Web based platform for Image Processor - Python - Flask - HTML5
I have developed a web-based image processing platform using Python (Flask), JavaScript, HTML/CSS, and Pillow (PIL). This project demonstrates my skills in server-side development, client-side interactivity, and image manipulation through a user-friendly interface.
Key Technical Contributions
1. Image Upload (Drag-and-Drop + File Selector)
Tech Stack: Flask backend + HTML5 + JavaScript
Implemented secure, session-tracked image uploading via drag-and-drop or manual selection.
Used uuid to assign unique session IDs to isolate editing history per user ( Skills: Session management, Web development, User experience).
2. Image Resizing (with aspect ratio sync in px/cm)
Backend: Used Pillow’s .resize() method to modify image dimensions.
Frontend: Enabled synchronized resizing in pixels and centimeters, with optional aspect ratio lock.
Skills: Image transformation, Aspect ratio maintenance, Interactive UI, Numerical input validation.
3. Brightness Adjustment
Functionality: Dynamically enhanced image brightness using ImageEnhance.Brightness.
Integrated a real-time slider on the frontend.
Skills: Dynamic user controls, Image enhancement, Front-end/backend integration.
4. Background Removal (White & Custom Color)
Built-in detection for white or user-specified RGB backgrounds using transparency conversion in RGBA mode.
Included color picker and tolerance range for flexibility.
Skills: Image masking, Background subtraction, Custom filter application, Color tolerance logic.
5. Filter Application Engine
Supported Filters: Gaussian, Sobel, Prewitt, Bandpass, CLAHE, Bilateral, Canny Edge, etc.
Combined OpenCV with Pillow to support advanced computer vision filters.
Included thresholding for binary segmentation.
Skills: Computer vision, Edge detection, Image filtering, OpenCV integration.
6. Text Enhancement for OCR Readiness
Added a filter pipeline for text sharpening and contrast enhancement using UnsharpMask and Contrast.
Skills: OCR preprocessing, Text clarity, Visual optimization.
7. Undo Feature (with image stack and deepcopy)
Each user session maintains an undo stack using copy.deepcopy() to preserve previous image states.
Implemented non-destructive editing, ensuring rollback capability.
Skills: Undo stack, State management, Image versioning, Deep copy logic.
8. Secure Download Functionality
Users can download the final processed image directly using Flask’s send_file() endpoint.
Skills: Download handling, File I/O, Blob handling, Secure data access.
Technologies Used
Programming Languages: Python, JavaScript, HTML, CSS
Libraries: Flask, Pillow (PIL), OpenCV (cv2), NumPy
Design Tools: HTML5 forms, Canvas previews, Interactive controls
Deployment Ready: Session-based, cleanup handlers, upload/download APIs
Skills: Flask framework, Image processing, Computer vision, Back-end API development, Stateful user sessions, Front-end integration.
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