Instructions to use kerasformers/depth_anything_v2_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/depth_anything_v2_large 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_large 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_large") - Notebooks
- Google Colab
- Kaggle
Upload kf_config.json with huggingface_hub
Browse files- kf_config.json +34 -0
kf_config.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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"model_module": "kerasformers.models.depth_anything_v2",
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"model_class": "DepthAnythingV2DepthEstimation",
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"variant": "depth_anything_v2_large",
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"weights": "model.weights.h5",
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"model_type": "depth_anything",
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"backbone_dim": 1024,
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"backbone_depth": 24,
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"backbone_num_heads": 16,
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"out_indices": [
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5,
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12,
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18,
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24
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],
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"neck_hidden_sizes": [
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256,
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512,
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1024,
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1024
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],
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"fusion_hidden_size": 256,
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"reassemble_factors": [
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4,
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2,
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1,
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0.5
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],
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"depth_estimation_type": "relative",
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"max_depth": 1.0,
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"image_size": 518
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}
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