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Action Leopard is spatial control and reasoning for action scenes in generative video. The app, its prompting system, and its reference image creation and segmentation tools are built for shots where location matters and continuity can't be approximated. Video models drift. Cars grow grilles facing the wrong direction, and action reverts to predictable scenarios from the models' training, making it hard to force objects and characters to do unique and surprising things while still following the rules of physics. Action Leopard tackles this in two ways. First, you upload a script and a set of ordered location photos that map a real place. An agentic loop plans shots and generates start frames, then a separate judge model checks each frame against the location, the script, and scene invariants (e.g., which character or vehicle is ahead) and rewrites prompts until physics and continuity hold. Second, when the loop hits something it can't fix, it hands the shot to you. Segmentation cuts characters, vehicles, and props out of your location photo as movable stickers over a clean background plate, so you can rearrange things on a canvas, annotate motion paths, and stage the reference frame yourself.

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