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from PIL import Image
import cv2
import numpy as np
def resize_if_needed(image):
width, height = image.size
if width < 50 or height < 50:
scale = max(70 / width, 70 / height)
elif width > 16000 or height > 16000:
scale = min(16000 / width, 16000 / height)
else:
return image
return image.resize((int(width * scale), int(height * scale)), Image.LANCZOS)
def center_on_white_background(image):
width, height = image.size
if width < 150 and height < 50:
background = Image.new('RGB', (150, 150), (255, 255, 255))
x, y = (150 - width) // 2, (150 - height) // 2
background.paste(image, (x, y))
return background
return image
def all_cropped_images_to_one_image(cropped_images, separator_image_path):
separator_image = Image.open(separator_image_path)
separator_height = separator_image.height
total_height = sum(img.height for img in cropped_images) + (len(cropped_images) - 1) * separator_height
print("Total Height:", total_height)
max_width = max(max(img.width for img in cropped_images), separator_image.width)
print("Max Width:", max_width)
combined_image = Image.new('RGB', (max_width, total_height))
y = 0
print(cropped_images, "before combine")
for i, img in enumerate(cropped_images):
combined_image.paste(img, (0, y))
y += img.height
if i < len(cropped_images) - 1:
combined_image.paste(separator_image, (0, y))
y += separator_height
combined_image.save("combinedImage.png")
return combined_image
def preprocess_image(image):
gray = cv2.cvtColor(np.array(image), cv2.COLOR_BGR2GRAY)
_, binary = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
return Image.fromarray(binary) |