Exclusive Models Documentation
Table of Contents
Apple Depth Pro
About
Apple Depth Pro is a cutting-edge depth estimation model designed to leverage Apple’s hardware and software capabilities for high-precision depth mapping. It integrates seamlessly with Apple’s vision framework to provide real-time depth perception for various applications.
Requirements
macOS 12.0 or later
Xcode 13 or later
Python 3.8+
PyTorch 1.10+
NumPy
OpenCV
Apple Vision Framework
certifi==2024.12.14
charset-normalizer==3.4.1
contourpy==1.3.0
cycler==0.12.1
-e git+https://github.com/apple/ml-depth-pro.git@b2cd0d51daa95e49277a9f642f7fd736b7f9e91d#egg=depth_pro
filelock==3.17.0
fonttools==4.55.7
fsspec==2024.12.0
huggingface-hub==0.28.0
idna==3.10
importlib_resources==6.5.2
Jinja2==3.1.5
kiwisolver==1.4.7
MarkupSafe==3.0.2
matplotlib==3.9.4
mpmath==1.3.0
networkx==3.2.1
numpy==1.26.4
nvidia-cublas-cu12==12.4.5.8
nvidia-cuda-cupti-cu12==12.4.127
nvidia-cuda-nvrtc-cu12==12.4.127
nvidia-cuda-runtime-cu12==12.4.127
nvidia-cudnn-cu12==9.1.0.70
nvidia-cufft-cu12==11.2.1.3
nvidia-curand-cu12==10.3.5.147
nvidia-cusolver-cu12==11.6.1.9
nvidia-cusparse-cu12==12.3.1.170
nvidia-nccl-cu12==2.21.5
nvidia-nvjitlink-cu12==12.4.127
nvidia-nvtx-cu12==12.4.127
packaging==24.2
pillow==11.1.0
pillow_heif==0.21.0
pyparsing==3.2.1
python-dateutil==2.9.0.post0
PyYAML==6.0.2
regex==2024.11.6
requests==2.32.3
safetensors==0.5.2
six==1.17.0
sympy==1.13.1
timm==1.0.14
tokenizers==0.21.0
torch==2.5.1
torchvision==0.20.1
tqdm==4.67.1
transformers==4.48.1
triton==3.1.0
typing_extensions==4.12.2
urllib3==2.3.0
zipp==3.21.0
Setup
- Create a conda environment:
conda create -n depth-pro -y python=3.9 conda activate depth-pro - Install dependencies:
pip install -r requirements.txt - Build and run the project:
python main.py
Example Code
from univlm.Model import unify
y= unify("AppledepthPro")
y.load()
image_path="input.jpg"
output=y.inference(image_path)