cv.imshow throws (-215:Assertion failed) src_depth != CV_16F && src_depth != CV_32S in function 'convertToShow'
Question:
In this code i am trying to integral image and every time i run this code
a window flash and desapear , then i get this error in terminal
import cv2
import numpy as np
image = cv2.imread("nancy.jpg")
(rows,cols,dims) = image.shape
sum = np.zeros((rows,cols), np.uint8)
imageIntegral = cv2.integral(image, sum, -1)
cv2.imshow("imageIntegral", imageIntegral)
cv2.waitKey()
Error:
cv2.imshow("imageIntegral",imageIntegral)cv2.error: OpenCV(4.1.0) C:/projects/opencv-python/opencv/modules/highgui/src/precomp.hpp:131:
error: (-215:Assertion failed) src_depth != CV_16F && src_depth !=
CV_32S in function ‘convertToShow’
Answers:
Help on cv2.integral:
>>> import cv2
>>> print(cv2.__version__)
4.0.1-dev
>>> help(cv2.integral)
Help on built-in function integral:
integral(...)
integral(src[, sum[, sdepth]]) -> sum
. @overload
A simple demo:
import numpy as np
import cv2
img = np.uint8(np.random.random((2,2,3))*255)
dst = cv2.integral(img)
>>> print(img.shape, img.dtype)
(2, 2, 3) uint8
>>> print(dst.shape, dst.dtype)
(3, 3, 3) int32
And you shouldn’t use imshow directly on the dst image because it’s not np.uint8. Normalize it to np.uint8 (range 0 to 255) or np.float32 (range 0.0 to 1.0). You can find the reason at this link: How to use `cv2.imshow` correctly for the float image returned by `cv2.distanceTransform`?
Check whether your image is uint8 or not
image = image.astype(np.uint8)
cv.imshow requires the given image to have dtype from the set of np.uint8, np.uint16, np.float32, np.float64. It does not accept other types.
Your integral image has type np.int32. The error message explicitly rejected your data because it was np.int32 (or half-float, CV_16F, but that’s not the case here).
So, you need to convert it to a dtype that is acceptable to imshow. Before converting with .astype(...), you must make sure that your value range is mapped into the range of 8-bit integers (0 to 255), or floats (imshow expects 0.0 to 1.0). Normalize your data using the maximum, like this:
imageIntegral = cv.integral(src=image)
# division results in values ranging from 0.0 to 1.0
# type is floating point array (float64)
presentable = imageIntegral / imageIntegral.max()
cv.imshow("imageIntegral", presentable)
cv.waitKey()
cv.destroyWindow("imageIntegral")
input, from OpenCV documentation:
presentable:
You obviously don’t see much in an integral image because by its nature it’s mostly a gradient. That is what happens when one integrates a series of values chosen from a range. That is also why imageIntegral.astype(np.uint8) results in noise:
In this code i am trying to integral image and every time i run this code
a window flash and desapear , then i get this error in terminal
import cv2
import numpy as np
image = cv2.imread("nancy.jpg")
(rows,cols,dims) = image.shape
sum = np.zeros((rows,cols), np.uint8)
imageIntegral = cv2.integral(image, sum, -1)
cv2.imshow("imageIntegral", imageIntegral)
cv2.waitKey()
Error:
cv2.imshow("imageIntegral",imageIntegral)cv2.error: OpenCV(4.1.0) C:/projects/opencv-python/opencv/modules/highgui/src/precomp.hpp:131:
error: (-215:Assertion failed) src_depth != CV_16F && src_depth !=
CV_32S in function ‘convertToShow’
Help on cv2.integral:
>>> import cv2
>>> print(cv2.__version__)
4.0.1-dev
>>> help(cv2.integral)
Help on built-in function integral:
integral(...)
integral(src[, sum[, sdepth]]) -> sum
. @overload
A simple demo:
import numpy as np
import cv2
img = np.uint8(np.random.random((2,2,3))*255)
dst = cv2.integral(img)
>>> print(img.shape, img.dtype)
(2, 2, 3) uint8
>>> print(dst.shape, dst.dtype)
(3, 3, 3) int32
And you shouldn’t use imshow directly on the dst image because it’s not np.uint8. Normalize it to np.uint8 (range 0 to 255) or np.float32 (range 0.0 to 1.0). You can find the reason at this link: How to use `cv2.imshow` correctly for the float image returned by `cv2.distanceTransform`?
Check whether your image is uint8 or not
image = image.astype(np.uint8)
cv.imshow requires the given image to have dtype from the set of np.uint8, np.uint16, np.float32, np.float64. It does not accept other types.
Your integral image has type np.int32. The error message explicitly rejected your data because it was np.int32 (or half-float, CV_16F, but that’s not the case here).
So, you need to convert it to a dtype that is acceptable to imshow. Before converting with .astype(...), you must make sure that your value range is mapped into the range of 8-bit integers (0 to 255), or floats (imshow expects 0.0 to 1.0). Normalize your data using the maximum, like this:
imageIntegral = cv.integral(src=image)
# division results in values ranging from 0.0 to 1.0
# type is floating point array (float64)
presentable = imageIntegral / imageIntegral.max()
cv.imshow("imageIntegral", presentable)
cv.waitKey()
cv.destroyWindow("imageIntegral")
input, from OpenCV documentation:
presentable:
You obviously don’t see much in an integral image because by its nature it’s mostly a gradient. That is what happens when one integrates a series of values chosen from a range. That is also why imageIntegral.astype(np.uint8) results in noise: