Technical implementation of multiple outcome generation mechanisms
The program uses multi-threaded calls to the Gemini API to output 10 differentiated fitting effects in parallel in a single request. This is based on the AI model's semantic understanding of clothing materials and human body dynamics: it automatically adjusts detailed elements such as clothing wrinkles, light and shadow reflections, and so on. Compared to the traditional scheme of single result output, batch processing enables users to compare different wearing scenarios (e.g., loose/slim fit) and supports fine-tuning of the generated parameters via the PROMPT command. Test data shows that the generation time for 10 results is stabilized at 47-82 seconds (for 1080P images), which is 60% shorter than the cumulative time consumed for single processing. the results are automatically saved to the results folder, and export in JPG/PNG format is supported.
This answer comes from the articleAI-ClothingTryOn: Gemini-based Virtual Clothing Try-On ToolThe
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