LibreYOLO9s Pose

--- license: mit library_name: libreyolo tags: - object-detection - pose-estimation - keypoints - yolo9 - coco --- # LibreYOLO9s-pose This repository contains `LibreYOLO9s-pose.pt`, an EXTREMELY experimental LibreYOLO9-s pose-estimation checkpoint for COCO-17 human keypoints. ## Experimental Status These weights are published as an early preview so LibreYOLO users can test the new `task="pose"` path. They are not a final production model, may be replaced, and may change without compatibility guarantees. ## Validation Snapshot - Training data: COCO person keypoints - Task: single-class person pose, 17 keypoints, `kpt_shape: [17, 3]` - Run: 30 epochs, 640 image size - Best checkpoint: epoch 30 - COCO val keypoints AP50-95: 0.5739 - COCO val keypoints AP50: 0.8310 ## Usage ```python from libreyolo import LibreYOLO model = LibreYOLO("yolo9-s-pose") result = model("image.jpg") print(result.keypoints) ``` Autodownload in LibreYOLO emits an experimental warning for this checkpoint. ## Source Trained by LibreYOLO contributors with the LibreYOLO pose-training implementation, initialized from the LibreYOLO9-s detection checkpoint and fine-tuned on COCO person keypoints. ## Modifications This is a native LibreYOLO training checkpoint with LibreYOLO checkpoint metadata. It is not a direct upstream conversion. ## License MIT License. See the [`LICENSE`](./LICENSE) file in this repository.

Source context: 0 downloads · 0 likes · Pipeline object-detection · Library libreyolo · Repo LibreYOLO/LibreYOLO9s-pose