Instructions to use a-ml/FaceDepth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- DepthAnythingV2
How to use a-ml/FaceDepth with DepthAnythingV2:
# Install from https://github.com/DepthAnything/Depth-Anything-V2 # Load the model and infer depth from an image import cv2 import torch from depth_anything_v2.dpt import DepthAnythingV2 # instantiate the model model = DepthAnythingV2(encoder="<ENCODER>", features=<NUMBER_OF_FEATURES>, out_channels=<OUT_CHANNELS>) # load the weights filepath = hf_hub_download(repo_id="a-ml/FaceDepth", filename="depth_anything_v2_<ENCODER>.pth", repo_type="model") state_dict = torch.load(filepath, map_location="cpu") model.load_state_dict(state_dict).eval() raw_img = cv2.imread("your/image/path") depth = model.infer_image(raw_img) # HxW raw depth map in numpy - Notebooks
- Google Colab
- Kaggle
Add Core ML fp32 (unquantized reference)
Browse files
coreml/FaceDepth_fp32.mlpackage/Data/com.apple.CoreML/model.mlmodel
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version https://git-lfs.github.com/spec/v1
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oid sha256:17ed8a1f725712dc54ff3e2a8e9c7959e31ef7f702248580281fd94eb94d77a8
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size 286886
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coreml/FaceDepth_fp32.mlpackage/Data/com.apple.CoreML/weights/weight.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a213bec4653af8874402f2d4b4ee7e6cd195a725b1188e62bff0eb0c8edd0902
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size 1335199616
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coreml/FaceDepth_fp32.mlpackage/Manifest.json
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{
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"fileFormatVersion": "1.0.0",
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"itemInfoEntries": {
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"49489823-C7EA-413B-B501-AD7376EBE47E": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Weights",
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"name": "weights",
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"path": "com.apple.CoreML/weights"
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},
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"EDF06A3A-2C50-4E5F-87CC-0BDCE336E4BD": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Specification",
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"name": "model.mlmodel",
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"path": "com.apple.CoreML/model.mlmodel"
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}
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},
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"rootModelIdentifier": "EDF06A3A-2C50-4E5F-87CC-0BDCE336E4BD"
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}
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