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SwishScan
SwishScan: Visualizing Basketball Prowess
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Created on 4th March 2024
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SwishScan
SwishScan: Visualizing Basketball Prowess
The problem SwishScan solves
SwishScan streamlines the process of analyzing basketball shots by automating trajectory prediction. It eliminates manual tracking efforts, enabling coaches, players, and analysts to quickly assess shooting proficiency and make data-driven decisions to improve performance.
Challenges I ran into
While developing SwishScan, a key challenge was ensuring accurate color detection for identifying the basketball in various lighting conditions. Adjusting HSV values in real-time to accommodate different environments required meticulous calibration and testing. Leveraging the cvzone library, I fine-tuned the color detection algorithm, achieving reliable results across diverse video settings.
Technologies used
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