Instructions to use zeromodels/depth_anything_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/depth_anything_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 zeromodels/depth_anything_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://zeromodels/depth_anything_large") - Notebooks
- Google Colab
- Kaggle
File size: 816 Bytes
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"library_name": "kerasformers",
"kerasformers_version": "1.2.1",
"model_module": "kerasformers.models.depth_anything_v1",
"model_class": "DepthAnythingV1DepthEstimation",
"variant": "depth_anything_large",
"weights": "model.weights.h5",
"schema_version": 2,
"weight_dtype": "float32",
"model_type": "depth_anything",
"vision_config": {
"backbone_dim": 1024,
"backbone_depth": 24,
"backbone_num_heads": 16,
"out_indices": [
21,
22,
23,
24
],
"neck_hidden_sizes": [
256,
512,
1024,
1024
],
"fusion_hidden_size": 256,
"reassemble_factors": [
4,
2,
1,
0.5
],
"depth_estimation_type": "relative",
"max_depth": 1.0,
"image_size": 518
}
} |