I need a program that can automatically identify the walking direction of a horse in yearling parade videos, detect the frame where the horse is most perpendicular to the camera, and extract a standardised clip around that moment. Requirements: - Process MP4 yearling parade videos - Use YOLO to detect the horse and SAM2 (or YOLO-seg) to generate a segmentation mask for each frame - Calculate the mask centroid per frame and determine walking direction based on consistent left-to-right X-movement - Select only the frames where the horse is clearly walking left-to-right - From those frames, detect the moment where the horse is most perpendicular to the camera - Extract a standardised segment around this point (e.g., ±75 frames or ±2 seconds depending on FPS) - Exclude videos that do not contain enough valid frames after the perpendicular moment - Output the clipped video using the original file naming structure Ideal Skills and Experience: - Strong experience with computer vision and video processing (Python, OpenCV, ffmpeg) - Proficiency with object detection and segmentation frameworks (YOLO, SAM2, etc.) - Ability to compute and analyse per-frame motion metrics (centroid tracking, direction inference) - Understanding of pose/angle detection or geometric heuristics for “perpendicular” classification - Experience building efficient pipelines capable of batch-processing large video datasets - Clear attention to detail and ability to implement robust quality-control rules Looking for a freelancer who can deliver a fast, scalable, and reliable solution suitable for processing thousands of videos.