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volleyball machine learning model versus anime same workflow using roboflow rapid + SAM3, details in QT

AA

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28,430 次观看 • 7 个月前 •via X (Twitter)

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i trained this computer vision model just by asking for "tennis players", using roboflow rapid and SAM3 the model picks out Alcaraz and Sinner, while correctly avoiding the ball boys and fans then I exported the model to python and wrote a script to filter the data, track movement history, and annotate the final video this was a quick experiment but I could expand the project to track player speeds, distance covered, shot count, etc. could use this for a sports analytics app that tracks live matches and calculates custom metrics

i trained this computer vision model just by asking for "tennis players", using roboflow rapid and SAM3 the model picks out Alcaraz and Sinner, while correctly avoiding the ball boys and fans then I exported the model to python and wrote a script to filter the data, track movement history, and annotate the final video this was a quick experiment but I could expand the project to track player speeds, distance covered, shot count, etc. could use this for a sports analytics app that tracks live matches and calculates custom metrics

AA

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I can't stop playing with Rapid Roboflow. The process is so smooth that you can just: - Go to the rapid roboflow platform - Drop a few images or a short video - Type a prompt like “yellow cap” or “person wearing red hat” - Instantly get a working detection model No training, no GPUs, no cloud setup. Plug it straight into your app. It’s also baked into Roboflow Workflows, so you can instantly build automations like “count vials crossing this line” in minutes. Computer vision just went from weeks in seconds.

I can't stop playing with Rapid Roboflow. The process is so smooth that you can just: - Go to the rapid roboflow platform - Drop a few images or a short video - Type a prompt like “yellow cap” or “person wearing red hat” - Instantly get a working detection model No training, no GPUs, no cloud setup. Plug it straight into your app. It’s also baked into Roboflow Workflows, so you can instantly build automations like “count vials crossing this line” in minutes. Computer vision just went from weeks in seconds.

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176,108 次观看 • 9 个月前

typing "player with a red shirt" was all it took to train this computer vision model just a few minutes to train the model, export to python, and create this video i'll keep testing roboflow rapid and will report back with the results in the meantime, enjoy the magic of Zlatan

typing "player with a red shirt" was all it took to train this computer vision model just a few minutes to train the model, export to python, and create this video i'll keep testing roboflow rapid and will report back with the results in the meantime, enjoy the magic of Zlatan

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Opus 5 created this Architectural model after looking at 34 images in about 1 hour using the official Blender MCP. More details below.

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i made four sport app prototypes this week, using roboflow rapid + SAM3 + python these ideas could be taken further to make $$$ example: SportRadar is a company that sells analytics to sports leagues and betting firms, with a market cap of $6 billion (!!) a few ideas - for coaches: automated analysis of trainings, tracking stats by player, scouting to prepare for future opponents - for players: compare your form against pros to improve your technique - for amateur leagues: turn hour-long full match footage into automated video reel highlights - for broadcasters: better visuals and stats during live events - for betting / prediction markets: real-time analysis of player performance to predict results

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220,528 次观看 • 9 个月前

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Great prompt, but fine details won't survive the grid. Nano Banana Pro generates each in ~1k resolution. Product text gets lost. This workflow fixes that: → Automatically extracts all 9 grid image → You select your favorite → Upscales to 4K using your input as reference

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