Solution: Step-by-step reasoning using visual thought chains
To address the problem of unclear steps in complex image analysis, Skywork-R1V provides a specialized Chain-of-Thought function. The following are the specific operation steps:
- Preparing the input material: Save complex images to be analyzed (e.g., infographics or flowcharts with multiple elements) as JPG/PNG files.
- Preparation of leading questions:: Use structured questioning, e.g., "Explain XX process in the image in steps" or "The picture shows several main parts, explain how they relate to each other."
- Configuring Inference Parameters: Set the detail_level=high parameter in reference_with_transformers.py to enable detailed explanation mode
- Running the inference engine: Add the -verbose parameter when executing the command to get the full inference path:
python inference_with_transformers.py --verbose 1...
Other optimization methods include: using an Example-guided approach to provide standard analysis templates for similar problems; adjusting the temperature parameter to control the deterministic nature of the output; and, for specialized technical images, pre-inputting a dictionary of relevant terms to improve parsing accuracy.
This answer comes from the articleSkywork-R1V: A Graphical Hybrid Multimodal Reasoning Model Open Source by Kunlun WanwenThe
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