Update app.py

app.py

@@ -55,9 +55,8 @@ def predict(img):
     start_time = timer()
     
     # Transform the target image and add a batch dimension
-    image = cv2.imread(img)
-    img1 = PIL.Image.open(img)
-    img1 = effnetb2_transforms(img1).unsqueeze(0)
+
+    img1 = effnetb2_transforms(img).unsqueeze(0)
     pix = normalize_2d(np.array(img))
 
     pix1=model.predict(str(image), confidence=40, overlap=30).numpy()