The Automated Image Classification and Labeling System is an advanced solution designed to streamline the process of image classification and labeling. Leveraging the power of RabbitMQ, Flask framework, MongoDB, and the YOLO model, this system provides a seamless and efficient workflow for processing, analyzing, and storing image data.
With this system, users can effortlessly upload images through a user-friendly web interface. The images are then passed to the RabbitMQ messaging queue, ensuring reliable and efficient distribution of image processing tasks. The YOLO model, renowned for its accuracy and efficiency, is employed for image classification and labeling, extracting valuable insights and information from the uploaded images.
The system seamlessly integrates with MongoDB, a robust and scalable database, to store the processed image labels. This enables easy retrieval and management of labeled image data for further analysis or reporting purposes. The user interface of the system is thoughtfully designed, providing an intuitive and visually appealing experience for users to upload images and view the associated labels effortlessly.
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