kevakba

PATH = "C:/Users/ADMIN/Desktop/Project/1/train/Sc/Sc_1.bmp"
image = mpimg.imread(PATH) 
plt.show()
plt.imshow(image)
plt.savefig('scratch.png')

kevakba

PATH = "C:/Users/ADMIN/Desktop/Project/1/train/RS/RS_1.bmp"
image = mpimg.imread(PATH) 
plt.show()
plt.imshow(image)
plt.savefig('rolled_in_scale.png')

kevakba

PATH = "C:/Users/ADMIN/Desktop/Project/1/train/Ps/PS_1.bmp"
image = mpimg.imread(PATH) 
plt.show()
plt.imshow(image)
plt.savefig('pitted_surface.png')

kevakba

PATH = "C:/Users/ADMIN/Desktop/Project/1/train/Pa/Pa_1.bmp"
image = mpimg.imread(PATH) 
plt.show()
plt.imshow(image)
plt.savefig('patch.png')

kevakba

PATH = "C:/Users/ADMIN/Desktop/Project/1/train/In/In_1.bmp"
image = mpimg.imread(PATH) 
plt.show()
plt.imshow(image)
plt.savefig('inclusion.png')

kevakba

PATH = "C:/Users/ADMIN/Desktop/Project/1/train/Cr/Cr_1.bmp"
image = mpimg.imread(PATH) 
plt.show()
plt.imshow(image)
plt.savefig('Crazing.png')

kevakba

plt.plot(epochs_range, loss, label='Training Loss')
plt.plot(epochs_range, val_loss, label='Validation Loss')
plt.legend(loc='upper right')
plt.title('Training and Validation Loss')
plt.show()

kevakba

plt.plot(epochs_range, loss, label='Training Loss')
plt.plot(epochs_range, val_loss, label='Validation Loss')
plt.legend(loc='upper right')
plt.title('Training and Validation Loss')
plt.show()

kevakba

acc = history.history['accuracy']
val_acc = history.history['val_accuracy']

loss = history.history['loss']
val_loss = history.history['val_loss']

epochs_range = range(epochs)

plt.plot(epochs_range, acc, label='Training Accuracy')
plt.plot(epochs_range, val_acc, label='Validation Accuracy')

kevakba

Epoch 1/20
48/48 [==============================] - 15s 320ms/step - loss: 1.9151 - accuracy: 0.2396 - val_loss: 1.6345 - val_accuracy: 0.3139
Epoch 2/20
48/48 [==============================] - 15s 314ms/step - loss: 1.4954 - accuracy: 0.3917 - val_loss: 1.3522 - val_accuracy: 0.4722
Epoch 3/20
48/48 [==============================] - 16s 330ms/step - loss: 1.1761 - accuracy: 0.5528 - val_loss: 1.1349 - val_accuracy: 0.5389
Epoch 4/20
48/48 [==============================] - 16s 339ms/step - loss: 0.8542 - accuracy: 0.6958 - val_loss: 0.6563 - val_accuracy: 0.7194
Epoch 5/20
48/48 [==============================] - 16s 340ms/step - loss: 0.6892 - accuracy: 0.7417 - val_loss: 0.7053 - val_accuracy: 0.7472