Update app.py

app.py

@@ -24,10 +24,10 @@ data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
 with open("labels.txt", "r") as file:
     labels = file.read().splitlines()
 
-def classify(Textbox, Textbox2, Textbox3):
+def classify(Textbox, image_path, Textbox2, Textbox3):
     if Textbox3 == code:
         output = []
-        image_data = np.array("Image")
+        image_data = np.array(image_path)
         image_data = cv.resize(image_data, (224, 224))
         image_array = np.asarray(image_data)
         normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1
@@ -42,7 +42,6 @@ def classify(Textbox, Textbox2, Textbox3):
         max_prediction_value = -1
 
         print('Prediction')
-        
 
         Textbox2 = Textbox2.replace("[", "").replace("]", "").replace("'", "")
         Textbox2 = Textbox2.split(",")
@@ -95,15 +94,16 @@ def classify(Textbox, Textbox2, Textbox3):
         return "Unauthorized"
 
 user_inputs = [
-    gr.inputs.Textbox(label="Textbox",type="text"),
-    gr.inputs.Textbox(label="Textbox2",type="text"),
-    gr.inputs.Textbox(label="Textbox3",type="password")
+    gr.inputs.Textbox(label="Textbox", type="text"),
+    gr.inputs.Image(),
+    gr.inputs.Textbox(label="Textbox2", type="text"),
+    gr.inputs.Textbox(label="Textbox3", type="password")
 ]
 
 iface = gr.Interface(
     fn=classify,
-    inputs = user_inputs,
-    outputs="text",
+    inputs=user_inputs,
+    outputs=gr.outputs.JSON(),
     title="Classifier",
 )
 iface.launch()