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  1. .gitattributes +5 -0
  2. README.md +16 -0
  3. home/wuyifan/EgoNet_train_20261008/.gitignore +36 -0
  4. home/wuyifan/EgoNet_train_20261008/README.md +19 -0
  5. home/wuyifan/EgoNet_train_20261008/REVIEW_GUIDE.md +40 -0
  6. home/wuyifan/EgoNet_train_20261008/THIRD_PARTY.md +12 -0
  7. home/wuyifan/EgoNet_train_20261008/configs/a_rgb_single_frame.yaml +16 -0
  8. home/wuyifan/EgoNet_train_20261008/configs/b_rgb_video_sequential.yaml +16 -0
  9. home/wuyifan/EgoNet_train_20261008/configs/c_rgb_video_alternating.yaml +16 -0
  10. home/wuyifan/EgoNet_train_20261008/configs/d_rgb_k_video_alternating.yaml +16 -0
  11. home/wuyifan/EgoNet_train_20261008/configs/e_rgb_depth_video_alternating.yaml +18 -0
  12. home/wuyifan/EgoNet_train_20261008/configs/e_rgb_depth_video_alternating_fixed_gate.yaml +19 -0
  13. home/wuyifan/EgoNet_train_20261008/configs/f_geometry_ablation.yaml +18 -0
  14. home/wuyifan/EgoNet_train_20261008/configs/f_geometry_fixed_gate_ablation.yaml +19 -0
  15. home/wuyifan/EgoNet_train_20261008/configs/f_rgb_depth_k_video_alternating.yaml +18 -0
  16. home/wuyifan/EgoNet_train_20261008/configs/f_rgb_depth_k_video_alternating_fixed_gate.yaml +19 -0
  17. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t0_s20260716.yaml +63 -0
  18. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t0_s20260717.yaml +63 -0
  19. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t0_s20260718.yaml +63 -0
  20. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t1_s20260716.yaml +63 -0
  21. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t1_s20260717.yaml +63 -0
  22. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t1_s20260718.yaml +63 -0
  23. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t0_s20260716.yaml +63 -0
  24. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t0_s20260717.yaml +63 -0
  25. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t0_s20260718.yaml +63 -0
  26. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t1_s20260716.yaml +63 -0
  27. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t1_s20260717.yaml +63 -0
  28. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t1_s20260718.yaml +63 -0
  29. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l2_t1_s20260716.yaml +63 -0
  30. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l2_t1_s20260717.yaml +63 -0
  31. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l2_t1_s20260718.yaml +63 -0
  32. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t0_s20260716.yaml +63 -0
  33. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t0_s20260717.yaml +63 -0
  34. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t0_s20260718.yaml +63 -0
  35. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t1_s20260716.yaml +63 -0
  36. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t1_s20260717.yaml +63 -0
  37. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t1_s20260718.yaml +63 -0
  38. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t0_s20260716.yaml +63 -0
  39. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t0_s20260717.yaml +63 -0
  40. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t0_s20260718.yaml +63 -0
  41. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t1_s20260716.yaml +63 -0
  42. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t1_s20260717.yaml +63 -0
  43. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t1_s20260718.yaml +63 -0
  44. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l2_t1_s20260716.yaml +63 -0
  45. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l2_t1_s20260717.yaml +63 -0
  46. home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l2_t1_s20260718.yaml +63 -0
  47. home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout005_geometry_m3_l1_t1_s20260716.yaml +65 -0
  48. home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout005_geometry_m3_l1_t1_s20260717.yaml +65 -0
  49. home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout005_geometry_m3_l1_t1_s20260718.yaml +65 -0
  50. home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout00_geometry_m3_l1_t1_s20260716.yaml +65 -0
.gitattributes CHANGED
@@ -58,3 +58,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ home/wuyifan/a7_canonical_gt_rotationfix_20260930/cache/native_inventory.json filter=lfs diff=lfs merge=lfs -text
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+ home/wuyifan/a7_canonical_gt_rotationfix_20260930/label_inventory.json filter=lfs diff=lfs merge=lfs -text
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+ home/wuyifan/foundation_hand_clean_gt_dino_20260925/cache/adapter_trainable_t8/arctic_t8.jsonl filter=lfs diff=lfs merge=lfs -text
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+ home/wuyifan/foundation_hand_clean_gt_dino_20260925/cache/adapter_trainable_t8/hot3d_t8.jsonl filter=lfs diff=lfs merge=lfs -text
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+ home/wuyifan/foundation_hand_clean_gt_dino_20260925/cache/trainable_t8_index.sqlite filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ # EgoNet training migration metadata
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+
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+ This private repository preserves the code snapshot, configuration, fixed
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+ 8-frame training manifests, SQLite sampling index, normalization statistics,
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+ and canonical-label provenance for the H2O, ARCTIC, HOT3D, and GRAB mixed run.
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+ Paths below `home/wuyifan/` mirror their original absolute paths on g2.
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+
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+ This repository is not a complete training dataset. It does not contain source
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+ RGB/depth/VRS recordings, rendered GRAB videos, filtered GT NPZ files,
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+ canonical label NPZ files, personalized MANO templates, licensed MANO model
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+ files, ViTPose visual weights, or training checkpoints. Restore those through
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+ the appropriate authorized channels before running the training code.
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+
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+ The manifests and inventory contain absolute source paths and content hashes.
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+ Preserve the original path layout on the destination, or explicitly rebuild
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+ the associated index, inventory, and provenance checks after changing paths.
home/wuyifan/EgoNet_train_20261008/.gitignore ADDED
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+ __pycache__/
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+ *.py[cod]
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+ .pytest_cache/
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+ .ruff_cache/
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+ .mypy_cache/
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+ .venv/
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+ *.egg-info/
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+
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+ .env
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+ .env.*
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+ *.pem
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+ *.key
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+ id_rsa*
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+ id_ed25519*
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+
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+ data/
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+ datasets/
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+ cache/
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+ checkpoints/
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+ runs/
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+ artifacts/
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+ third_party/
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+ *.pt
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+ *.pth
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+ *.ckpt
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+ *.safetensors
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+ *.npy
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+ *.npz
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+ *.vrs
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+ *.mp4
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+ *.avi
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+ *.png
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+ *.jpg
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+ *.jpeg
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+ *.lock
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+ *.log
home/wuyifan/EgoNet_train_20261008/README.md ADDED
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+ # EgoNet
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+
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+ EgoNet is the review snapshot of the Foundation Hand bimanual reconstruction code and its current RGB training lineage. The Python package is still named `foundation_hand` so checkpoint keys and historical imports remain recognizable.
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+
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+ This repository contains model and dataset code, training/evaluation scripts, configs, tests, and the experiment-specific source used for S4, A7, U0, N0, and N1. It does **not** contain datasets, fitted label caches, MANO assets, DINO weights, model checkpoints, videos, or third-party source trees. See [REVIEW_GUIDE.md](REVIEW_GUIDE.md) for the exact lineage, review entry points, and known limitations.
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+
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+ The snapshot preserves the code that produced the reported experiments. In particular, the historical N0/N1 trainer still has a teacher term and the known bf16 GT-6D precision issue; do not use it for the new B0/B1 contract. The new no-teacher, MANO-pkl-mean-pose-delta model and loss path has passed two real updates per arm, but formal training and benchmark validation have not started.
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+
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+ The matched RGB non-MoT/MoT smoke configuration is in `experiments/from_scratch_mean_pose/config.json`. Both arms use mean-pose delta and normalized orthogonal GT 6D. It remains smoke-only (`training_approved=false`) and is not consumed by the historical trainer. See `docs/PIONAI_NON2D_HANDOFF_20261005.md` for the PionAI transfer and readiness status.
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+
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+ Primary materials:
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+
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+ - `experiments/u0_normalized6d/train.py`: N0/N1 training entry point.
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+ - `experiments/u0_normalized6d/normalized_loss.py`: normalized direct-6D and geometry supervision.
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+ - `src/foundation_hand/`: core architecture, data readers, MANO geometry, and losses.
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+ - `docs/HK.md`: evaluation and hard-pose diagnostics.
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+ - `docs/FROM_SCRATCH_MEAN_POSE_REVIEW.md`: proposed next controlled experiment, not launched.
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+
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+ Python 3.11 is required by `pyproject.toml`. The original environment also requires the external packages and pinned upstream repositories listed in [THIRD_PARTY.md](THIRD_PARTY.md), plus separately provided licensed MANO assets and datasets. Several historical scripts contain host-specific absolute paths; they are retained for audit, not presented as portable launch commands.
home/wuyifan/EgoNet_train_20261008/REVIEW_GUIDE.md ADDED
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+ # Code review guide
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+
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+ ## Scope and provenance
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+
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+ The root `src/foundation_hand/`, `scripts/`, and training helper files are from the frozen `foundation_hand_clean_gt_dino_20260925/code` snapshot used by the current lineage. Missing general tests and historical configs come from the `/home/jiasen/foundation_hand` working tree; where files overlapped, the frozen training snapshot takes precedence. The original project was at commit `5d59528` before local changes. No source tree or checkpoint was modified to make this review snapshot.
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+
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+ The experiment chain uses these directories, in dependency order:
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+
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+ | Directory | Role |
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+ | --- | --- |
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+ | `experiments/clean_gt_dino` | Clean-GT data filtering and from-DINO training helpers |
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+ | `experiments/s4_modality_experts` | RGB/K/depth expert sampling and training contracts |
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+ | `experiments/a7_mot_residual` | MoT residual expert code |
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+ | `experiments/a7_canonical_gt_cache` | Corrected-left MANO label migration and audits |
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+ | `experiments/a7_rotation_fix` | Frozen A7 rotation-fix data/training scripts |
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+ | `experiments/a7_canonical_gt_train` | Canonical GT A7 trainer and geometry validation |
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+ | `experiments/u0_depthsafe` | U0 RGB parent model, loss, and trainer |
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+ | `experiments/u0_normalized6d` | Matched N0/N1 direct-6D continuation trainer |
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+ | `experiments/pose_delta_diagnostics` | Frozen-panel and hard-case diagnostic scripts |
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+
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+ These are source snapshots, not a single importable package. Their original configs name absolute paths under `/home/wuyifan` and data roots under `/SSD*`; the review of what ran should use those values together with the SHA256 checkpoint and code records in the experiment reports. To rerun elsewhere, map those paths, obtain the datasets/weights/assets, and revalidate each hash-bound registration. Do not treat a path substitution alone as a reproduced experiment.
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+
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+ ## Start here for the current training review
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+
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+ 1. `experiments/u0_normalized6d/config.json` fixes a 60-clip update with H2O/ARCTIC/HOT3D quotas 21/15/24, AdamW learning rates, loss coefficients, the RGB teacher weight, and checkpoint interval.
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+ 2. `experiments/u0_normalized6d/train.py` controls data coverage, source scaling, DDP, optimizer groups, clipping, checkpoints, and provenance.
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+ 3. `experiments/u0_normalized6d/normalized_loss.py` defines the direct rotation-6D and geometry terms. `src/foundation_hand/models/bimanual.py` and `src/foundation_hand/models/decoder.py` define prediction and temporal fusion.
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+ 4. `experiments/a7_canonical_gt_train/targets.py` and `common.py` apply corrected-left labels and check MANO reconstruction. `src/foundation_hand/data/{h2o,arctic,hot3d}_dataset.py` construct camera-space source targets.
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+ 5. `experiments/pose_delta_diagnostics/pose_hard_case_monitor.py` defines GT-hard buckets and paired evaluation. The reports in `reports/` use source-native GT on fixed development panels; they are not official benchmark submissions.
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+
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+ ## Known review findings
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+
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+ - N0/N1 both continue from the same U0 RGB checkpoint and use a teacher geometry anchor of weight 0.05. They do not test from-scratch or mean-pose-delta training.
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+ - The training loss compares Gram-Schmidt-normalized predicted 6D with the first two rows of GT rotations. GT axis-angle conversion is currently executed inside bf16 autocast, causing a small orthogonality error. This is recorded in `docs/HK.md`; it is not silently patched in this snapshot.
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+ - Valid 3D hand geometry and root pose are camera-space. The 15 MANO finger rotations are local to the kinematic chain. The cached label is axis-angle; 6D is generated during loss computation.
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+ - N1 improves some high-bend HOT3D hands but does not pass cross-source four-metric/no-harm gates. N0 was stopped after log step 19,247; its last complete checkpoint is 18K. See `docs/HK.md` for matched 18K numbers and the N1 20K curve point.
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+
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+ ## What is intentionally absent
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+
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+ No raw or filtered dataset, per-frame label cache, MANO asset, DINO weight, training checkpoint, optimizer state, image/video, SSH credential, or access token is included. Runtime JSON manifests that can enumerate private data recordings are omitted; short config and aggregate reports are included. The code can be reviewed immediately but cannot reproduce training from this repository alone.
home/wuyifan/EgoNet_train_20261008/THIRD_PARTY.md ADDED
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+ # External dependencies
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+
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+ `pyproject.toml` lists Python package dependencies. The original Foundation Hand repository also recorded these external repositories as Git submodules; their source is not redistributed in this review snapshot:
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+
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+ | Upstream | Original revision |
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+ | --- | --- |
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+ | `https://github.com/taeinkwon/h2odataset.git` | `ebcb48996849f747580907dc22f8745633ae60b0` |
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+ | `https://github.com/facebookresearch/dinov3.git` | `346f38fee679c56a6888f91c51670fae61d364e0` |
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+ | `https://github.com/taeinkwon/h2oplayer.git` | `6f30a287f04e50bb96c6ba5e986ff72c75dd05e5` |
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+ | `https://github.com/hassony2/manopth.git` | `4f1dcad1201ff1bfca6e065a85f0e3456e1aa32b` |
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+
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+ The HOT3D Python API was present in the original runtime as a separate third-party tree, but no pinned upstream revision was registered in the project's `.gitmodules`. Reviewers should obtain a version compatible with the original dataset API before attempting to rerun its reader. MANO model files and DINO pretrained weights require their own licenses and are not included.
home/wuyifan/EgoNet_train_20261008/configs/a_rgb_single_frame.yaml ADDED
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+ name: a_rgb_single_frame
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 1, stride: 1, batch_size: 2}
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+ model:
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+ encoder: dinov3
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+ decoder_dim: 512
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+ decoder_layers: 3
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+ attention_heads: 8
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+ decoder_mode: sequential
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+ use_temporal: false
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+ use_depth: false
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+ use_rays: false
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+ use_bimanual_interaction: true
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+ require_mano: true
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+ assets: {dinov3_source: third_party/dinov3, dinov3_weights: /SSD3/jiasen/foundation_hand/pretrained/dinov3, mano_root: /SSD3/jiasen/foundation_hand/pretrained/mano}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/b_rgb_video_sequential.yaml ADDED
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+ name: b_rgb_video_sequential
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ model:
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+ encoder: dinov3
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+ decoder_dim: 512
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+ decoder_layers: 3
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+ attention_heads: 8
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+ decoder_mode: sequential
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+ use_temporal: true
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+ use_depth: false
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+ use_rays: false
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+ use_bimanual_interaction: true
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+ require_mano: true
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+ assets: {dinov3_source: third_party/dinov3, dinov3_weights: /SSD3/jiasen/foundation_hand/pretrained/dinov3, mano_root: /SSD3/jiasen/foundation_hand/pretrained/mano}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/c_rgb_video_alternating.yaml ADDED
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+ name: c_rgb_video_alternating
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ model:
5
+ encoder: dinov3
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+ decoder_dim: 512
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+ decoder_layers: 3
8
+ attention_heads: 8
9
+ decoder_mode: alternating
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+ use_temporal: true
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+ use_depth: false
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+ use_rays: false
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+ use_bimanual_interaction: true
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+ require_mano: true
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+ assets: {dinov3_source: third_party/dinov3, dinov3_weights: /SSD3/jiasen/foundation_hand/pretrained/dinov3, mano_root: /SSD3/jiasen/foundation_hand/pretrained/mano}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/d_rgb_k_video_alternating.yaml ADDED
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+ name: d_rgb_k_video_alternating
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ model:
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+ encoder: dinov3
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+ decoder_dim: 512
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+ decoder_layers: 3
8
+ attention_heads: 8
9
+ decoder_mode: alternating
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+ use_temporal: true
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+ use_depth: false
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+ use_rays: true
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+ use_bimanual_interaction: true
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+ require_mano: true
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+ assets: {dinov3_source: third_party/dinov3, dinov3_weights: /SSD3/jiasen/foundation_hand/pretrained/dinov3, mano_root: /SSD3/jiasen/foundation_hand/pretrained/mano}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/e_rgb_depth_video_alternating.yaml ADDED
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+ name: e_rgb_depth_video_alternating
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ model:
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+ encoder: dinov3
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+ decoder_dim: 512
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+ decoder_layers: 3
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+ attention_heads: 8
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+ decoder_mode: alternating
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+ use_temporal: true
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+ use_depth: true
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+ depth_mode: log_depth
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+ depth_gate_floor: 0.05
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+ use_rays: false
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+ use_bimanual_interaction: true
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+ require_mano: true
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+ assets: {dinov3_source: third_party/dinov3, dinov3_weights: /SSD3/jiasen/foundation_hand/pretrained/dinov3, mano_root: /SSD3/jiasen/foundation_hand/pretrained/mano}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/e_rgb_depth_video_alternating_fixed_gate.yaml ADDED
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+ name: e_rgb_depth_video_alternating_fixed_gate
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ model:
5
+ encoder: dinov3
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+ decoder_dim: 512
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+ decoder_layers: 3
8
+ attention_heads: 8
9
+ decoder_mode: alternating
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+ use_temporal: true
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+ use_depth: true
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+ depth_mode: log_depth
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+ depth_gate_mode: fixed
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+ depth_gate_fixed_value: 0.5
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+ use_rays: false
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+ use_bimanual_interaction: true
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+ require_mano: true
18
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/f_geometry_ablation.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: f_geometry_ablation
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/f_geometry_fixed_gate_ablation.yaml ADDED
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1
+ name: f_geometry_fixed_gate_ablation
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+ seed: 20260716
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/f_rgb_depth_k_video_alternating.yaml ADDED
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1
+ name: f_rgb_depth_k_video_alternating
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+ seed: 20260716
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+ data: {resolution_hw: [288, 512], T: 8, stride: 1, batch_size: 1}
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+ precision: bf16
home/wuyifan/EgoNet_train_20261008/configs/f_rgb_depth_k_video_alternating_fixed_gate.yaml ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: f_rgb_depth_k_video_alternating_fixed_gate
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+ seed: 20260716
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t0_s20260716.yaml ADDED
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+ name: core_m0_l0_t0_s20260716
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t0_s20260717.yaml ADDED
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+ name: core_m0_l0_t0_s20260717
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t0_s20260718.yaml ADDED
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+ name: core_m0_l0_t0_s20260718
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t1_s20260716.yaml ADDED
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+ name: core_m0_l0_t1_s20260716
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t1_s20260717.yaml ADDED
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+ name: core_m0_l0_t1_s20260717
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l0_t1_s20260718.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t0_s20260716.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m0_l1_t0_s20260717.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l0_t0_s20260716.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t1_s20260716.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l1_t1_s20260718.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l2_t1_s20260716.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l2_t1_s20260717.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/core/core_m3_l2_t1_s20260718.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout005_geometry_m3_l1_t1_s20260716.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout005_geometry_m3_l1_t1_s20260717.yaml ADDED
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+ name: depth_dropout005_geometry_m3_l1_t1_s20260717
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home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout005_geometry_m3_l1_t1_s20260718.yaml ADDED
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home/wuyifan/EgoNet_train_20261008/configs/phase3/depth_fusion/depth_dropout00_geometry_m3_l1_t1_s20260716.yaml ADDED
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+ name: depth_dropout00_geometry_m3_l1_t1_s20260716
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+ global_orientation: 1.0
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+ shape: 0.1
44
+ translation: 10.0
45
+ reprojection: 1.0
46
+ temporal_velocity: 0.1
47
+ temporal_acceleration: 0.05
48
+ bimanual_relative_wrist: 1.0
49
+ presence: 0.0
50
+ assets:
51
+ dinov3_source: third_party/dinov3
52
+ dinov3_weights: /SSD3/jiasen/foundation_hand/pretrained/dinov3
53
+ mano_root: /SSD3/jiasen/foundation_hand/pretrained/mano
54
+ precision: bf16
55
+ protocol:
56
+ max_steps: 100000
57
+ num_workers: 4
58
+ checkpoint_interval: 25000
59
+ validation_interval: 5000
60
+ validation_batches: 256
61
+ learning_rate: 5.0e-05
62
+ min_learning_rate: 5.0e-06
63
+ warmup_steps: 500
64
+ early_stopping_patience: 0
65
+ validation_subset_manifest: artifacts/phase3/validation_subset/validation_subset_256.json