Image Enhancer

Upscale and clean up images with classic resampling and Pillow's enhancement filters — no machine-learning model, no OpenCV. It resizes to a target resolution (up to 8K) using Lanczos/bicubic resampling, then optionally sharpens, adjusts contrast and saturation, and runs a light denoise/edge pass.

Comes in three forms, all built on the same Pillow pipeline:

Entry point	What it is
image enchancer/enhancer_gui.py	Tkinter desktop app (also works as a CLI) — file/folder picker, presets, sliders, progress bar, activity log
image enchancer/enhancer_pro.py	Command-line tool with presets and batch mode
image enchancer/web/app.py	Flask web UI — upload an image, tune settings, download the result
image enchancer/enhancer.py	Minimal script: resize to 4K/8K, nothing else

Quick start

pip install Pillow                 # GUI + CLI
pip install Pillow flask flask-cors # also the web app

# desktop app
python "image enchancer/enhancer_gui.py"

# CLI: 4K, vivid preset
python "image enchancer/enhancer_pro.py" photo.jpg -r 4k --preset vivid

# batch a folder
python "image enchancer/enhancer_pro.py" ./photos --batch -r 4k

# web app  → http://localhost:5000
python "image enchancer/web/app.py"

What it actually does

• Resize — Lanczos (default), bicubic, bilinear, nearest or box, to 720p / 1080p / 2K / 4K / 8K
• Sharpen / contrast / saturation — PIL.ImageEnhance, 0.5–3.0
• Denoise / edge enhance — PIL.ImageFilter passes, toggleable
• Presets — photo, artwork, text, soft, vivid, hdr bundle the above
• Output — written to an enhanced/ folder next to the input, named name_resolution_preset.jpg

Upscaling past the source resolution interpolates pixels — it will not recover detail that isn't in the original. For that you'd need a super-resolution model, which this tool deliberately doesn't ship.

See image enchancer/README.md for the full option list.