Hello all. I am working on a OpenCV python project where i have to detect and classify objects in images. Note: I am not supposed to make my system learn. There are 3 categories (Cactus Plant, Vehicles and Traffic Signs) There are several pictures and that too with so much variations (i will show them here). So far, after watching so many videos i have been able to detect the objects with almost 70% accuracy (because of huge variations) using "Contours" but i have not been able to classify them (putting labels on each of them , cactus , vehicle). How to classify them? Kindly Help. I have tried to find "Area" using CountArea function, but it doesn't work since they are not placed at the same place each time in an image.
C:\fakepath\47.jpg C:\fakepath\383.jpg C:\fakepath\original.jpg C:\fakepath\original2.jpg
Screenshot of detected objects is below: C:\fakepath\HSV detection.png
