import cv2
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.keras.preprocessing.image import load_img, img_to_array
#load model using tensorflow
model = tf.keras.models.load_model('./models/Object_Detection.h5')
print('model loaded successfully')
path = './test_images/N11.jpg'
image = load_img(path) #PIL object
image = np.array(image,dtype=np.uint8) #8 bit array (0,255)
image1 = load_img(path,target_size=(224,224))
image_arr_224 = img_to_array(image1)/255.0 #convert into array and get the normalized output
#print size of original image
h,w,d = image.shape
print('height:',h)
print('width:',w)
plt.imshow(image)
plt.show()
That is the code am using on windows 10 with an 8gb ram and 1tb storage. Am running that code in jupyter notebook via a tensorflow virtual environment created via anaconda cmd. But whenever i try to run the plt.imshow() and plt.show() function to display the image, the kernel dies out and restarts automatically. Have tried to tried all the solutions with almost similar problem but still it didn’t work.