my

app.py

@@ -88,16 +88,16 @@ def process_image():
     )
     bounding_box_annotator = sv.BoundingBoxAnnotator()
     label_annotator = sv.LabelAnnotator()
-    image_dir = "./data1"
-    files = os.listdir('./data1')
+    image_dir = "./mnt/data1"
+    files = os.listdir('./mnt/data1')
     files.sort()
     files = files[0:100]
     print(files)
     counter = 0
     for ii in files:
-        random_image_data = cv2.imread('./data1/' + ii)
-        random_image_data1 = cv2.imread('./data1/' + ii)
-        results = model(source='./data1/' + ii, conf=0.07)[0]
+        random_image_data = cv2.imread('./mnt/data1/' + ii)
+        random_image_data1 = cv2.imread('./mnt/data1/' + ii)
+        results = model(source='./mnt/data1/' + ii, conf=0.07)[0]
         detections = sv.Detections.from_ultralytics(results)
         annotated_image = bounding_box_annotator.annotate(scene=random_image_data, detections=detections)
         annotated_image = label_annotator.annotate(scene=annotated_image, detections=detections)
@@ -125,7 +125,7 @@ def process_image():
             user_network_directory='./EasyOCR-Trainer/EasyOCR/user_network')
         import re
         input_file_path = './bounding_boxes.txt'
-        cropped_images_folder = './cropped_images/'
+        cropped_images_folder = ./mnt/cropped_images/'
         output_csv_path = './Folder2/' + ii + 'bounding_boxes_with_recognition.csv'
         print(f"Checking contents of /mnt/data: {bounding_box_save_path}")
         print(f"Directory listing: {os.listdir('/mnt/data')}")