identify not white pixels in bmp

[flash77]

Dear deanhystad,

I was a bit confused and tried a lot, because the detection of the right primary color ratio wasn't working properly...
(And, among other things, I tried to use Counter instead of numpy.unique - but I wasn't able to get it working.)

I'm sorry for my slightly confused posting...

What do you think of my new idea to use:

# reducing colors
    image = img.quantize(colors=2, method=None, kmeans=0, palette=None)

to reduce the colors?

My idea is to use it like a filter to get the right primary color ratio.

Testing the code with a "clean" white 10 x 10 pixel bmp-file, which contains 2 colored pixels:
The result is that primColorRatio is 0.98.
filled_ratio is about 0.02.
And the image is considered as filled.

Then I tested the code with a scanned white sheet of paper, which contained only black writing.
The result is that primColorRatio is 0.912429823754084.
filled_ratio is about 0.08757017624591601.
And the image is considered as filled.

Is this a suitable way to perform primaryColorRatio determination?
I'm pretty confident...

If that is the case, then the next step I will take is to examine every xth pixel.

Best regards,

flash77

import numpy as np
from pdf2image import convert_from_path
from PIL import Image
import time


def primary_color_ratio(pdf_name):
    """Return ratio of pixels that are the "background" color."""
    pages = convert_from_path(pdf_name, 300)
    # save pdf to bmp
    bmpImage = pages[0].save("bmpImage.bmp", "BMP")
    # open Image
    img = Image.open(r"bmpImage.bmp")
    # reducing colors
    image = img.quantize(colors=2, method=None, kmeans=0, palette=None)
    # convert to rgb
    image_rgb = image.convert('RGB')
    # I will do it later: examine just every xth pixel
    rgb = np.array(image_rgb).reshape(-1, 3)#[::x]
    #get 24Bit Color
    b24 = rgb[:, 0] * 65536 + rgb[:, 1] * 256 + rgb[:, 2]
    _, counts = np.unique(b24, return_counts=True)
    return max(counts) / max(len(b24), 1)


#"filled" is the content that can be read by humans (for example: writing)
#"userdef_image_filled_ratio_whole_page": the ratio at which an image is considered filled
pdf_name = "t2.pdf"
userdef_image_filled_ratio_whole_page = 0.02
startTime = time.time()
primColorRatio = primary_color_ratio(pdf_name)
print("primColorRatio = " + str(primColorRatio))
filled_ratio = 1 - primColorRatio
endTime = time.time()
print("filled_ratio = " + str(filled_ratio))
print("elapsed time: ", (endTime - startTime))
if filled_ratio >= userdef_image_filled_ratio_whole_page:
    print("The image is filled.")
else:
    print("The image is empty.")