FrameDetect is a computer vision platform that extracts and stitches drone video frames for precision agriculture applications. The system uses advanced machine learning algorithms to process video data and create panoramic images with object detection capabilities.
Key Features & Achievements:
- Developing a computer vision pipeline using Python, OpenCV, NumPy to extract and stitch drone video frames for precision agriculture with modular architecture, automated preprocessing, and scalable deployment workflows.
- Reduced redundant frames by 45% and improved stitching speed by 35% through algorithmic optimization.
- Implemented end-to-end data ingestion and preprocessing pipelines, improving model training speed and data quality for ML workflows.
- Built a web platform with ML object detection capabilities, allowing users to upload videos and receive stitched panoramas with detected objects.
Technologies Used: Python, OpenCV, NumPy, Machine Learning, Computer Vision, Web Development