Image classification with CNN Python I'm working on image classification using CNN, my dataset contains more than 50 classes (50 folders) which represent the types of car parts, and in each folder we have vehicle brands, each vehicle folder contains the images of the part taken in different sides: front, back, left , right, top, bottom. For example: a folder 'door' wil contain different brand of cars, in each car we will have images of the door tooken by different sides.
I have to create a model to recognize the type of the car part and also the side that the picture was taken.
Please, can anyone suggest how can I use all these folders for my training dataset and how to recognize those two things ( type and side).
You can try and use the tf.keras.preprocessing.image.ImageDataGenerator's flow-from_directory() method. Here are a few links for reference:

tf.data: Build TensorFlow input pipelines

Retraining an Image Classifier

Notebook on Image Captioning