Intern - Sclanet
The images collected are pre-processed and augmented to improve the model’s robustness. A custom object detection model is then trained using TensorFlow’s Object Detection API, leveraging transfer learning from a pre-trained model to expedite the training process. The trained model is evaluated using metrics such as mAP (mean Average Precision) to ensure its accuracy and reliability in detecting products on shelves.