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qualityAn MCP server that reviews UI edit requests by comparing before and after screenshots, providing visual feedback on whether changes satisfy the user's requirements.
Last updated 7 months ago
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GPL 2.0
Ultralytics YOLO is an open-source computer vision model family known for real-time object detection, image/video segmentation, and classification.
Why this server?
Recommends using YOLO mode in Cursor settings for optimal experience with the frontend review tool.
Why this server?
Recommends using YOLO mode for optimal experience, suggesting the MCP server works best with this feature enabled in Cursor settings.
Why this server?
Recommends using YOLO mode in Cursor settings to optimize the frontend review experience, allowing for more seamless interaction with the visual review tools.
Why this server?
Requires YOLO mode to be enabled in Cursor settings for optimal experience with the webdev-mcp server's screenshot functionality.
Why this server?
Leverages YOLO (You Only Look Once) models for advanced computer vision tasks including object detection, segmentation, classification, and pose estimation with support for model training, validation, and export
Why this server?
Integrates YOLO object detection models for identifying and locating objects in images with customizable confidence settings.
Why this server?
Supports deployment and optimization of YOLO models for object detection on Jetson Nano devices.
Why this server?
Integrates YOLO for clothing detection in user-uploaded images, which are then processed by CLIP for encoding and recommendation.
Why this server?
Exposes YOLO's object detection capabilities through a RESTful API, enabling training custom models, performing predictions, tracking objects in videos, and exporting models to different formats.