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.
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()