I am working on pre-trained vgg16 model, for that I need to have input size of image file to be (224,224,3).
The code I am working on is:
from tensorflow.keras.preprocessing import image import cv2 import matplotlib.pyplot as plt img = image.load_img('abc.jpg',target_size=(224,224)) img = image.img_to_array(img) print(img.shape) ## output : (224,224,3) img_grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #plt.imshow(img_grey) th3 = cv2.adaptiveThreshold(img_grey,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2) plt.figure(figsize=(20,10)) plt.imshow(th3)
error Traceback (most recent call last) <ipython-input-88-2a8a27b965ed> in <module> 17 #plt.imshow(img_grey) 18 ---> 19 th3 = cv2.adaptiveThreshold(img_grey,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2) 20 plt.figure(figsize=(20,10)) 21 plt.imshow(th3) error: OpenCV(4.1.0) /io/opencv/modules/imgproc/src/thresh.cpp:1627: error: (-215:Assertion failed) src.type() == CV_8UC1 in function 'adaptiveThreshold'
Help me in resolving the issue.
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Answer
The error says the solution: src.type() == CV_8UC1
meaning you need to set your image type to the uint8
source
So if you redefine your img
variable:
img = image.img_to_array(img, dtype='uint8')
Problem will be solved but I have a question.
Why do you define the below statement?
img_grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
How do you know load_img
loads the image in BGR
fashion?
We know opencv loads the image cv2.imread
in BGR
fashion.
The statement is wrong, since load_img
loads the image in RGB
format source
Therefore the correct statement will be:
img_grey = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
or you can do:
img = image.load_img('15f8U.png', grayscale=True, target_size=(224, 224))
Correct Code:
from keras.preprocessing import image import cv2 import matplotlib.pyplot as plt img = image.load_img('15f8U.png', grayscale=True, target_size=(224, 224)) img = image.img_to_array(img, dtype='uint8') print(img.shape) ## output : (224,224,3) #plt.imshow(img_grey) th3 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2) plt.figure(figsize=(20,10)) plt.imshow(th3, cmap="gray") plt.show()