graftd",
-   "transfer": "role_ws",
-   "seed": 1,
-   "epochs": 90,
-   "imgsz": 896,
-   "floor": 16,
-   "batch": 16,
-   "tier": 1,
-   "eval_sizes": [
-    1024
-   ],
-   "notes": "C1"
-  },
-  {
-   "run_id": "v10-base-f16-896-e90-s1",
-   "group": "YOLOv10 baseline, v10, 896 px, 90 ep",
-   "family": "v10",
-   "variant": "base",
-   "transfer": "role",
-   "seed": 1,
-   "epochs": 90,
-   "imgsz": 896,
-   "floor": 16,
-   "batch": 32,
-   "tier": 1,
-   "eval_sizes": [
-    1024
-   ],
-   "notes": "C1"
-  },
-  {
-   "run_id": "v10-graftd-ws-896-e90-s2",
-   "group": "P2-Graft deep, warm-started, v10, 896 px, 90 ep",
-   "family": "v10",
-   "variant": "graftd",
-   "transfer": "role_ws",
-   "seed": 2,
-   "epochs": 90,
-   "imgsz": 896,
-   "floor": 16,
-   "batch": 16,
-   "tier": 1,
-   "eval_sizes": [
-    1024
-   ],
-   "notes": "C1"
-  },
-  {
-   "run_id": "v10-base-f16-896-e90-s2",
-   "group": "YOLOv10 baseline, v10, 896 px, 90 ep",
-   "family": "v10",
-   "variant": "base",
-   "transfer": "role",
-   "seed": 2,
-   "epochs": 90,
-   "imgsz": 896,
-   "floor": 16,
-   "batch": 32,
-   "tier": 1,
-   "eval_sizes": [
-    1024
-   ],
-   "notes": "C1"
-  }
- ],
- "n_parallel": 3,
- "workers": 6,
- "cache": "ram",
- "device": null,
- "deadline": 1793756562.1234503,
- "hard_deadline": 1793758362.1234503,
- "s_per_epoch": 45.87700128555298,
- "eval_s": 240.0,
- "gpu_gb": 102.0,
- "tide": true,
- "test_dev": true,
- "bootstrap_B": 200,
- "hf_tag": "sessionA-20261103-1538",
- "notebook_file": "/marimo/notebook.py"
-}

sessionA-20261103-1538/results/all_runs.csv DELETED Viewed

	@@ -1,2 +0,0 @@
1	- run_id,group,family,variant,transfer,floor,seed,epochs,imgsz,tier,batch,val_AP,val_AP50,val_AP75,val_APs,val_APm,val_APl,val_AP_tiny,val_AP_xsmall,val_AP50_tiny,val_AP50_xsmall,val_AP50_small,val_AP50_medium,val_AP50_large,val_ARmax,val_ARtiny,val_perclass_AP50,val_perclass_AP,test_AP,test_AP50,test_AP75,test_APs,test_APm,test_APl,test_AP_tiny,test_AP_xsmall,test_AP50_tiny,test_AP50_xsmall,test_AP50_small,test_AP50_medium,test_AP50_large,test_ARmax,test_ARtiny,val_AP50_at1024,val_AP_at1024,val_APs_at1024,test_AP50_at1024,test_AP_at1024,test_APs_at1024,params_deploy_M,params_train_M,gflops,latency_ms,throughput_b16,latency_seq,train_h,frac_transferred,frac_aligned,tide_Cls,tide_Loc,tide_Both,tide_Dupe,tide_Bkg,tide_Miss,tide_FalsePos,tide_FalseNeg
2	- v10-base-f16-896-e90-s0,"YOLOv10 baseline, v10, 896 px, 90 ep",v10,base,role,16,0,90,896,1,32,23.280049504959845,39.84672089672938,23.292959743474093,14.33226951557722,33.95320359472515,46.369615378876325,7.4582319228719705,18.968374880891194,19.087338301837903,36.715878512474035,29.56482495028996,53.87141245245619,63.55967108444749,40.848956439009065,20.86339101840089,"[46.549101660680016, 35.851671994346205, 15.938605161271601, 79.7063335169492, 42.68951862742571, 37.555494909790944, 27.17780999758818, 14.509042160569392, 51.75898665589688, 46.73064428277569]","[20.95823003535132, 13.803232764799139, 7.000001054529759, 54.85466004523039, 30.04122996410517, 24.118540533483554, 14.665949042611723, 8.718582624544561, 37.9271750781492, 20.712893906793656]",18.052231775932828,32.14618070812275,17.89194387878635,9.521888159720785,26.617546872719856,38.75220719588064,4.701795793820285,13.651028540521931,12.440747000813925,29.61787034359921,21.228881654553273,45.473764325780195,56.214261840069355,36.67271823207911,15.928210401461355,41.7705495710642,24.660609233155423,15.996349521456757,34.048797296537806,19.39876454624835,10.6230575150931,2.267118,2.71094,13.044957184,4.769739499806747,970.0759754193149,False,2.0302396156390508,0.9431252299898545,0.9431252299898545,13.65884494857319,4.012447686626601,0.9974592889619132,1.0576703456363106,2.6415273227814,5.959350488955167,28.074071182478548,15.98537307846582

sessionA-20261103-1538/results/leaderboard.csv DELETED Viewed

	@@ -1,2 +0,0 @@
1	- family,variant,transfer,imgsz,epochs,label,n,seeds,val_AP,val_AP_std,val_AP50,val_AP50_std,val_APs,val_APs_std,test_AP,test_AP_std,test_AP50,test_AP50_std,test_APs,test_APs_std,gflops,gflops_std,params_deploy_M,params_deploy_M_std,latency_ms,latency_ms_std,throughput_b16,throughput_b16_std,train_h,train_h_std,val_AP_at1024,test_AP_at1024,d_test,d_test_sd,d_test_pairs,d_test_same_sign,d_val,d_frontier_test
2	- v10,base,role,896,90,"YOLOv10 baseline, v10, 896 px, 90 ep",1,0,23.280049504959845,,39.84672089672938,,14.33226951557722,,18.052231775932828,,32.14618070812275,,9.521888159720785,,13.044957184,,2.267118,,4.769739499806747,,970.0759754193149,,2.0302396156390508,,24.660609233155423,19.39876454624835,,,,,,

sessionA-20261103-1538/results/leaderboard.md DELETED Viewed

@@ -1,3 +0,0 @@
-| label | family | imgsz | ep | n | test AP | d test (sd; pairs; same sign) | d frontier | val AP | d val | test AP50 | GFLOPs | img/s b16 | ms b1 |
-|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
-| YOLOv10 baseline, v10, 896 px, 90 ep | v10 | 896 | 90 | 1 | 18.05 | - | - | 23.28 | - | 32.15 | 13.0 | 970 | 4.77 |

sessionA-20261103-1538/runs/v10-base-f16-896-e90-s0/args.yaml DELETED Viewed

@@ -1,115 +0,0 @@
-task: detect
-mode: train
-model: /home/marimo/graft_p2_work/cfg/v10-base.yaml
-data: /home/marimo/graft_p2_work/cfg/visdrone_s896.yaml
-epochs: 90
-time: null
-patience: 100
-batch: 32
-imgsz: 896
-save: true
-save_period: -1
-cache: ram
-device: '0'
-workers: 6
-project: /home/marimo/graft_p2_work/runs
-name: v10-base-f16-896-e90-s0
-exist_ok: true
-pretrained: /home/marimo/graft_p2_work/weights/yolov10n.pt
-cls_remap: true
-optimizer: SGD
-verbose: false
-seed: 0
-deterministic: false
-single_cls: false
-rect: false
-cos_lr: false
-close_mosaic: 10
-resume: false
-amp: true
-fraction: 1.0
-profile: false
-freeze: null
-multi_scale: 0.0
-compile: false
-channels_last: null
-overlap_mask: true
-mask_ratio: 4
-dropout: 0.0
-val: false
-split: val
-save_json: false
-conf: null
-iou: 0.7
-max_det: 300
-quantize: null
-dnn: false
-plots: false
-nms: null
-source: null
-vid_stride: 1
-stream_buffer: false
-visualize: false
-augment: false
-agnostic_nms: false
-classes: null
-retina_masks: false
-embed: null
-show: false
-save_frames: false
-save_txt: false
-save_conf: false
-save_crop: false
-show_labels: true
-show_conf: true
-show_boxes: true
-line_width: null
-format: torchscript
-keras: false
-optimize: false
-dynamic: false
-simplify: true
-opset: null
-workspace: null
-lr0: 0.01
-lrf: 0.01
-momentum: 0.937
-weight_decay: 0.0005
-warmup_epochs: 3.0
-warmup_momentum: 0.8
-warmup_bias_lr: 0.1
-distill_model: null
-dis: 6.0
-box: 7.5
-cls: 0.5
-cls_pw: 0.0
-dfl: 1.5
-pose: 12.0
-kobj: 1.0
-rle: 1.0
-angle: 1.0
-dlog: 1.0
-dgrad: 0.5
-dlam: 1.0
-nbs: 64
-hsv_h: 0.015
-hsv_s: 0.7
-hsv_v: 0.4
-degrees: 0.0
-translate: 0.1
-scale: 0.5
-shear: 0.0
-perspective: 0.0
-flipud: 0.0
-fliplr: 0.5
-bgr: 0.0
-mosaic: 1.0
-mixup: 0.0
-cutmix: 0.0
-copy_paste: 0.0
-copy_paste_mode: flip
-auto_augment: randaugment
-erasing: 0.4
-cfg: null
-tracker: tracktrack.yaml
-save_dir: /home/marimo/graft_p2_work/runs/v10-base-f16-896-e90-s0