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.