Visual Content Processing Core Technology
The system is operated through theMultimodal Filter PipesRealize intelligent image processing:
- Acquisition phase: Adoption of a hybrid crawling strategy that simultaneously retrieves open image libraries such as Google Images, Wikimedia Commons, etc., and is tied to a text content relevance score (threshold default 0.75)
- Mass filtration: Apply CV algorithms to detect parameters such as resolution (minimum 800×600), watermark (rejection rate >15%), color gamut anomalies, etc.
- semantic matching: Calculate graphic embedding similarity using the CLIP model and filter mismatched candidate images
- Copyright Compliance: Automatically filter CC-BY licensed content, commercial version supports Shutterstock and other paid gallery docking
The user can set in config.yaml theimage_strictness: 1-5Adjust the stringency or pass the--no-imagesparameter to disable the feature completely. Typical reports will contain 3-5 calibrated matching images with automatically generated alt-text descriptions.
This answer comes from the articleGPT Researcher: Generate comprehensive, detailed research reports utilizing local and web-based dataThe
May not be reproduced without permission:AI productivity tools " How does GPT Researcher's Smart Image Capture feature work? What are the filtering mechanisms?
