Update app.py

app.py

@@ -19,11 +19,6 @@ import tempfile
 import subprocess
 
 
-# @st.cache(allow_output_mutation=True)
-# # @st.cache_resource(allow_output_mutation=True)
-# def get_model():
-#     return load_model()
-
 # Load the OCR model outside the function to prevent reloading it every time
 ocr_model = load_model()
 
@@ -180,27 +175,6 @@ def download_ultralytics_yolov3_folder():
     st.text("Download and extraction completed!")
 
 
-def get_detected_boxes(txt_path, img_width, img_height):
-    with open(txt_path, 'r') as f:
-        lines = f.readlines()
-        boxes = []
-        for line in lines:
-            parts = list(map(float, line.strip().split()))
-            # Assuming the format is: class x_center y_center width height confidence
-            x_center, y_center, width, height = parts[1:5]
-            
-            # Convert to pixel values
-            x_center *= img_width
-            y_center *= img_height
-            width *= img_width
-            height *= img_height
-
-            boxes.append([x_center, y_center, width, height])
-
-    return boxes
-
-
-
 def process_with_yolo(img_pil):
 
 
@@ -309,12 +283,6 @@ def display_detected_lines(original_path, output_path):
 
 
 
-def crop_detected_line(img_path, bounding_box):
-    with Image.open(img_path) as img:
-        cropped_img = img.crop(bounding_box)
-    return cropped_img
-
-
 def perform_ocr_on_detected_lines(detected_line_paths):
     """
     Performs OCR on the provided list of detected line image paths.