Update app.py

app.py

@@ -93,11 +93,14 @@ def get_upload_path():
     return upload_file_path
 
 
-def process_input_image(img_url):
+def process_input_image(input_):
     upload_file_path = get_upload_path()
-    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36'}
-    r = get(img_url, headers=headers)
-    arr = np.frombuffer(r.content, np.uint8)
+    if input_type == 'Paste image URL':
+        headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36'}
+        r = get(img_url, headers=headers)
+        arr = np.frombuffer(r.content, np.uint8)
+    else:
+        arr = np.frombuffer(input_, np.uint8)
     input_image = cv2.imdecode(arr, cv2.IMREAD_UNCHANGED)
     input_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
     input_image = cv2.resize(input_image, (640, 640))
@@ -105,22 +108,45 @@ def process_input_image(img_url):
     return upload_file_path
 
 
+st.markdown("<h3>Vehicle Registration Number Detection</h3>", unsafe_allow_html=True)
+desc = '''Dataset used to fine-tune YOLOv8 
+can be found <a href="https://universe.roboflow.com/my-workspace-cut7i/lpr_ocr/dataset/1" target="_blank">
+here</a> See that the input images are similar to these for better detection.
+'''
+st.markdown(desc, unsafe_allow_html=True)
+input_type = st.radio('Select an option:', ['Paste image URL', 'Capture using camera'], 
+                      captions=['Recommended for laptops/desktops', 'Recommended for mobile devices'],
+                      horizontal=True)
+
+
 try:
-    st.markdown("<h3>Vehicle Registration Number Detection</h3>", unsafe_allow_html=True)
-    desc = '''Dataset used to fine-tune YOLOv8 
-    can be found <a href="https://universe.roboflow.com/my-workspace-cut7i/lpr_ocr/dataset/1" target="_blank">
-    here</a> See that the input images are similar to these for better detection.
-    '''
-    st.markdown(desc, unsafe_allow_html=True)
-    img_url = st.text_input("Paste the image URL of the vehicle license/registration plate:", "")
-    placeholder = st.empty()
-    if img_url:
-        placeholder.empty()
-        img_path = process_input_image(img_url)
-        inference(img_path)
-        files_cleanup(img_path)
-        
+    if input_type == 'Paste image URL':
+        img_url = st.text_input("Paste the image URL of the vehicle license/registration plate:", "")
+        if img_url:
+            img_path = process_input_image(img_url)
+            inference(img_path)
+            files_cleanup(img_path)
+    else:
+        st.markdown("<h4>Capture the image in landscape mode</h4>", unsafe_allow_html=True)
+        col1, col2, col3 = st.columns([0.15, 0.7, 0.15])
+        with col1:
+            st.write(' ')
+        with col2:   
+            img_file_buffer = st.camera_input("Take the number plate's picture")
+            st.write(' ')
+        with col3:
+            st.write(' ')
+        with col2:   
+            st.write(' ')
+        with col2:   
+            st.write(' ')
+        if img_file_buffer is not None:
+            bytes_data = img_file_buffer.getvalue()
+            img_path = process_input_image(bytes_data)
+            inference(img_path)
+            files_cleanup(img_path)
+                
 except Exception as e:
     upload_file_path = get_upload_path()
     files_cleanup(upload_file_path)
-    st.error(f'An unexpected error occured:  \n{e}')
+    st.error(f'An unexpected error occured:  \n{e}')