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
File size: 461 Bytes
1e46918 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"auto_map": {
"AutoProcessor": "processing_depth_anything_v1.DepthAnythingV1Processor"
},
"image_processor": {
"auto_map": {
"AutoImageProcessor": "image_processing_depth_anything_v1.DepthAnythingV1ImageProcessor",
"AutoProcessor": "processing_depth_anything_v1.DepthAnythingV1Processor"
},
"image_processor_type": "DepthAnythingV1ImageProcessor",
"input_size": 518
},
"processor_class": "DepthAnythingV1Processor"
}
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