Arduino connected to servo motors, and nano jetson with built in camera. Camera was used as input video feed into the custom trained yolov7 model for our use case. Conveyer belt was built using 2 toilet rolls and a cloth as a base with paper wrapping onto it. Conveyer belt flap was built using a cardboard and bamboo sticks. Software components Model used: wongkinyiu-YOLOv7 object detection Data used to train the model: 1. Gary Thung Trashnet 2. E-waste: ROBOFLOW ewaste-mx8fq
Both datasets were combined and converted into yolo format before fine-tuning Model was finetuned using YOLOv7 COCO pretrained weights. The object detection model was fine-tuned on a 3090 GPU for 300 epochs with batch size of 32 with image size of 512 Training took total of about 3 to 4 hours
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