I have an image-based face dataset of my own and I’d like a clear, self-contained example that shows how to run face recognition with InsightFace (https://github.com/deepinsight/insightface). The goal is to move from raw images to identification results, demonstrating the typical workflow in code and explaining each step. What I need • A Python script or notebook that loads my image folders, detects faces, extracts embeddings and performs recognition/verification using InsightFace’s recommended pre-trained model (e.g., ArcFace). • A short README walking through environment setup, command-line arguments, and expected folder structure for my images. • Comments in the code that highlight key InsightFace calls so I can adapt them later. Acceptance If I can point the script at my dataset or upload image manually as dataset, run it on a fresh machine following the README, and receive a printed match score or ID for each query image, the job is done.