![GitHub - ppogg/YOLOv5-Lite: 🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 930+kb (int8) and 1.7M (fp16). It can reach 10+ FPS on the GitHub - ppogg/YOLOv5-Lite: 🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 930+kb (int8) and 1.7M (fp16). It can reach 10+ FPS on the](https://user-images.githubusercontent.com/82716366/167448925-a431d3a4-ad5d-491d-be95-c90701122a54.png)
GitHub - ppogg/YOLOv5-Lite: 🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 930+kb (int8) and 1.7M (fp16). It can reach 10+ FPS on the
![Large Difference in the YOLOv5 mAP value(Accuracy Performance on Raspberry Pi and Server - FOSS United Large Difference in the YOLOv5 mAP value(Accuracy Performance on Raspberry Pi and Server - FOSS United](https://forum.fossunited.org/uploads/default/optimized/1X/96ab0b555ef8ee2b46ebdcccffa6249bda212451_2_690x345.jpeg)
Large Difference in the YOLOv5 mAP value(Accuracy Performance on Raspberry Pi and Server - FOSS United
![raspberry pi 4 yolov5 custom object detection | How to Train YOLO v5 on a Custom Dataset | yolov5 - YouTube raspberry pi 4 yolov5 custom object detection | How to Train YOLO v5 on a Custom Dataset | yolov5 - YouTube](https://i.ytimg.com/vi/fBHvyiXE0RY/hqdefault.jpg)