I want to reduce the pixel value by 100 for all pixels (all r,g,b) then if update the pixel values to 255 (all r,g,b) where the r=g=b and r > 127
I have tried using CV2 and numpy it works fine, however i am asked to do it using pure PIL Image only.
The code in CV2/numpy is
def getCorrectedImage(im):
print type(im), im.shape
multiplier = np.ones(im.shape, dtype="uint8") * 100
outImage = cv2.subtract(im, multiplier)
height, width, channel = outImage.shape
for x in range(0, height):
for y in range(0, width):
b, g, r = outImage[x, y]
if b > 128 and g > 128 and r > 128:
outImage[x, y] = (255, 255, 255)
return outImage
I want similar code using pure PIL Image, I am not allowed to import CV2 or numpy
Something like that ?
def correct(pImg):
vImg = pImg
width, height = vImg.size
for x in range(width):
for y in range(height):
pixel = (pix - 100 for pix in vImg.getpixel((x, y)))
if (pixel[0] > 127 && pixel.count(pixel[0]) == 3):
pixel = (255, 255, 255)
vImg.putpixel((x,y),pixel)
return vImg
@IQbrod 's answer (after rectification) may work for the immediate problem, but is quite inefficient in the long run.
def getCorrectedImage(img):
data = list(img.getdata())
new_data = [(255, 255, 255) if x[0]== x[1] and x[1] == x[2] and x[0] > 127 else (x[0]-100, x[1]-100, x[2]-100) for x in data]
img.putdata(new_data)
return img
The above code, takes in an image object (created via Image.open
) and then obtains it's pixel map using img.getdata()
and stores it in a variable ( data
) of type list. Then uses list comprehension for modifying pixel values, guided by a condition. And in the end returns the modified image object.
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