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Advanced Object Detection with Tensorflow API [Work In Progress]

My goal is to to predict if horses break down hurdles during a show jumping competition 3 seconds ahead

Jumper classes are held over a course of show jumping obstacles, including verticals, spreads, and double and triple combinations, usually with many turns and changes of direction. The intent is to jump cleanly over a set course within an allotted time. Time faults are assessed for exceeding the time allowance. Jumping faults are incurred for knockdowns and blatant disobedience, such as refusals (when the horse stops before a fence or “runs out”) (see “Modern rules” below). Horses are allowed a limited number of refusals before being disqualified. A refusal may lead to a rider exceeding the time allowed on course. Placings are based on the lowest number of points or “faults” accumulated. A horse and rider who have not accumulated any jumping faults or penalty points are said to have scored a “clear round”. Tied entries usually have a jump-off over a raised and shortened course, and the course is timed; if entries are tied for faults accumulated in the jump-off, the fastest time wins.

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Show Jumping Competition - Detect Horses

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