Yolo_to_production

Yolov5-prod.py

import os, sys, random
from glob import glob
import matplotlib.pyplot as plt
%matplotlib inline
!pip install -qr '/content/drive/My Drive/Machine Learning Projects/YOLO/SOURCE/requirements.txt'  # install dependencies

## Add the path where you have stored the neccessary supporting files to run detect.py ##
## Replace this with your path.##
sys.path.insert(0, '/content/drive/My Drive/Machine Learning Projects/YOLO/SOURCE/') 
print(sys.path)
cwd = os.getcwd()
print(cwd)

## Single Image prediction
## Beware the contents in the output folder will be deleted for every prediction
output = !python '/content/drive/My Drive/Machine Learning Projects/YOLO/SOURCE/detect.py' 
          --source '/content/BloodImage_00026.jpg' 
          --weights '/content/drive/My Drive/Machine Learning Projects/YOLO/SOURCE/best_BCCM.pt' 
           --output '/content/OUTPUTS/' --device 'cpu'
print(output)
img = plt.imread('/content/OUTPUTS/BloodImage_00026.jpg')
plt.imshow(img)

## Folder Prediction
output = !python '/content/drive/My Drive/Machine Learning Projects/YOLO/SOURCE/detect.py' 
          --source '/content/inputs/' 
          --weights '/content/drive/My Drive/Machine Learning Projects/YOLO/SOURCE/best_BCCM.pt' 
          --output '/content/OUTPUTS/' --device 'cpu'
          
print(output)