ML · Done
Prototype Chicken Detection Model
Overview
Computer vision system to detect and count chickens in real-time for poultry monitoring. Built using Python, Detectron2, and PyTorch, this prototype employs a RetinaNet model with a ResNet-50 FPN backbone, optimized through dynamic quantization and structured pruning.
Challenge
Developing a high-sensitivity deep learning model for accurate real-time chicken detection in poultry farm environments.
Result
Developed a prototype capable of reliable chicken detection and counting in images and videos, designed for future integration into a real-time monitoring application.
Key Statistics
~150 MB
Model Size
70%
Detection Accuracy
Poultry Farm Monitoring
Target Application
Technologies
Frameworks
Programming
Libraries
Model Architecture
Gallery
Chicken Detection Output
Image with detected chickens and bounding boxes.
Video Detection Frame
Frame from video showing result for chicken detection.