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import numpy as np
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from PIL import Image, ImageOps
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import logging
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class Image_Processor:
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def __init__(self):
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pass
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def is_image_white_by_percentage(self,image_path, white_threshold):
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image = image_path.convert('RGB')
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image_np = np.array(image)
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white_pixel = np.array([255, 255, 255])
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white_pixels_count = np.sum(np.all(image_np == white_pixel, axis=-1))
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total_pixels = image_np.shape[0] * image_np.shape[1]
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white_pixel_percentage = (white_pixels_count / total_pixels) * 100
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return white_pixel_percentage > white_threshold
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def padding_white(self,image, output_size=(512, 512)):
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if image.mode != 'RGB':
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image = image.convert('RGB')
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new_image = ImageOps.pad(image, output_size, method=Image.Resampling.LANCZOS, color=(255, 255, 255))
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return new_image
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def resize_image_with_aspect_ratio(self,img):
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target_size=512
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width, height = img.size
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original_aspect_ratio = width / height
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if width > height:
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new_width = target_size
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new_height = int(target_size / original_aspect_ratio)
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else:
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new_height = target_size
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new_width = int(target_size * original_aspect_ratio)
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resized_img = img.resize((new_width, new_height))
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return resized_img
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def get_processed_img(self,image):
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white_thresh = self.is_image_white_by_percentage(image,50)
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if white_thresh == True:
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resized_image = self.resize_image_with_aspect_ratio(image)
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final_image = self.padding_white(resized_image)
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logging.info('Resized and Padded Image')
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else:
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final_image = image.resize((512,512))
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logging.info('Resized Image')
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final_image = final_image.convert('L') if final_image.mode != 'L' else final_image
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return final_image |
