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Commit History
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Add Gradio app for inference and model selection
- Introduced app.py for a Gradio interface allowing users to upload images and select between baseline and GNN models for inference. - Implemented ModelRegistry for caching loaded models and managing checkpoints. - Added README_SPACE.md to guide users on setting up the Hugging Face Space with the necessary files and configurations. - Created requirements-space.txt for dependencies specific to the Gradio app. - Developed scripts for single-image inference and comparison of baseline vs GNN model metrics. - Enhanced existing README.md with updated training and evaluation instructions for both models.419fc11 -
Add data pipeline scripts and configuration files for Visual Genome processing
Ashish Mehta- Introduced .gitignore to exclude unnecessary files and directories. - Added requirements.txt for project dependencies. - Implemented dataset.yaml with download, extraction, and processing configurations. - Created multiple scripts for data handling: download, extract, process, and build splits. - Developed run_baselines.py and eval_baseline.py for baseline model evaluation. - Enhanced README.md with data pipeline instructions and expected outputs. - Established src/data module for data utilities and processing functions.4687353
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Add initial project structure and configuration files for Adjective-Aware Object Embedding
Ashish Mehta- Created README.md detailing project objectives, structure, and execution strategy. - Added dataset.yaml for dataset configuration, including attribute taxonomy and splits. - Introduced eval.yaml for evaluation metrics and visualization settings. - Established experiment.yaml for defining baseline and proposed runs. - Configured model.yaml for encoder settings and GNN architecture. - Developed train.yaml for training parameters and optimization strategies. - Drafted plan_draft.md outlining project goals, architecture, and data preparation strategies.8e53dc6 -
first commit
Ashish Mehtaecc9495