mehdidc/DALLE_clip_score
Simple script to compute CLIP-based scores given a DALL-e trained model.
This tool helps researchers and developers evaluate the quality of images generated by a DALL-E model. You provide your trained DALL-E model and a dataset of real images with their corresponding text captions. The tool then calculates various "CLIP scores" that indicate how well the generated images match their intended captions, and also how they compare to real images. This is useful for anyone working on text-to-image generation models to understand and improve their performance.
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Use this if you are developing or fine-tuning a text-to-image generation model, specifically DALL-E, and need quantitative metrics to assess the image-text alignment of your model's outputs.
Not ideal if you are looking for a tool to generate images directly or to evaluate image quality based on human perception rather than a model-based metric.
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Language
Python
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Last pushed
Jun 13, 2021
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Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/mehdidc/DALLE_clip_score"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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