scombat/wiot-image-optimizer

AI Summary: Implement a Gaussian blur filter in the WIOT image processing pipeline. This involves creating a `BlurOptions` struct, integrating it into the `ProcessingOptions`, adding a CLI flag (`--blur`), incorporating the blur operation into the pipeline after cropping, adding input validation, and writing unit tests. Documentation updates are also required.

AI Summary: Implement GIF image decoding and encoding support within the WIOT image optimization toolkit. This involves integrating a suitable GIF library (like giflib or imageio's GIF plugin) to handle GIF input and output, ensuring seamless processing alongside existing formats like JPEG, PNG, WebP, and AVIF.

AI Summary: Implement TGA (TARGA) image format support for the WIOT image optimization toolkit, including both decoding and encoding capabilities. This involves integrating a suitable library (like stb_image/stb_image_write) to handle TGA file I/O and adding the necessary processing steps within WIOT's pipeline.

AI Summary: Implement QOI (Quite OK Image) encoding and decoding capabilities within the WIOT (Web Image Optimizer Toolkit) project. This involves adding support for reading and writing QOI image files, integrating it into the existing image processing pipeline, and potentially updating the CLI and API to handle QOI as an input/output format. The task prioritizes a functional implementation over extensive optimization initially.

AI Summary: Implement support for decoding and encoding Portable Anymap (PNM) images (PBM, PGM, PPM) within the WIOT image optimization toolkit. This involves adding the necessary reading and writing capabilities to handle these formats, integrating them into the existing pipeline, and potentially adding unit tests.

AI Summary: Implement OpenEXR (.exr) image format support in the WIOT image optimization toolkit, including decoding and optionally encoding capabilities. This involves integrating an OpenEXR library and handling floating-point image data within the existing pipeline. The task is optional and of low priority.

AI Summary: Implement Farbfeld image format support (encoding and decoding) for the WIOT image optimization toolkit. This involves adding a new decoder and encoder to handle the simple RGBA format. The task is considered optional and low priority, suitable for a first-time contributor.

AI Summary: Implement optional support for decoding and encoding DSS (Digital Speech Standard) images in the WIOT (Web Image Optimizer Toolkit) project. This involves adding new functionality, potentially behind a feature flag or plugin system, to handle DSS files without requiring external conversion tools. The implementation should prioritize maintainability and integration with the existing architecture.

AI Summary: Implement ICO (Windows icon) file support in the WIOT image optimization tool. This involves adding the capability to decode and encode ICO files, treating them as containers of PNG/BMP frames, and integrating this functionality into the existing image processing pipeline. The goal is to allow users to optimize ICO files directly without manual extraction and conversion of individual frames.

AI Summary: Implement TIFF image support (encoding and decoding) for the WIOT image optimization tool, handling multi-page TIFFs. This involves integrating a suitable TIFF library (like libtiff) to enable native processing of TIFF files within the existing WIOT pipeline, improving workflow by eliminating the need for external TIFF conversion.

AI Summary: Implement BMP image decoding and encoding capabilities within the WIOT (Web Image Optimizer Toolkit) project. This involves adding the necessary code to handle BMP files throughout the image processing pipeline, ensuring compatibility with existing features like resizing and quality optimization.

AI Summary: Implement HDR image support in WIOT, including decoding (e.g., using TinyEXR), internal tone mapping, and encoding of HDR or LDR formats. This requires adding new decoder and encoder capabilities to the existing image processing pipeline.