training.py

import tensorflow as tf 
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense,Dropout,Activation,Flatten
import pickle

from tensorflow.keras.layers import Conv2D,MaxPooling2D

pickle_in=open(r"C:\Users\Priya\Desktop\Projects-master\PY Ashish\PetImages\X.pickle","rb")
X=pickle.load(pickle_in)

pickle_in=open(r"C:\Users\Priya\Desktop\Projects-master\PY Ashish\PetImages\Y.pickle","rb")
Y=pickle.load(pickle_in)

X=X/255.0

print(X)

model=Sequential()

model.add(Conv2D(256,(3,3),input_shape=X.shape[1:]))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Conv2D(256,(3,3)))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Flatten())
model.add(Dense(64))

model.add(Dense(1))
model.add(Activation("sigmoid"))

model.compile(loss="binary_crossentropy",optimizer='adam',metrics=['accuracy'])

model.fit(X,Y,batch_size=4,epoch=8,validation_split=0.3)

model.save(r"C:\Users\Priya\Desktop\Projects-master\PY Ashish")