Hello world!

				
					import matplotlib.pyplot as plt

fig=plt.figure(figsize=(16,16))
all_top_classes = []

# Loop through images run them through our classifer
for (i,file) in enumerate(file_names):

    img = image.load_img(mypath+file, target_size=(224, 224))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = preprocess_input(x)
    
    #load image using opencv
    img2 = cv2.imread(mypath+file)
    #imageL = cv2.resize(img2, None, fx=.5, fy=.5, interpolation = cv2.INTER_CUBIC) 
    
    # Get Predictions
    preds = model.predict(x)
    preditions = decode_predictions(preds, top=10)[0]
    all_top_classes.append([x[1] for x in preditions])
    # Plot image
    sub = fig.add_subplot(len(file_names),1, i+1)
    sub.set_title(f'Predicted {str(preditions)}')
    plt.axis('off')
    plt.imshow(cv2.cvtColor(img2, cv2.COLOR_BGR2RGB))

plt.show()