ysig/diff-mining
Diffusion Models as Data Mining Tools
This project helps researchers and analysts understand what specific visual elements in images are most representative or 'typical' for a given category. You provide a collection of labeled images (e.g., photos of different car models, types of scenes, or medical X-rays with conditions), and it identifies and groups the key visual patches that define each label. This allows image analysts, medical researchers, or urban planners to gain insights into distinguishing visual features.
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Use this if you need to pinpoint and categorize the most characteristic visual components within a large dataset of images that belong to different labels.
Not ideal if you are looking to generate entirely new images, perform basic image classification, or if your dataset consists of non-visual data.
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Language
Python
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Last pushed
May 12, 2025
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