dataloader.py

train_dataset = Dataset(df_train)
test_dataset  = Dataset(df_test)

BATCH_SIZE=32
train_dataloader = Dataloder(train_dataset, batch_size=BATCH_SIZE, shuffle=True)
test_dataloader = Dataloder(test_dataset, batch_size=BATCH_SIZE, shuffle=True)]

#=========================================================  View Output

rows,cols=3,3
fig=plt.figure(figsize=(10,10))
for i in range(1,rows*cols+1):
    index=np.random.randint(1,len(train_dataloader))
    #index=i+20
    fig.add_subplot(rows,cols,i)
    img_path=train_dataloader[index-1][0][0]
    msk_path=train_dataloader[index-1][1][0]
    plt.imshow(np.reshape(img_path,(256,256)),cmap='Greens')
    #plt.imshow(msk_path,alpha=0.5, cmap="gray")

plt.show()