ImageLab Interactive Learning

ImageLab is a block-based image processing tool built with Blockly and OpenCV . It helps students learn image processing by building pipelines with visual blocks. Problem statement: This project has the following key issues: This project will implement "Interactive Learning Mode" transforming ImageLab into a transparent, collaborative, and scalable learning ecosystem. First, per-step processing that returns intermediate image outputs after every operator, displayed in a scrollable filmstrip timeline so students can see the output after each step and what each step is contributing for the final output. Second, an image analysis panel showing RGB histograms and metadata for any selected step. Third, pipeline persistence allowing students to save, load, version, and share pipelines using secure share tokens. Fourth, a batch processing engine to run one pipeline across multiple images concurrently with progress tracking and ZIP download. Fifth, custom composite operators (macros) that let students save reusable block sub-chains into the Blockly toolbox. Deliverables: A production-ready fully tested interactive step viewer, image analysis panel with Canvas-based histogram renderer, SQLModel backed pipeline persistence with HMAC share tokens, asyncio batch processing engine, and a macro system with DAG validation and Blockly toolbox injection.