Commit History

major(feat): add support for Gradio API model and enhance ONNX model handling
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less load: inference shouldn't take longer than 3 seconds...
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feat: refactor prediction functions and enhance image loading capabilities for improved processing and noise estimation
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feat: enhance model registration by adding architecture and dataset metadata to the ModelEntry class
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feat: implement new app structure with enhanced ensemble prediction capabilities and integrate multiple models for image analysis
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refactor: update import paths for forensics utilities and enhance logging functionality in inference data
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refactor: simplify ELA function name and clean up unused augmentations in Gradio interface
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refactor: ensemble monitoring and weight optimization agents, refactor minmax processing function, and update requirements
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fix: ensure Hugging Face API token is used for dataset repository initialization
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feat: implement CommitScheduler for automated logging to Hugging Face dataset and refactor dataset initialization process
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fix: enable dataset logging to Hugging Face Hub by uncommenting push_to_hub functionality
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feat: implement custom JSON encoder for numpy types and ensure type consistency in inference results
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feat: improve JSON handling and type safety in inference results and dataset logging
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feat: add detailed logging for input types in inference data processing
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feat: enhance image handling by ensuring input is a PIL Image and updating forensic image logging
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major(feat): restructure models and introduce new monitoring and weight management agents
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feat: add logging
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make clear distinction between ensemble agents and smart agents
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major: prep implementtation of vLLM smart agents
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cv2
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(major)feat: add new functionalities for AI-generated content detection
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UPDATED: Updated ELA image processing in app.py and ela.py
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πŸ—οΈ build(utils): update image preprocess and functionality expansion
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```
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πŸ› fix(image processing): ensure image consistency for gradient and minmax preprocessors
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✨ feat(image processing): add MinMax pre-processing to image pipeline
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✨ feat(image): add gradient processing in predict_image Function
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✨ feat(predict): add Error Level Analysis to image prediction
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✨ feat(ui): add sharpen and noise augmentation
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πŸ› fix(app): add input degrees having a bug for cases without augmentation
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♻️ refactor(app): code cleanup
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Refactor project interface and remove unused utility files
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ethix commited on

Refine UI layout and GOAT inference call
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Update utils/goat.py
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Update utils/goat.py
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Create __init__.py
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Create goat.py
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Create utils/onnx.py
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