my

app.py

@@ -39,15 +39,15 @@ def calculate_iou(bbox1, bbox2):
     return iou
 
 
-cropped_dir = "D:/demo/OCR-Project/cropped_images/"
+cropped_dir = "./cropped_images/"
 if os.path.exists(cropped_dir):
         shutil.rmtree(cropped_dir)
 os.makedirs(cropped_dir, exist_ok=True)
 
-output_dir1 = "D:/demo/OCR-Project/Folder1"
-output_dir2 = "D:/demo/OCR-Project/Folder2"
-output_dir3 = "D:/demo/OCR-Project/Folder3"
-UPLOAD_FOLDER = "D:/demo/OCR-Project/data1"
+output_dir1 = "./Folder1"
+output_dir2 = "./Folder2"
+output_dir3 = "./Folder3"
+UPLOAD_FOLDER = "./data1"
 os.makedirs(output_dir1, exist_ok=True)
 os.makedirs(output_dir2, exist_ok=True)
 os.makedirs(output_dir3, exist_ok=True)
@@ -82,14 +82,14 @@ def process_image():
 
     model = YOLOv10(f'./runs/detect/train3/weights/best (1).pt')
     dataset = sv.DetectionDataset.from_yolo(
-        images_directory_path=f"/data/MyNewVersion5.0Dataset/valid/images",
-        annotations_directory_path=f"/data/MyNewVersion5.0Dataset/valid/labels",
-        data_yaml_path=f"/data/MyNewVersion5.0Dataset/data.yaml"
+        images_directory_path=f"./data/MyNewVersion5.0Dataset/valid/images",
+        annotations_directory_path=f"./data/MyNewVersion5.0Dataset/valid/labels",
+        data_yaml_path=f"./data/MyNewVersion5.0Dataset/data.yaml"
     )
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
     image_dir = "./data1"
-    files = os.listdir('/data1')
+    files = os.listdir('./data1')
     files.sort()
     files = files[0:100]
     print(files)
@@ -107,7 +107,7 @@ def process_image():
         bounding_boxes = results.boxes.xyxy.cpu().numpy()
         class_ids = results.boxes.cls.cpu().numpy()
         confidences = results.boxes.conf.cpu().numpy()
-        bounding_box_save_path = "/bounding_boxes.txt"
+        bounding_box_save_path = "./bounding_boxes.txt"
         with open(bounding_box_save_path, 'w') as f:
             for i, (bbox, class_id, confidence) in enumerate(zip(bounding_boxes, class_ids, confidences)):
                 x1, y1, x2, y2 = map(int, bbox)
@@ -121,8 +121,8 @@ def process_image():
         reader = easyocr.Reader(
             ['en'],
             recog_network='en_sample',
-            model_storage_directory='/EasyOCR-Trainer/EasyOCR/easyocr/model',
-            user_network_directory='/EasyOCR-Trainer/EasyOCR/user_network')
+            model_storage_directory='./EasyOCR-Trainer/EasyOCR/easyocr/model',
+            user_network_directory='./EasyOCR-Trainer/EasyOCR/user_network')
         import re
         input_file_path = '/bounding_boxes.txt'
         cropped_images_folder = '/cropped_images/'