turbo_inversion / croper.py
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import PIL
import numpy as np
from PIL import Image
class Croper:
def __init__(
self,
input_image: PIL.Image,
target_mask: np.ndarray,
mask_size: int = 256,
mask_expansion: int = 20,
):
self.input_image = input_image
self.target_mask = target_mask
self.mask_size = mask_size
self.mask_expansion = mask_expansion
def corp_mask_image(self):
target_mask = self.target_mask
input_image = self.input_image
mask_expansion = self.mask_expansion
original_width, original_height = input_image.size
mask_indices = np.where(target_mask)
start_y = np.min(mask_indices[0])
end_y = np.max(mask_indices[0])
start_x = np.min(mask_indices[1])
end_x = np.max(mask_indices[1])
mask_height = end_y - start_y
mask_width = end_x - start_x
# choose the max side length
max_side_length = max(mask_height, mask_width)
# expand the mask area
height_diff = (max_side_length - mask_height) // 2
width_diff = (max_side_length - mask_width) // 2
start_y = start_y - mask_expansion - height_diff
if start_y < 0:
start_y = 0
end_y = end_y + mask_expansion + height_diff
if end_y > original_height:
end_y = original_height
start_x = start_x - mask_expansion - width_diff
if start_x < 0:
start_x = 0
end_x = end_x + mask_expansion + width_diff
if end_x > original_width:
end_x = original_width
expanded_height = end_y - start_y
expanded_width = end_x - start_x
expanded_max_side_length = max(expanded_height, expanded_width)
# calculate the crop area
crop_mask = target_mask[start_y:end_y, start_x:end_x]
crop_mask_start_y = (expanded_max_side_length - expanded_height) // 2
crop_mask_end_y = crop_mask_start_y + expanded_height
crop_mask_start_x = (expanded_max_side_length - expanded_width) // 2
crop_mask_end_x = crop_mask_start_x + expanded_width
# create a square mask
square_mask = np.zeros((expanded_max_side_length, expanded_max_side_length), dtype=target_mask.dtype)
square_mask[crop_mask_start_y:crop_mask_end_y, crop_mask_start_x:crop_mask_end_x] = crop_mask
square_mask_image = Image.fromarray((square_mask * 255).astype(np.uint8))
crop_image = input_image.crop((start_x, start_y, end_x, end_y))
square_image = Image.new("RGB", (expanded_max_side_length, expanded_max_side_length))
square_image.paste(crop_image, (crop_mask_start_x, crop_mask_start_y))
self.origin_start_x = start_x
self.origin_start_y = start_y
self.origin_end_x = end_x
self.origin_end_y = end_y
self.square_start_x = crop_mask_start_x
self.square_start_y = crop_mask_start_y
self.square_end_x = crop_mask_end_x
self.square_end_y = crop_mask_end_y
self.square_length = expanded_max_side_length
self.square_mask_image = square_mask_image
self.square_image = square_image
self.corp_mask = crop_mask
mask_size = self.mask_size
self.resized_square_mask_image = square_mask_image.resize((mask_size, mask_size))
self.resized_square_image = square_image.resize((mask_size, mask_size))
return self.resized_square_mask_image
def restore_result(self, generated_image):
square_length = self.square_length
generated_image = generated_image.resize((square_length, square_length))
square_mask_image = self.square_mask_image
cropped_generated_image = generated_image.crop((self.square_start_x, self.square_start_y, self.square_end_x, self.square_end_y))
cropped_square_mask_image = square_mask_image.crop((self.square_start_x, self.square_start_y, self.square_end_x, self.square_end_y))
restored_image = self.input_image.copy()
restored_image.paste(cropped_generated_image, (self.origin_start_x, self.origin_start_y), cropped_square_mask_image)
return restored_image
def restore_result_v2(self, generated_image):
square_length = self.square_length
generated_image = generated_image.resize((square_length, square_length))
cropped_generated_image = generated_image.crop((self.square_start_x, self.square_start_y, self.square_end_x, self.square_end_y))
restored_image = self.input_image.copy()
restored_image.paste(cropped_generated_image, (self.origin_start_x, self.origin_start_y))
return restored_image