Instructions to use kerasformers/depth_anything_v2_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/depth_anything_v2_base with KerasFormers:
# 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
- Keras
How to use kerasformers/depth_anything_v2_base with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kerasformers/depth_anything_v2_base") - DepthAnythingV2
How to use kerasformers/depth_anything_v2_base 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="kerasformers/depth_anything_v2_base", 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
Upload kf_preprocessor.json with huggingface_hub
Browse files- kf_preprocessor.json +19 -0
kf_preprocessor.json
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{
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"library_name": "kerasformers",
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"kerasformers_version": "1.1.3",
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"preprocessor_module": "kerasformers.models.depth_anything_v2",
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"preprocessor_class": "DepthAnythingV2ImageProcessor",
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"variant": "depth_anything_v2_base",
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"target_size": 518,
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"data_format": null
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}
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