Sports Coaching App

The solution leveraged a PyTorch-based cloud-deployed AI engine for in-depth analysis of 133 body joints, facilitating performance feedback, player tracking, and key modules for Object Detection, Object Tracking, and Pose Estimation, powered by Python, PyTorch, MMCV, Time Series Analysis, Kubeflow, Google Cloud Platform (GCP), Flutter, and Firebase.

The story

Our client, a key player in the sports broadcast industry in India, was responsible for managing cricket broadcasts, one of the nation’s most beloved sports. He recognized the immense potential of artificial intelligence (AI) and was determined to harness it to create a groundbreaking sports coaching platform. His vision was to pioneer a transformative approach to sports training.

The challenge

The challenge at hand was to develop an AI-based coaching platform for cricket, a sport known for its complexity and nuance. The client aimed to leverage AI to analyze and improve players’ performance, addressing specific areas of improvement based on recorded data. Additionally, there was a need to track and analyze individual players within a team during gameplay.

The solution

To tackle this challenge, the client assembled a skilled team comprising Data Scientists, Mobile Developers, and Quality Assurance Engineers. They employed a sophisticated tech stack that included PyTorch, OpenCV, and a machine learning pipeline hosted on Google Cloud Platform (GCP).

Firstly, an AI-based model was crafted using PyTorch and deployed on the cloud, capable of extracting 133 vital body joints from the subject player, facilitating in-depth movement analysis. Secondly, the model was geared towards scrutinizing recorded performances of players, delivering precise feedback to pinpoint areas necessitating improvement, thereby enhancing overall player skills.

Thirdly, the system exhibited advanced player tracking capabilities, enabling the extraction and tracking of the subject player amidst an entire team, thereby enabling individualized analysis within a team context. Lastly, the platform incorporated indispensable modules for Object Detection (including person and ball detection), Object Tracking, and Pose Estimation, collectively crafting a holistic and comprehensive sports coaching experience. The technology stack included Python, PyTorch, MMCV, Time Series Analysis, Kubeflow, Google Cloud Platform (GCP), Flutter, and Firebase, forming the backbone of this groundbreaking sports coaching solution.

The outcome

The development of an AI-based sports coaching system marked a significant milestone. The client successfully harnessed the power of AI, image processing, and computer vision to provide personalized coaching feedback to cricket players. The system’s ability to track and analyze individual players within a team offered a unique edge in sports training.

The app not only revolutionized sports coaching in cricket but also showcased the potential of AI-driven solutions in the realm of sports performance analysis. It stands as a testament to the client’s vision and the expertise of the interdisciplinary team that made this innovative platform a reality.

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