Update app.py

app.py

@@ -72,24 +72,27 @@ if img_file_buffer is not None:
     faces = face_cascade.detectMultiScale(
         image=img_gray, scaleFactor=1.3, minNeighbors=5)
     st.write("gray")
-    for (x, y, w, h) in faces:
-        cv2.rectangle(img=img, pt1=(x, y), pt2=(
-            x + w, y + h), color=(255, 0, 0), thickness=2)
-        roi_gray = img_gray[y:y + h, x:x + w]
-        roi_gray = cv2.resize(roi_gray, (48, 48), interpolation=cv2.INTER_AREA)
-        if np.sum([roi_gray]) != 0:
-            roi = roi_gray.astype('float') / 255.0
-            roi = img_to_array(roi)
-            roi = np.expand_dims(roi, axis=0)
-            prediction = classifier.predict(roi)[0]
-            maxindex = int(np.argmax(prediction))
-            finalout = emotion_dict[maxindex]
-            output = str(finalout)
-            st.write(output)
-        label_position = (x, y)
-        img = cv2.putText(img, output, label_position, cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
-        st.image(img, use_column_width=True)
-        st.write("emotion done")
+    try:
+        for (x, y, w, h) in faces:
+            cv2.rectangle(img=img, pt1=(x, y), pt2=(
+                x + w, y + h), color=(255, 0, 0), thickness=2)
+            roi_gray = img_gray[y:y + h, x:x + w]
+            roi_gray = cv2.resize(roi_gray, (48, 48), interpolation=cv2.INTER_AREA)
+            if np.sum([roi_gray]) != 0:
+                roi = roi_gray.astype('float') / 255.0
+                roi = img_to_array(roi)
+                roi = np.expand_dims(roi, axis=0)
+                prediction = classifier.predict(roi)[0]
+                maxindex = int(np.argmax(prediction))
+                finalout = emotion_dict[maxindex]
+                output = str(finalout)
+                st.write(output)
+            label_position = (x, y)
+            img = cv2.putText(img, output, label_position, cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
+            st.image(img, use_column_width=True)
+            st.write("emotion done")
+        except:
+            st.write("face is not clear")
 
     #########################
     imgS = cv2.resize(image,(0,0),None,0.25,0.25)