| 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=(336, 336)): |
| |
| 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=336 |
| 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((336,336)) |
| logging.info('Resized Image') |
| |
| final_image = final_image.convert('L') if final_image.mode != 'L' else final_image |
| return final_image |
