问题
from scipy.misc import imread
from matplotlib import pyplot
import cv2
from cv2 import cv
from SRM import SRM ## Module for Statistical Regional Segmentation
im = imread("lena.png")
im2 = cv2.imread("lena.png")
print type(im), type(im2), im.shape, im2.shape
## Prints <type 'numpy.ndarray'> <type 'numpy.ndarray'> (120, 120, 3) (120, 120, 3)
srm = SRM(im, 256)
segmented = srm.run()
srm2 = SRM(im2, 256)
segmented2 = srm2.run()
pic = segmented/256
pic2 = segmented2/256
pyplot.imshow(pic)
pyplot.imsave("onePic.jpg", pic)
pic = pic.astype('uint8')
cv2.imwrite("onePic2.jpg", pic2)
pyplot.show()
onePic.jpg
gives the correct segmented image but onePic2.jpg
gives a complete black image.
Converting the datatype to uint8
using pic = pic.astype('uint8')
did not help. I still gives a black image!
onePic.jpg using pyplot.imsave()
:
onePic2.jpg using cv2.imwrite()
:
Please help!
回答1:
Before converting pic
to uint8
, you need to multiply it by 255 to get the correct range.
回答2:
Although I agree with @sansuiso, in my case I found a possible edge case where my images were being shifted either one bit up in the scale or one bit down.
Since we're dealing with unsigned ints, a single shift means a possible underflow/overflow, and this can corrupt the whole image.
I found cv2's convertScaleAbs with an alpha value of 255.0 to yield better results.
def write_image(path, img):
# img = img*(2**16-1)
# img = img.astype(np.uint16)
# img = img.astype(np.uint8)
img = cv.convertScaleAbs(img, alpha=(255.0))
cv.imwrite(path, img)
This answer goes into more detail.
来源:https://stackoverflow.com/questions/19239381/pyplot-imsave-saves-image-correctly-but-cv2-imwrite-saved-the-same-image-as