copy images and labels during forming dataset. add folder for corrupted labels, small refactor

dataset-visualiser.py

@@ -6,25 +6,47 @@ from dto.imageLabel import ImageLabel
 from preprocessing import read_labels
 from matplotlib import pyplot as plt
 
-from constants import datasets_dir, prefix
-
-
+from constants import datasets_dir, prefix, processed_images_dir, processed_labels_dir
 annotation_classes = AnnotationClass.read_json()
-cur_dataset = os.path.join(datasets_dir, f'{prefix}2024-06-18', 'train')
-images_dir = os.path.join(cur_dataset, 'images')
-labels_dir = os.path.join(cur_dataset, 'labels')
 
-for f in os.listdir(images_dir)[35247:]:
-    image_path = os.path.join(images_dir, f)
-    labels_path = os.path.join(labels_dir, f'{Path(f).stem}.txt')
-    img = ImageLabel(
-        image_path=image_path,
-        image=cv2.imread(image_path),
-        labels_path=labels_path,
-        labels=read_labels(labels_path)
-    )
-    img.visualize(annotation_classes)
-    print(f'visualizing {image_path}')
-    plt.close()
-    key = input('Press any key to continue')
 
+def visualise_dataset():
+    cur_dataset = os.path.join(datasets_dir, f'{prefix}2024-06-18', 'train')
+    images_dir = os.path.join(cur_dataset, 'images')
+    labels_dir = os.path.join(cur_dataset, 'labels')
+
+    for f in os.listdir(images_dir)[35247:]:
+        image_path = os.path.join(images_dir, f)
+        labels_path = os.path.join(labels_dir, f'{Path(f).stem}.txt')
+        img = ImageLabel(
+            image_path=image_path,
+            image=cv2.imread(image_path),
+            labels_path=labels_path,
+            labels=read_labels(labels_path)
+        )
+        img.visualize(annotation_classes)
+        print(f'visualizing {image_path}')
+        plt.close()
+        key = input('Press any key to continue')
+
+
+def visualise_processed_folder():
+
+    def show_image(img):
+        image_path = os.path.join(processed_images_dir, img)
+        labels_path = os.path.join(processed_labels_dir, f'{Path(img).stem}.txt')
+        img = ImageLabel(
+            image_path=image_path,
+            image=cv2.imread(image_path),
+            labels_path=labels_path,
+            labels=read_labels(labels_path)
+        )
+        img.visualize(annotation_classes)
+    images = os.listdir(processed_images_dir)
+    cur = 0
+    show_image(images[cur])
+    pass
+
+
+if __name__ == '__main__':
+    visualise_processed_folder()