more to run the app

app.py

@@ -60,26 +60,27 @@ def main():
             --weights {MODEL_PATH} \
             --source {image_path} \
             --img 640 \
-            --conf 0.5 \
+            --conf 0.4 \
             --name temp_exp \
             --hide-labels \
             --hide-conf \
             --save-txt \
-            --exist-ok
+            --exist-ok \
+            --save-conf
         '''
 
         # Run the command
         os.system(command)
 
-        st.write('The detection is completed!!!')
+        # st.write('The detection is completed!!!')
 
         os.chdir(CUR_DIR)
 
-        st.write(os.path.exists('yolov5/runs/detect/temp_exp'))
+        # st.write(os.path.exists('yolov5/runs/detect/temp_exp'))
 
         if os.path.exists('yolov5/runs/detect/temp_exp'):
             processed_image = cv2.imread('yolov5/runs/detect/temp_exp/odometer_image.jpg')
-            st.write('Image boxed and loaded')
+            # st.write('Image boxed and loaded')
             text_files = os.listdir('yolov5/runs/detect/temp_exp/labels')
             original_img = cv2.imread('odometer_image.jpg')
             gray = cv2.cvtColor(original_img, cv2.COLOR_BGR2GRAY)
@@ -89,7 +90,7 @@ def main():
             else:
                 text_file_path = f'yolov5/runs/detect/temp_exp/labels/{text_files[0]}'
                 x1, y1, x2, y2 = yolov5_to_image_coordinates(text_file_path)
-                st.write(x1, y1, x2, y2)
+                # st.write(x1, y1, x2, y2)
                 cropped_image = gray[x1:x2, y1:y2]
 
                 reader = easyocr.Reader(['en'])
@@ -101,14 +102,16 @@ def main():
                 else:
                     odometer_value = 'not detected'
                     display_text = f"The odometer value is {odometer_value}!!!"
-            try:
-                shutil.rmtree('odometer_image.jpg')
-            except:
-                pass
         else:
             display_text = "An odometer is not detected in the image!!!"
             processed_image = cv2.imread('odometer_image.jpg')
 
+        try:
+            shutil.rmtree('odometer_image.jpg')
+            shutil.rmtree('runs/detect/temp_exp')
+        except:
+            pass
+
         # Resize or preprocess the image as needed for your model
         # For example, resizing to a specific input size
         # processed_image = cv2.resize(image_np, (224, 224))

xyxy_converter.py

@@ -14,8 +14,14 @@ def yolov5_to_image_coordinates(text_file, image_width=640, image_height=640):
     with open(text_file, 'r') as f:
         xywh_text = f.read()
     
-    xywh_splitted = xywh_text.split('\n')[0]
-    yolo_box = [float(i) for i in xywh_splitted.split(' ')[1:]]   
+    xywh_splitted = xywh_text.split('\n')
+    if xywh_splitted[-1] == '':
+        xywh_splitted = xywh_text.split('\n')[0]
+    else:
+        conf_list = [float(i.split(' ')[-1]) for i in xywh_splitted]
+        max_conf_idx = conf_list.index(max(conf_list))
+        xywh_splitted = xywh_text.split('\n')[max_conf_idx]
+    yolo_box = [float(i) for i in xywh_splitted.split(' ')[1:-1]]   
     # yolo_box = [float(i) for i in xywh_text.replace('\n', '').split(' ')[1:]]
         
     x_center, y_center, width, height = yolo_box

yolov5/runs/detect/temp_exp/labels/odometer_image.txt

@@ -1,10 +1,2 @@
-0 0.635938 0.4625 0.30625 0.325
-0 0.452344 0.715625 0.429688 0.18125
-0 0.452344 0.715625 0.429688 0.18125
-0 0.409375 0.657031 0.375 0.148438
-0 0.409375 0.657031 0.375 0.148438
-0 0.409375 0.657031 0.375 0.148438
-0 0.564844 0.671094 0.207813 0.0859375
-0 0.442187 0.621094 0.38125 0.139062
-0 0.510156 0.665625 0.254687 0.11875
-0 0.539062 0.586719 0.375 0.201562
+0 0.617188 0.760156 0.128125 0.0515625 0.718977
+0 0.579687 0.696875 0.265625 0.121875 0.872913