Revert "update source"

This reverts commit d44e0e76290fd1b543e0ebabd8a7a177a12b9257.

app.py

@@ -34,7 +34,7 @@ def transform_image(image, box):
     
     img_height, img_width = dst_img.shape[0:2]
     if img_height/img_width >= 1.25:
-        dst_img = np.rot90(dst_img, k=3)
+            dst_img = np.rot90(dst_img, k=3)
 
     return dst_img
 
@@ -44,36 +44,30 @@ def main():
     uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
     if uploaded_file is not None:
-        # Create two columns
-        col1, col2 = st.columns(2)
-
-        # Display the uploaded image in the left column
-        with col1:
-            st.header("Uploaded Image")
-            file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
-            org_image = cv2.imdecode(file_bytes, 1)
-            st.image(org_image, channels="BGR", caption='Uploaded Image')
+        # Convert the uploaded file to an OpenCV image
+        file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
+        org_image = cv2.imdecode(file_bytes, 1)
+        st.image(org_image, channels="BGR", caption='Uploaded Image')
 
         images = []
         start = time.perf_counter()
         boxes = box_engine(org_image)
         processing_time = time.perf_counter() - start
+        st.write(f"Box detection took {processing_time:.2f} seconds.")
 
-        for box in boxes:
+        for box in boxes[::-1]:
             org_image = cv2.polylines(org_image, [box.astype(np.int32)], isClosed=True, color=(0, 255, 0), thickness=2)
             image = transform_image(org_image, box)
             images.append(image)
 
-        texts = text_engine(images)
+        # Convert back to PIL Image for displaying
+        output_image = Image.fromarray(cv2.cvtColor(org_image, cv2.COLOR_BGR2RGB))
+        st.image(output_image, caption='Detected Text Boxes', use_column_width=True)
 
-        # Display the result in the right column
-        with col2:
-            st.header("Detected Text Boxes and Extracted Text")
-            output_image = Image.fromarray(cv2.cvtColor(org_image, cv2.COLOR_BGR2RGB))
-            st.image(output_image, caption='Detected Text Boxes', use_column_width=True)
-            st.write(f"Processing time: {processing_time:.2f} seconds")
-            st.write("Extracted Texts:")
-            st.write(texts)
+        texts = text_engine(images)
+        
+        st.write("Extracted Texts:")
+        st.write(texts)
 
 if __name__ == '__main__':
     main()