Instructions to use py-feat/retinaface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Py-Feat
How to use py-feat/retinaface with Py-Feat:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| { | |
| "name": "mobilenet0.25", | |
| "min_sizes": [ | |
| [ | |
| 16, | |
| 32 | |
| ], | |
| [ | |
| 64, | |
| 128 | |
| ], | |
| [ | |
| 256, | |
| 512 | |
| ] | |
| ], | |
| "steps": [ | |
| 8, | |
| 16, | |
| 32 | |
| ], | |
| "variance": [ | |
| 0.1, | |
| 0.2 | |
| ], | |
| "clip": false, | |
| "loc_weight": 2.0, | |
| "gpu_train": true, | |
| "batch_size": 32, | |
| "ngpu": 1, | |
| "epoch": 250, | |
| "decay1": 190, | |
| "decay2": 220, | |
| "image_size": 640, | |
| "pretrain": false, | |
| "return_layers": { | |
| "stage1": 1, | |
| "stage2": 2, | |
| "stage3": 3 | |
| }, | |
| "in_channel": 32, | |
| "out_channel": 64, | |
| "resize": 1, | |
| "detection_threshold": 0.5, | |
| "nms_threshold": 0.1, | |
| "top_k": 5000, | |
| "keep_top_k": 750, | |
| "confidence_threshold": 0.02, | |
| "pretrained": "local" | |
| } |