support mmpose and image tagging with vlm

[Cathy0908]

[gemini-code-assist[bot]]

Summary of Changes

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This pull request significantly expands the multimodal processing capabilities by introducing new mappers for advanced image analysis. It enables the generation of detailed image tags using Visual Language Models and facilitates human keypoint detection through MMPose models, leveraging mmdeploy for robust model integration. These additions aim to provide more comprehensive and automated metadata extraction from visual data.

Highlights

• New Image Tagging with VLM: Introduced a new ImageTaggingVLMMapper that leverages Visual Language Models (VLMs) to generate descriptive tags for images. This mapper supports both API-based and vLLM-based models, enhancing the ability to extract rich metadata from visual content.
• New MMPose Mapper for Keypoint Detection: Added a MMPoseMapper to perform human keypoint detection using MMPose models. This mapper integrates with mmdeploy for efficient model inference and can extract detailed pose information, including keypoints, bounding boxes, and scores, with optional visualization capabilities.
• MMLab Model Integration: Integrated mmdeploy to support MMLab models, providing a generic wrapper (MMLabModel) and a preparation function (prepare_mmlab_model) to load and utilize these models within the framework.
• Minor Logging Refinement: Updated several files to reformat a vLLM tensor parallel size logging message, making it more concise and on a single line.

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