Depth Estimation
Transformers
Safetensors
prompt_depth_anything
prompt-depth-anything
metric-depth
custom_code
Instructions to use bigshanedogg/Prompt-Depth-Anything-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigshanedogg/Prompt-Depth-Anything-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="bigshanedogg/Prompt-Depth-Anything-Large", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("bigshanedogg/Prompt-Depth-Anything-Large", trust_remote_code=True) model = AutoModelForDepthEstimation.from_pretrained("bigshanedogg/Prompt-Depth-Anything-Large", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from bigshanedogg/Prompt-Depth-Anything-Large: direct link, hf CLI and curl.
- Browser
- Download file 492 Bytes
-
https://huggingface.co/bigshanedogg/Prompt-Depth-Anything-Large/resolve/main/processor_config.json
- Command line
-
hf download hf://bigshanedogg/Prompt-Depth-Anything-Large/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/bigshanedogg/Prompt-Depth-Anything-Large/resolve/main/processor_config.json
492 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_prompt_depth_anything.PromptDepthAnythingProcessor" | |
| }, | |
| "image_processor": { | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_prompt_depth_anything.PromptDepthAnythingImageProcessor", | |
| "AutoProcessor": "processing_prompt_depth_anything.PromptDepthAnythingProcessor" | |
| }, | |
| "image_processor_type": "PromptDepthAnythingImageProcessor", | |
| "max_size": 1008 | |
| }, | |
| "processor_class": "PromptDepthAnythingProcessor" | |
| } | |