Update app.py

app.py

@@ -11,8 +11,8 @@ model = cv2.dnn_DetectionModel(net)
 model.setInputParams(scale=1 / 255, size=(416, 416), swapRB=True)
 
 def detect(image):
-    img = cv2.imread(image)
-    img = Image.fromarray(img)
+    img1 = Image.fromarray(image)
+    img = cv2.imread(img1)
     classIds, scores, boxes = model.detect(img, confThreshold=0.6, nmsThreshold=0.4)
 
     for (classId, score, box) in zip(classIds, scores, boxes):