Instructions to use hf-internal-testing/tiny-random-VitPoseForPoseEstimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VitPoseForPoseEstimation with Transformers:
# Load model directly from transformers import AutoImageProcessor, VitPoseForPoseEstimation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-VitPoseForPoseEstimation") model = VitPoseForPoseEstimation.from_pretrained("hf-internal-testing/tiny-random-VitPoseForPoseEstimation") - Notebooks
- Google Colab
- Kaggle
File size: 363 Bytes
2b3854b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"do_affine_transform": true,
"do_normalize": true,
"do_rescale": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "VitPoseImageProcessor",
"image_std": [
0.229,
0.224,
0.225
],
"normalize_factor": 200.0,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 256,
"width": 192
}
}
|