Instructions to use kerasformers/depth_anything_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/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 kerasformers/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://kerasformers/depth_anything_large") - Notebooks
- Google Colab
- Kaggle
| { | |
| "library_name": "kerasformers", | |
| "kerasformers_version": "1.1.3", | |
| "model_module": "kerasformers.models.depth_anything_v1", | |
| "model_class": "DepthAnythingV1DepthEstimation", | |
| "variant": "depth_anything_large", | |
| "weights": "model.weights.h5", | |
| "model_type": "depth_anything", | |
| "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 | |
| } |