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...It supplies cwebp to compress images into WebP and dwebp to decompress them back, making it easy to test quality/size trade-offs across presets and tuning parameters. The GitHub repository is a mirror; the canonical source of truth lives on Chromium’s git, and developer docs are hosted on WebP’s portal. The project underpins WebP support across browsers, imaging libraries, and many native apps thanks to its stable C API. Additional companion repos host test data and demos, including JavaScript builds and timing tests for various platforms. As a widely deployed codec, libwebp balances compression efficiency, speed, and integration simplicity across platforms.

...Features Multi-instrument Support: Process both MIRI and NIRCam data Background Matching: Automatic background leveling across exposures Cosmic Ray Rejection: Advanced cosmic ray identification and removal Seamless Mosaicking: Create continuous field mosaics from dithered observations Source Extraction: Generate segmentation maps and source catalogs Calibration-ready: Works with JWST pipeline products (_cal.fits, _rate.fits) Memory Efficient: Handles large JWST datasets efficiently Installation Prerequisites Python 3.8 or higher JWST calibration pipeline 4GB+ RAM recommended for large mosaics Quick Install git clone https://github.com/tlcagford/JWST-Merge cd JWST-Merge pip install -r requirements.txt