Update app.py

app.py

@@ -33,16 +33,16 @@ if img_file_buffer is not None:
      test_image = Image.open(img_file_buffer)
      st.image(test_image, use_column_width=True)
      st.write(type(test_image))
-     test_image = np.asarray(test_image)
-     gray = cv2.cvtColor(test_image,cv2.COLOR_BGR2GRAY)
+     image = np.asarray(test_image)
+     gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
      face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
-     faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+     faces = face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5)
 
      i = 0
 
      for (x,y,w,h) in faces:
              i = i+1
-             cv2.rectangle(test_image,(x,y),(x+w,y+h),(203,12,255),2)
+             cv2.rectangle(image,(x,y),(x+w,y+h),(203,12,255),2)
 
              img_gray=gray[y:y+h,x:x+w]
 
@@ -66,7 +66,7 @@ if img_file_buffer is not None:
             
              col = (0,255,0)
 
-             cv2.putText(test_image, str(i),(x,y),cv2.FONT_HERSHEY_SIMPLEX,1,col,2)
-     st.image(cv2.cvtColor(test_image, cv2.COLOR_BGR2RGB))
+             cv2.putText(image, str(i),(x,y),cv2.FONT_HERSHEY_SIMPLEX,1,col,2)
+     st.image(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
 if bytes_data is None:
      st.stop()