Follow a step-by-step processing workflow in Siril for astrophotography data collected with a Seastar S50, specifically targeting the M8 Lagoon Nebula. This detailed guide starts by setting the home directory and utilizing the Seestar pre-processing script to stack 91 FIT files. Key initial steps include removing green noise and employing the Graxpert AI Python script for effective background extraction. After plate solving the M8 target and performing spectrophotometric color calibration (using the one-shot color Seastar S50 sensor setting), the tutorial demonstrates how to use StarNet for star removal. The resulting starless image is then refined with multiple applications of denoising via Cosmic Clarity scripts. Learn how to properly stretch the image using the Generalized Hyperbolic Stretch and Linear Stretch to adjust the black point without unwanted clipping. The final stages involve star recomposition, careful balancing of the star mask and starless image, and applying a final sharpen and denoise before saving the finished image as a JPEG, TIFF, and FIT file. The video offers one user's specific method, noting that external tools like Graxpert and StarNet++ must be installed for this process..