Instructions to use dl1wjd2/Logistics_AX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dl1wjd2/Logistics_AX with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("dl1wjd2/Logistics_AX", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download training/evaluation.json from dl1wjd2/Logistics_AX: direct link, hf CLI and curl.
- Browser
- Download file 976 Bytes
-
https://huggingface.co/dl1wjd2/Logistics_AX/resolve/main/training/evaluation.json
- Command line
-
hf download hf://dl1wjd2/Logistics_AX/training/evaluation.json
-
curl -L -o evaluation.json https://huggingface.co/dl1wjd2/Logistics_AX/resolve/main/training/evaluation.json
976 Bytes
| { | |
| "run": "pallet_pose_20261029T110641464517Z", | |
| "best_epoch": 95, | |
| "epochs_completed": 100, | |
| "counts": { | |
| "train": 124, | |
| "val": 31, | |
| "test": 0 | |
| }, | |
| "metrics": { | |
| "metrics/precision(B)": 0.9973, | |
| "metrics/recall(B)": 1.0, | |
| "metrics/mAP50(B)": 0.995, | |
| "metrics/mAP50-95(B)": 0.84352, | |
| "metrics/precision(P)": 0.96062, | |
| "metrics/recall(P)": 0.91667, | |
| "metrics/mAP50(P)": 0.915, | |
| "metrics/mAP50-95(P)": 0.915, | |
| "val/box_loss": 0.91957, | |
| "val/pose_loss": 0.07617, | |
| "val/kobj_loss": 0.12809, | |
| "val/cls_loss": 0.12259, | |
| "val/l1_loss": 0.00793, | |
| "val/rle_loss": 0.0, | |
| "fitness": 1.75852 | |
| }, | |
| "weights_sha256": "6b91d8fbb1dc62eb6ccd1c10ae312908d0204e87d62cb3af78e5a1d25065b8ca", | |
| "dataset": { | |
| "repo_id": "dl1wjd2/Logistics_AX", | |
| "revision": "v2026-10-29-155", | |
| "manifest_sha256": "558615a635ffd24dc612fb81e143998cccb9ca7cb30518fe4213578c7b5f2b19", | |
| "commit": "ca1a17875de52c422d557107432be7616171c6e9" | |
| } | |
| } | |