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#clone YOLOv5 and 
!git clone https://github.com/ultralytics/yolov5  # clone repo
%cd yolov5
%pip install -qr requirements.txt # install dependencies
%pip install -q roboflow

import torch
import os
from IPython.display import Image, clear_output  # to display images

print(f"Setup complete. Using torch {torch.__version__} ({torch.cuda.get_device_properties(0).name if torch.cuda.is_available() else 'CPU'})")

!python train.py --img 640 --batch 16 --epochs 30 --data /content/data.yaml --weights yolov5s.pt --cache

!python detect.py --weights runs/train/exp/weights/best.pt --img 540 --conf 0.1 --source /content/VOC2005_1/test/images

#display inference on ALL test images

import glob
from IPython.display import Image, display

for imageName in glob.glob('/content/yolov5/runs/detect/exp/*.jpg'): #assuming JPG
    display(Image(filename=imageName))
    print("\n")
	
!python export.py --imgsz 640 640 --weights /content/yolov5/runs/train/exp/weights/best.pt --simplify --data /content/data.yaml --include onnx