Update app.py

app.py

@@ -1,5 +1,4 @@
 import math
-
 import gradio as gr
 import tensorflow as tf
 
@@ -19,27 +18,31 @@ new_model = tf.keras.models.load_model(config["model"])
 def classify_image(inp):
     inp = inp.reshape((-1, config["size"], config["size"], 3))
     prediction = new_model.predict(inp).flatten()
-    print(prediction)
+
     if len(prediction) > 1:
         probability = 100 * math.exp(prediction[0]) / (math.exp(prediction[0]) + math.exp(prediction[1]))
     else:
         probability = round(100. / (1 + math.exp(-prediction[0])), 2)
+
     if probability > 45:
-        return "Glaucoma", probability
-    if probability > 25:
-        return "Unclear", probability
-    return "Not glaucoma", probability
+        label = "Glaucoma"
+    elif probability > 25:
+        label = "Unclear"
+    else:
+        label = "Not glaucoma"
 
+    return {"Label": label, "Glaucoma probability (0 - 100)": probability}
 
-gr.Interface(
+iface = gr.Interface(
     fn=classify_image, 
     inputs=gr.inputs.Image(shape=(config["size"], config["size"])),
     outputs=[
-    gr.outputs.Textbox(label="Label"),
-    gr.outputs.Textbox(label="Glaucoma probability (0 - 100)"),
+        gr.outputs.Textbox(label="Label"),
+        gr.outputs.Textbox(label="Glaucoma probability (0 - 100)")
     ],
     examples=["001.jpg", "002.jpg", "225.jpg"],
     flagging_options=["Correct label", "Incorrect label"],
-    allow_flagging="manual",
-).launch()
+    allow_flagging="manual"
+)
 
+iface.launch()