Image Processing For Deep learning-FunctionedWay

Before Using these functions you have to make sure your directory pattern look like below:

Function Available

unzipping_file
joining_directory_to_each_other_binary_class
training_filename_show
train_validation_size
plotting_image
resize_labeled_images
resize_labeled_images_augmentation
training_with_loading
load_fit_again_saved_model
evaluate_the_model_performance
images_in_conv_layer
upload_image_to_test
test_image
clean_up

1. We will join the directory and thus it will save us huge amount of time.

from Updated import imagePyTen


import os
import zipfile
import matplotlib.image as mpimg
import matplotlib.pyplot as plt

from tensorflow.keras.preprocessing.image import ImageDataGenerator
import random
from tensorflow.keras.preprocessing.image import img_to_array, load_img
from google.colab import files
import matplotlib.pyplot as plt
from keras.preprocessing import image

2. Use as your need.

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