Batch Image Resizer and Converter

Resizing images one by one is drudgery: a student with 40 project photos, or a seller with 200 product shots, faces the same repetitive loop of open-resize-save in an editor. Online batch tools exist but require uploading personal photos to a stranger's server, and most cap file counts or watermark the output. This project builds a desktop batch image resizer and converter that processes entire queues locally. The user drops in any number of JPG, PNG or WebP files, selects a max-width preset (1920, 1280, 800 px or custom), picks an output format and quality, and the app resizes every image while preserving aspect ratio — reporting original vs resized dimensions and the percentage saved per file, with a before/after comparison view for any image. Because the pipeline runs in the browser engine's canvas, the tool works identically as a desktop app or a web page, fully offline.

1. The user drags image files into the drop zone (or clicks to browse); each file is read locally and shown as a thumbnail with its native dimensions.
2. The user picks a max-width preset or enters a custom width, selects JPG/PNG/WebP output, sets quality, and optionally a filename prefix.
3. On "Process batch", each image is drawn onto an offscreen HTML canvas scaled so its width equals the target (scale capped at 1.0 — images are never upscaled).
4. The canvas is serialized with toDataURL in the chosen format and quality, producing the resized file entirely in memory.
5. A results table is built: original dimensions/size vs resized dimensions/size, with the percentage saved computed per file.
6. Clicking a row opens the before/after comparison; each row's Download button saves that file with the configured prefix.

Tech stack:

• HTML5 Canvas API (resize pipeline)
• JavaScript FileReader API (local file intake)
• Electron (desktop packaging)
• HTML/CSS (queue and results UI)
• WebP/JPG/PNG encoders (browser-native)

• [Batch queue] Drag-and-drop any number of JPG, PNG or WebP files; each shows a thumbnail with its original dimensions before processing.
• [Width presets] One-click targets — Full HD 1920 px, HD 1280 px, web 800 px — plus a custom width field; aspect ratio is always preserved automatically.
• [Format conversion] Output to JPG, PNG or WebP with a quality slider (40–100), so the same batch can be optimized for print or for fast web pages.
• [Per-file savings report] A results table shows original vs resized dimensions, file sizes and the percentage saved for every image — the numbers that justify the tool.
• [Before/after comparison] Click any processed row to see the original and resized images side by side with their dimensions.
• [Individual downloads] Each result has its own download button with an automatic renamed file (configurable prefix), plus the originals are never modified.
• [Fully offline] The canvas-based pipeline never uploads images; a folder of private photos stays private.

• Complete application source code (desktop + web-usable)
• Electron packaging configuration
• User manual with resize/convert walkthroughs
• Project report PDF (background, canvas scaling design, format trade-offs, methodology)
• PPT presentation for final review
• Viva Q&A preparation document (image formats, canvas API, lossy vs lossless, file handling)

• Images are never upscaled — a 400 px wide photo stays 400 px even if the preset is 1920 px; upscaling would only invent pixels.
• No cropping, rotation or watermarking in this version; those are documented as planned extensions.
• Very large source images (50+ MP) are processed one at a time in memory and may be slow on low-RAM machines.
• EXIF metadata (camera settings, GPS) is not preserved in the resized output — noted honestly in the manual.
• Output quality below ~60 can show visible compression artifacts on detailed photos; the slider default is 85 as a balanced choice.