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"""Image operations."""
from copy import deepcopy
from PIL import Image
import numpy as np
def center_crop(im: Image):
width, height = im.size
new_width = width if width < height else height
new_height = height if height < width else width
left = (width - new_width)/2
top = (height - new_height)/2
right = (width + new_width)/2
bottom = (height + new_height)/2
# Crop the center of the image
im = im.crop((left, top, right, bottom))
return im
def pad_to_square(im: Image, color=(0, 0, 0)):
im = deepcopy(im)
width, height = im.size
vert_pad = (max(width, height) - height) // 2
hor_pad = (max(width, height) - width) // 2
if len(im.mode) == 3:
color = (0, 0, 0)
elif len(im.mode) == 1:
color = 0
else:
raise ValueError(f"Image mode not supported. Image has {im.mode} channels.")
return add_margin(im, vert_pad, hor_pad, vert_pad, hor_pad, color=color)
def add_margin(pil_img, top, right, bottom, left, color=(0, 0, 0)):
"""Ref: https://note.nkmk.me/en/python-pillow-add-margin-expand-canvas/"""
width, height = pil_img.size
new_width = width + right + left
new_height = height + top + bottom
result = Image.new(pil_img.mode, (new_width, new_height), color)
result.paste(pil_img, (left, top))
return result
def resize_image(image, new_height, new_width):
# Convert the numpy array image to PIL Image
pil_image = Image.fromarray(image)
# Resize the PIL Image
resized_image = pil_image.resize((new_width, new_height))
# Convert the resized PIL Image back to numpy array
resized_image_np = np.array(resized_image)
return resized_image_np
def pad_to_width(pil_image, new_width, color=(0, 0, 0)):
"""Pad the image to the specified width."""
# Convert the numpy array image to PIL Image
# pil_image = Image.fromarray(image)
# Get the current width and height of the image
width, height = pil_image.size
assert new_width > width, f"New width {new_width} is less than the current width {width}."
# Calculate the padding required
hor_pad = new_width - width
# Add padding to the image
padded_image = add_margin(pil_image, 0, hor_pad, 0, 0, color=color)
# Convert the padded PIL Image back to numpy array
# padded_image_np = np.array(padded_image)
return padded_image
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