Failure to use adaptiveThreshold: CV_8UC1 in function adaptiveThreshold
Question:
I have used openCV python and encountered an error.
img_blur = cv2.medianBlur(self.cropped_img,5)
img_thresh_Gaussian = cv2.adaptiveThreshold(img_blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
plt.subplot(1,1,1),plt.imshow(img_thresh_Gaussian, cmap = 'gray')
plt.title("Image"), plt.xticks([]), plt.yticks([])
plt.show()
but I received:
cv2.error: /home/phuong/opencv_src/opencv/modules/imgproc/src/thresh.cpp:1280: error: (-215) src.type() == CV_8UC1 in function adaptiveThreshold
Do I have to install something else?
Answers:
you should load your file like this
src.create(rows, cols, CV_8UC1);
src = imread(your-file, CV_8UC1);
and after that
adaptiveThreshold(src, dst, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 75, 10);
The problem is that you are trying to use adaptive thresholding to an image that is not in greyscale. And the function only works with a greyscale images.
So you have to convert your image to a greyscale format as it is described in documentation.
They read the image in a greyscale format with: img = cv2.imread('dave.jpg',0). You can also convert it to greyscale with: img_grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
you can change the code to slightly like this :
img_blur = cv2.medianBlur(self.cropped_img,5).astype('uint8')
img_thresh_Gaussian = cv2.adaptiveThreshold(img_blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
just by adding (‘uint8’) while blurring has resolved my issue.
Try to add cv2.IMREAD_GRAYSCALE in the second parameter of imread
img = cv2.imread(File_path, cv2.IMREAD_GRAYSCALE)
you have to imread your image in grayscale, so use the code below:
image = imread('address', 0)
0 exchange the channel of image to grayscale
Convert the image to grayscale before thresholding:
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img_blur = cv2.medianBlur(img_gray,5)
img_thresh_Gaussian = cv2.adaptiveThreshold(img_blur, 255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
To solve this issue, you need to load grayscale image using 0(zero) as another parameter than the image path.
img = cv2.imread(imagepath, 0)
OR
img = cv2.imread(imagepath, cv2.IMREAD_GRAYSCALE)
I have used openCV python and encountered an error.
img_blur = cv2.medianBlur(self.cropped_img,5)
img_thresh_Gaussian = cv2.adaptiveThreshold(img_blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
plt.subplot(1,1,1),plt.imshow(img_thresh_Gaussian, cmap = 'gray')
plt.title("Image"), plt.xticks([]), plt.yticks([])
plt.show()
but I received:
cv2.error: /home/phuong/opencv_src/opencv/modules/imgproc/src/thresh.cpp:1280: error: (-215) src.type() == CV_8UC1 in function adaptiveThreshold
Do I have to install something else?
you should load your file like this
src.create(rows, cols, CV_8UC1);
src = imread(your-file, CV_8UC1);
and after that
adaptiveThreshold(src, dst, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 75, 10);
The problem is that you are trying to use adaptive thresholding to an image that is not in greyscale. And the function only works with a greyscale images.
So you have to convert your image to a greyscale format as it is described in documentation.
They read the image in a greyscale format with: img = cv2.imread('dave.jpg',0). You can also convert it to greyscale with: img_grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
you can change the code to slightly like this :
img_blur = cv2.medianBlur(self.cropped_img,5).astype('uint8')
img_thresh_Gaussian = cv2.adaptiveThreshold(img_blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
just by adding (‘uint8’) while blurring has resolved my issue.
Try to add cv2.IMREAD_GRAYSCALE in the second parameter of imread
img = cv2.imread(File_path, cv2.IMREAD_GRAYSCALE)
you have to imread your image in grayscale, so use the code below:
image = imread('address', 0)
0 exchange the channel of image to grayscale
Convert the image to grayscale before thresholding:
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img_blur = cv2.medianBlur(img_gray,5)
img_thresh_Gaussian = cv2.adaptiveThreshold(img_blur, 255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
To solve this issue, you need to load grayscale image using 0(zero) as another parameter than the image path.
img = cv2.imread(imagepath, 0)
OR
img = cv2.imread(imagepath, cv2.IMREAD_GRAYSCALE)