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pythonimagejupyter-notebooktrim

Trim image thigh Using python with jupyter notebook

Hey everyone I try to trim an image thigh, I tried many functions but no one gives the good results that I need.

input: png image like this enter image description here

output: png image trimmed

enter image description here

I have many images like these and I want to trim thight I can.

code attempt:

    from PIL import Image, ImageChops
import numpy as np

image=Image.open('C:\\11031\\SimpleTest\\1.png')
image.load()
image = image.crop((219, 0, 860, 1365))
image_data = np.asarray(image)
image_data_bw = image_data.max(axis=2)
non_empty_columns = np.where(image_data_bw.max(axis=0)>0)[0]
non_empty_rows = np.where(image_data_bw.max(axis=1)>0)[0]
cropBox = (min(non_empty_rows), max(non_empty_rows), min(non_empty_columns), max(non_empty_columns))

image_data_new = image_data[cropBox[0]:cropBox[1]+1, cropBox[2]:cropBox[3]+1 , :]

new_image = Image.fromarray(image_data_new)
new_image.save('L_2d_cropped.png')

Thank you for any help!

Solution

  • The background is white, and the code is implemented as if the background is black.
    As simple solution is inverting the polarity at the beginning:

    image_data = np.asarray(image)
image_data_inv = 255 - image_data  # Invert polarity (the background is going to be black instead of white).
image_data_bw = image_data_inv.max(axis=2)

    After polarity inversion, the background is going to be black, and the "object" is going to be brighter than the background.

    Code sample:

    from PIL import Image, ImageChops
import numpy as np

image = Image.open('1.png')
image.load()
image = image.crop((0, 219, 1365, 860)) #image = image.crop((219, 0, 860, 1365))
image_data = np.asarray(image)
image_data_inv = 255 - image_data  # Invert polarity (the background is going to be black instead of white).
image_data_bw = image_data_inv.max(axis=2)

non_empty_columns = np.where(image_data_bw.max(axis=0)>0)[0]
non_empty_rows = np.where(image_data_bw.max(axis=1)>0)[0]
cropBox = (min(non_empty_rows), max(non_empty_rows), min(non_empty_columns), max(non_empty_columns))

image_data_new = image_data[cropBox[0]:cropBox[1]+1, cropBox[2]:cropBox[3]+1 , :]

new_image = Image.fromarray(image_data_new)
new_image.save('L_2d_cropped.png')

    Result:
    enter image description here

    You are saying that you have many images like these...
    The above solution is going to work only for images with white background.