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Description: A web platform for CloudCV where users can upload, browse, and download pre-trained computer vision models, with automated benchmarking on standard datasets. Results are displayed in an interactive AngularJS dashboard, and models are containerized with Docker for reproducibility.
Features:
Model registry with Django backend and AWS S3 storage.
Automated benchmarking using Python and Docker, executed on AWS.
AngularJS frontend for browsing and visualizing results.
Reproducibility via downloadable Docker images and collaboration via comments.
Impact: Enhances CloudCV’s ecosystem by providing a collaborative hub for sharing and comparing vision models, making AI research more reproducible and accessible.
Skills: Python, Django, Docker, AngularJS, AWS, computer vision, deep learning.
Mentor Notes: Could integrate with EvalAI or support specific model formats (e.g., ONNX).