add structure how it should work

in preprocessing.py

datasets/zombobase-current/labels/Himars_vs_Tulpan_000091.txt

@@ -0,0 +1,3 @@
+3 0.41877 0.64332 0.06107 0.07926
+7 0.40442 0.78827 0.06779 0.05212
+7 0.19860 0.90662 0.05314 0.05429

preprocessing.py

@@ -0,0 +1,72 @@
+import os.path
+import time
+
+import cv2
+import albumentations as alb
+from os import listdir
+from os.path import isfile, join
+from pathlib import Path
+
+labels_dir = 'labels'
+images_dir = 'images'
+current_dataset_dir = os.path.join('datasets', 'zombobase-current')
+
+class ImageAnnotation:
+
+    def read_annotations(self) -> [[]]:
+        with open(self.annotation_path, 'r') as f:
+            rows = f.readlines()
+            arr = []
+            for row in rows:
+                str_coordinates = row.split(' ')
+                class_num = str_coordinates.pop(0)
+                coordinates = [float(n) for n in str_coordinates]
+                coordinates.append(class_num)
+                arr.append(coordinates)
+            return arr
+
+    def __init__(self, image_path):
+        self.image_path = image_path
+        self.image_name = Path(image_path).stem
+        self.dataset_image_path = os.path.join(current_dataset_dir, images_dir, self.image_name, os.path.basename(image_path))
+        self.image = cv2.imread(image_path)
+
+        self.annotation_path = os.path.join(labels_dir, self.image_name, '.txt')
+        self.dataset_annotation_path = os.path.join(current_dataset_dir, labels_dir, self.image_name, '.txt')
+        self.annotations = self.read_annotations()
+
+def image_processing(img_ann: ImageAnnotation) -> [ImageAnnotation]:
+    # return structure example:
+    # utilize transform albumentations here
+    return [ImageAnnotation(f'{img_ann.image_name}1', image1, bboxes1 ),
+            ImageAnnotation(f'{img_ann.image_name}2', image2, bboxes2),
+            ...
+                ]
+
+def write_results(img_ann: ImageAnnotation):
+    # write image cv2.imwrite(, image) dataset_image_path
+    # write img_ann.annotations into new file with name dataset_annotation_path
+
+
+def process_image(img_ann):
+    results = image_processing(img_ann)
+    for res_ann in results:
+        write_results(res_ann)
+    write_results(img_ann)
+    os.remove(img_ann.image_path)
+    os.remove(img_ann.annotation_path)
+
+
+def main():
+    while True:
+        images = os.listdir(images_dir)
+        if len(images) == 0:
+            time.sleep(5)
+            continue
+
+        for image in images:
+            image_path = os.path.join(images_dir, image)
+            process_image(ImageAnnotation(image_path))
+
+if __name__ == '__main__':
+    main()