Depth Estimation
Core ML
Depth Pro
visionos
apple-silicon
amlr
computer-vision
512x512
ane-optimized
Instructions to use aarondevstack/DepthPro-512x512-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Depth Pro
How to use aarondevstack/DepthPro-512x512-coreml with Depth Pro:
# Download checkpoint pip install huggingface-hub huggingface-cli download --local-dir checkpoints aarondevstack/DepthPro-512x512-coreml
import depth_pro # Load model and preprocessing transform model, transform = depth_pro.create_model_and_transforms() model.eval() # Load and preprocess an image. image, _, f_px = depth_pro.load_rgb("example.png") image = transform(image) # Run inference. prediction = model.infer(image, f_px=f_px) # Results: 1. Depth in meters depth = prediction["depth"] # Results: 2. Focal length in pixels focallength_px = prediction["focallength_px"] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 856c0c296636fe98e681d9efcf02d2cb934db6d512bbbb027d20bfc367b058d8
- Size of remote file:
- 558 kB
- SHA256:
- 44614936d9717f42f27cf5675f11e5b06c9d1f297f7ca1ff599ed631efc65978
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