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zxsanny
53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
import os
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from pathlib import Path
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import cv2
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from dto.annotationClass import AnnotationClass
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from dto.imageLabel import ImageLabel
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from preprocessing import read_labels
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from matplotlib import pyplot as plt
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from constants import datasets_dir, prefix, processed_images_dir, processed_labels_dir
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annotation_classes = AnnotationClass.read_json()
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def visualise_dataset():
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cur_dataset = os.path.join(datasets_dir, f'{prefix}2024-06-18', 'train')
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images_dir = os.path.join(cur_dataset, 'images')
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labels_dir = os.path.join(cur_dataset, 'labels')
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for f in os.listdir(images_dir)[35247:]:
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image_path = os.path.join(images_dir, f)
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labels_path = os.path.join(labels_dir, f'{Path(f).stem}.txt')
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img = ImageLabel(
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image_path=image_path,
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image=cv2.imread(image_path),
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labels_path=labels_path,
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labels=read_labels(labels_path)
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)
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img.visualize(annotation_classes)
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print(f'visualizing {image_path}')
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plt.close()
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key = input('Press any key to continue')
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def visualise_processed_folder():
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def show_image(img):
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image_path = os.path.join(processed_images_dir, img)
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labels_path = os.path.join(processed_labels_dir, f'{Path(img).stem}.txt')
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img = ImageLabel(
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image_path=image_path,
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image=cv2.imread(image_path),
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labels_path=labels_path,
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labels=read_labels(labels_path)
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)
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img.visualize(annotation_classes)
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images = os.listdir(processed_images_dir)
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cur = 0
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show_image(images[cur])
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pass
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if __name__ == '__main__':
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visualise_processed_folder()
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