Depth Estimation
Transformers
Safetensors
depth_anything_v1
feature-extraction
depth-anything
custom_code
Instructions to use bigshanedogg/Depth-Anything-V1-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigshanedogg/Depth-Anything-V1-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="bigshanedogg/Depth-Anything-V1-Base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bigshanedogg/Depth-Anything-V1-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from bigshanedogg/Depth-Anything-V1-Base: direct link, hf CLI and curl.
- Browser
- Download file 582 Bytes
-
https://huggingface.co/bigshanedogg/Depth-Anything-V1-Base/resolve/main/config.json
- Command line
-
hf download hf://bigshanedogg/Depth-Anything-V1-Base/config.json
-
curl -L -o config.json https://huggingface.co/bigshanedogg/Depth-Anything-V1-Base/resolve/main/config.json
582 Bytes
| { | |
| "architectures": [ | |
| "DepthAnythingV1ForDepthEstimation" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_depth_anything_v1.DepthAnythingV1Config", | |
| "AutoModel": "modeling_depth_anything_v1.DepthAnythingV1ForDepthEstimation", | |
| "AutoModelForDepthEstimation": "modeling_depth_anything_v1.DepthAnythingV1ForDepthEstimation" | |
| }, | |
| "dtype": "float32", | |
| "encoder": "vitb", | |
| "features": 128, | |
| "model_type": "depth_anything_v1", | |
| "out_channels": [ | |
| 96, | |
| 192, | |
| 384, | |
| 768 | |
| ], | |
| "transformers_version": "5.20.2", | |
| "use_bn": false, | |
| "use_clstoken": false | |
| } | |