We provide 4 models of varying size. Sapiens-0.3B, Sapiens-0.6B, Sapiens-1B, Sapiens-2B. In general, performance improves with increasing the model size.
Best for general in-the-wild scenarios with body keypoints only, adhering to the COCO keypoint format.
Please download the models from hugging-face-pose.
Model | Checkpoint Path |
---|---|
Sapiens-0.3B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_0.3b/sapiens_0.3b_coco_best_coco_AP_796.pth |
Sapiens-0.6B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_0.6b/sapiens_0.6b_coco_best_coco_AP_812.pth |
Sapiens-1B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_1b/sapiens_1b_coco_best_coco_AP_821.pth |
Sapiens-2B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_2b/sapiens_2b_coco_best_coco_AP_822.pth |
Offers second-best generalization with body, face, hands, and feet keypoints, following the COCO-WholeBody keypoint format.
Please download the models from hugging-face-pose.
Model | Checkpoint Path |
---|---|
Sapiens-0.3B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_0.3b/sapiens_0.3b_coco_wholebody_best_coco_wholebody_AP_620.pth |
Sapiens-0.6B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_0.6b/sapiens_0.6b_coco_wholebody_best_coco_wholebody_AP_695.pth |
Sapiens-1B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_1b/sapiens_1b_coco_wholebody_best_coco_wholebody_AP_727.pth |
Sapiens-2B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_2b/sapiens_2b_coco_wholebody_best_coco_wholebody_AP_745.pth |
The highest number of keypoints predictor. Detailed 274 face keypoints. Following the Sociopticon keypoint format. Please download the models from hugging-face.
Model | Checkpoint Path |
---|---|
Sapiens-0.3B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_0.3b/sapiens_0.3b_goliath_best_goliath_AP_573.pth |
Sapiens-0.6B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_0.6b/sapiens_0.6b_goliath_best_goliath_AP_609.pth |
Sapiens-1B | $SAPIENS_CHECKPOINT_ROOT/pose/checkpoints/sapiens_1b/sapiens_1b_goliath_best_goliath_AP_639.pth |
Navigate to the script directory and launch the inference scripts for your desired keypoint configuration.
- Navigate to your script directory:
cd $SAPIENS_ROOT/pose/scripts/demo/local
- For 17 keypoints estimation (uncomment your model config line for inference):
./keypoints17.sh
- For 133 keypoints estimation (uncomment your model config line for inference):
./keypoints133.sh
- For 308 keypoints estimation (uncomment your model config line for inference):
./keypoints308.sh
Define INPUT
for your image directory and OUTPUT
for results. Visualization and keypoints in JSON format are saved to OUTPUT
. Customize LINE_THICKNESS
, RADIUS
, and KPT_THRES
as needed. Adjust JOBS_PER_GPU
, TOTAL_GPUS
and VALID_GPU_IDS
for multi-GPU configurations.
Generate OpenPose skeletons on a black background, compatible with ControlNet.
- Navigate to your script directory:
cd $SAPIENS_ROOT/pose/scripts/demo/local
- For 17 keypoints estimation (uncomment your model config line for inference):
./keypoints17_openpose.sh
- For 133 keypoints estimation (uncomment your model config line for inference):
./keypoints133_openpose.sh
Customization options as mentioned above are applicable here as well.