From 0788449be1d75272348ca0bc07042918ce230213 Mon Sep 17 00:00:00 2001 From: Sujit Mandal <49348037+sujitmandal@users.noreply.github.com> Date: Wed, 1 Jul 2020 14:11:30 +0530 Subject: [PATCH] Delete data_procession.py --- Pneumonia Classification/data_procession.py | 263 -------------------- 1 file changed, 263 deletions(-) delete mode 100644 Pneumonia Classification/data_procession.py diff --git a/Pneumonia Classification/data_procession.py b/Pneumonia Classification/data_procession.py deleted file mode 100644 index 50faf98..0000000 --- a/Pneumonia Classification/data_procession.py +++ /dev/null @@ -1,263 +0,0 @@ -#Import required libraries -import os -import cv2 -import numpy as np -from tqdm import tqdm -import tensorflow as tf -from random import shuffle -from tensorflow import keras -import matplotlib.pyplot as plt - -#Github: https://github.com/sujitmandal -#This programe is create by Sujit Mandal -""" -Github: https://github.com/sujitmandal -This programe is create by Sujit Mandal -LinkedIn : https://www.linkedin.com/in/sujit-mandal-91215013a/ -Facebook : https://www.facebook.com/sujit.mandal.33671748 -Twitter : https://twitter.com/mandalsujit37 -""" - -#Read The Dataset -train_pneumonia_dir = ('/media/sujit/2C1EFB771EFB3902/Pneumonia Dataset/train/Pneumonia') -train_normal_dir = ('/media/sujit/2C1EFB771EFB3902/Pneumonia Dataset/train/Normal') -test_pneumonia_dir = ('/media/sujit/2C1EFB771EFB3902/Pneumonia Dataset/test/Pneumonia') -test_normal_dir = ('/media/sujit/2C1EFB771EFB3902/Pneumonia Dataset/test/Normal') - - -image_size = 1000 -#image_size = int(input('Enter The Image Size [32, 64, 128] :')) - -#Label The Images -def label_image(image): - word_label = image.split('.')[-3] - - if word_label == 'Pneumonia': - return [0] - elif word_label == 'Normal': - return [1] - else: - print('Image not found!') - -def train_pneumonia_image(): - train_pneumonia_image = [] - - for image in tqdm(os.listdir(train_pneumonia_dir)): - path = os.path.join(train_pneumonia_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - train_pneumonia_image.append([np.array(image)]) - shuffle(train_pneumonia_image) - - return(train_pneumonia_image) - -def train_pneumonia_label(): - train_pneumonia_label = [] - - for image in tqdm(os.listdir(train_pneumonia_dir)): - label = label_image(image) - path = os.path.join(train_pneumonia_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - train_pneumonia_label.append([np.array(label)]) - shuffle(train_pneumonia_label) - - return(train_pneumonia_label) - -def train_normal_image(): - train_normal_image = [] - - for image in tqdm(os.listdir(train_normal_dir)): - path = os.path.join(train_normal_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - train_normal_image.append([np.array(image)]) - shuffle(train_normal_image) - - return(train_normal_image) - -def train_normal_label(): - train_normal_label = [] - - for image in tqdm(os.listdir(train_normal_dir)): - label = label_image(image) - path = os.path.join(train_normal_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - train_normal_label.append([np.array(label)]) - shuffle(train_normal_label) - - return(train_normal_label) - -def test_pneumonia_image(): - test_pneumonia_image = [] - - for image in tqdm(os.listdir(test_pneumonia_dir)): - path = os.path.join(test_pneumonia_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - test_pneumonia_image.append([np.array(image)]) - shuffle(test_pneumonia_image) - - return(test_pneumonia_image) - - -def test_pneumonia_label(): - test_pneumonia_label = [] - - for image in tqdm(os.listdir(test_pneumonia_dir)): - label = label_image(image) - path = os.path.join(test_pneumonia_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - test_pneumonia_label.append([np.array(label)]) - shuffle(test_pneumonia_label) - - return(test_pneumonia_label) - -def test_normal_image(): - test_normal_image = [] - - for image in tqdm(os.listdir(test_normal_dir)): - path = os.path.join(test_normal_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - test_normal_image.append([np.array(image)]) - shuffle(test_normal_image) - - return(test_normal_image) - -def test_normal_label(): - test_normal_label = [] - - for image in tqdm(os.listdir(test_normal_dir)): - label = label_image(image) - path = os.path.join(test_normal_dir, image) - - image = cv2.imread(path) - image = cv2.resize(image, (image_size, image_size)) - test_normal_label.append([np.array(label)]) - shuffle(test_normal_label) - - return(test_normal_label) - -list_train_pneumonia_image = train_pneumonia_image() -list_pneumonia_label = train_pneumonia_label() -list_train_normal_image = train_normal_image() -list_train_normal_label = train_normal_label() -list_test_pneumonia_image = test_pneumonia_image() -list_test_pneumonia_label = test_pneumonia_label() -list_test_normal_image = test_normal_image() -list_test_normal_label = test_normal_label() - -array_train_pneumonia_image = np.array(list_train_pneumonia_image) -array_train_pneumonia_label = np.array(list_pneumonia_label) -array_train_normal_image = np.array(list_train_normal_image) -array_train_normal_label = np.array(list_train_normal_label) -array_test_pneumonia_image = np.array(list_test_pneumonia_image) -array_test_pneumonia_label = np.array(list_test_pneumonia_label) -array_test_normal_image = np.array(list_test_normal_image) -array_test_normal_label = np.array(list_test_normal_label) - -print(array_train_pneumonia_image.shape) -print(array_train_pneumonia_label.shape) -print(array_train_normal_image.shape) -print(array_train_normal_label.shape) -print(array_test_pneumonia_image.shape) -print(array_test_pneumonia_label.shape) -print(array_test_normal_image.shape) -print(array_test_normal_label.shape) - -train_pneumonia_image = array_train_pneumonia_image[:,0,:,:] -train_pneumonia_label = array_train_pneumonia_label[:,0,:] -train_normal_image = array_train_normal_image[:,0,:,:] -train_normal_label = array_train_normal_label[:,0,:] -test_pneumonia_image = array_test_pneumonia_image[:,0,:,:] -test_pneumonia_label = array_test_pneumonia_label[:,0,:] -test_normal_image = array_test_normal_image[:,0,:,:] -test_normal_label = array_test_normal_label[:,0,:] - -print(train_pneumonia_image.shape) -print(train_pneumonia_label.shape) -print(train_normal_image.shape) -print(train_normal_label.shape) -print(test_pneumonia_image.shape) -print(test_pneumonia_label.shape) -print(test_normal_image.shape) -print(test_normal_label.shape) - -train_pneumonia_image_class = ['Pneumonia', 'Normal'] - -plt.figure(figsize=(10,10)) -for i in range(16): - plt.subplot(4,4,i+1) - plt.xticks([]) - plt.yticks([]) - plt.grid(False) - plt.imshow(train_pneumonia_image[i], cmap=plt.cm.binary) - plt.xlabel(train_pneumonia_image_class[train_pneumonia_label[i][0]]) -plt.show() - -train_normal_image_class = ['Pneumonia', 'Normal'] - -plt.figure(figsize=(10,10)) -for i in range(16): - plt.subplot(4,4,i+1) - plt.xticks([]) - plt.yticks([]) - plt.grid(False) - plt.imshow(train_normal_image[i], cmap=plt.cm.binary) - plt.xlabel(train_normal_image_class[train_normal_label[i][0]]) -plt.show() - -test_pneumonia_image_class = ['Pneumonia', 'Normal'] - -plt.figure(figsize=(10,10)) -for i in range(16): - plt.subplot(4,4,i+1) - plt.xticks([]) - plt.yticks([]) - plt.grid(False) - plt.imshow(test_pneumonia_image[i], cmap=plt.cm.binary) - plt.xlabel(test_pneumonia_image_class[test_pneumonia_label[i][0]]) -plt.show() - -test_normal_image_class = ['Pneumonia', 'Normal'] - -plt.figure(figsize=(10,10)) -for i in range(16): - plt.subplot(4,4,i+1) - plt.xticks([]) - plt.yticks([]) - plt.grid(False) - plt.imshow(test_normal_image[i], cmap=plt.cm.binary) - plt.xlabel(test_normal_image_class[test_normal_label[i][0]]) -plt.show() - - -train_images = np.append(train_pneumonia_image, train_normal_image, axis=0) -train_labels = np.append(train_pneumonia_label, train_normal_label, axis=0) -test_images = np.append(test_pneumonia_image, test_normal_image, axis=0) -test_labels = np.append(test_pneumonia_label, test_normal_label, axis=0) - -print(train_images.shape) -print(train_labels.shape) -print(test_images.shape) -print(test_labels.shape) - -#Save The Array in The Local Disk.... -np.save('Dataset/train_images.npy',train_images) -np.save('Dataset/train_labels.npy',train_labels) -np.save('Dataset/test_images.npy',test_images) -np.save('Dataset/test_labels.npy',test_labels) -print('\ntrain_images.npy is saved on the Current Directory.....') -print('train_labels.npy is saved on the Current Directory.....') -print('test_images.npy is saved on the Current Directory.....') -print('test_labels.npy is saved on the Current Directory.....')