Instructions to use usyd-community/vitpose-base-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usyd-community/vitpose-base-simple with Transformers:
# Load model directly from transformers import AutoImageProcessor, VitPoseForPoseEstimation processor = AutoImageProcessor.from_pretrained("usyd-community/vitpose-base-simple") model = VitPoseForPoseEstimation.from_pretrained("usyd-community/vitpose-base-simple") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
CHANGED
|
@@ -8,7 +8,7 @@ pipeline_tag: keypoint-detection
|
|
| 8 |
|
| 9 |
# Model Card for VitPose
|
| 10 |
|
| 11 |
-
<img src="https://cdn-uploads.huggingface.co/production/uploads/6579e0eaa9e58aec614e9d97/ZuIwMdomy2_6aJ_JTE1Yd.png" alt="x" width="
|
| 12 |
|
| 13 |
ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation and ViTPose+: Vision Transformer Foundation Model for Generic Body Pose Estimation. It obtains 81.1 AP on MS COCO Keypoint test-dev set.
|
| 14 |
|
|
|
|
| 8 |
|
| 9 |
# Model Card for VitPose
|
| 10 |
|
| 11 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/6579e0eaa9e58aec614e9d97/ZuIwMdomy2_6aJ_JTE1Yd.png" alt="x" width="400"/>
|
| 12 |
|
| 13 |
ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation and ViTPose+: Vision Transformer Foundation Model for Generic Body Pose Estimation. It obtains 81.1 AP on MS COCO Keypoint test-dev set.
|
| 14 |
|