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