Update app.py

app.py

@@ -22,8 +22,10 @@ st.text("Build with Streamlit and OpenCV")
 face_cascade = cv2.CascadeClassifier('frecog/haarcascade_frontalface_default.xml')
 eye_cascade = cv2.CascadeClassifier('frecog/haarcascade_eye.xml')
 smile_cascade = cv2.CascadeClassifier('frecog/haarcascade_smile.xml')
-obj_detector = pipeline('object-detection')
-
+#@st_cache
+#od():
+    #obj_detector = pipeline('object-detection')
+    #return obj_detector
 def detect_faces(our_image):
 	new_img = np.array(our_image.convert('RGB'))
 	img = cv2.cvtColor(new_img,1)
@@ -148,7 +150,7 @@ if choice == 'Detection':
 		else:
 			st.image(our_image,width=300)
 		# Face Detection
-		task = ["Faces","Smiles","Eyes","Cannize","Cartonize","detect_objects"]
+		task = ["Detect_any_objects", "Faces","Smiles","Eyes","Cannize","Cartonize"]
 		feature_choice = st.sidebar.selectbox("Find Features",task)
 		if st.button("Process"):
 			if feature_choice == 'Faces':
@@ -171,7 +173,7 @@ if choice == 'Detection':
 			elif feature_choice == 'Cannize':
 				result_canny = cannize_image(our_image)
 				st.image(result_canny)
-			elif feature_choice == 'detect_objects':
+			elif feature_choice == 'Detect_any_objects':
 				detect_objects(our_image)
 			
 elif choice == 'About':