tomrussobuilds/orchard-ml
Modular PyTorch framework: Pydantic schemas + Optuna optimization + resolution-aware architectures for vision research
This tool helps computer vision researchers and scientists reliably train deep learning models for image classification and object detection. You provide image datasets and configuration settings, and it automatically trains and optimizes models for tasks like medical image analysis or astronomical object identification. The output is a well-performing model ready for deployment or further research, along with detailed experiment logs.
Used by 1 other package. Available on PyPI.
Use this if you need a structured and reproducible way to conduct computer vision experiments, especially when working with diverse image resolutions and managing multiple model architectures.
Not ideal if you are a beginner looking for a simple drag-and-drop solution without any coding, or if your primary focus is on non-vision deep learning tasks.
Stars
11
Forks
—
Language
Python
License
MIT
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
Dependencies
25
Reverse dependents
1
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