Update app.py

app.py

@@ -51,24 +51,24 @@ def predict_class(image):
     return prediction[0]
 
 # UI Design for single class output
-# def classify_image(image):
-#     predicted_class = predict_class(image)
-#     output = f"<h2>Predicted Class: <span style='text-transform:uppercase';>{predicted_class}</span></h2>"
-#     return output
+def classify_image(image):
+    predicted_class = predict_class(image)
+    output = f"<h2>Predicted Class: <span style='text-transform:uppercase';>{predicted_class}</span></h2>"
+    return output
 
 
 # UI Design for multy class output
-def classify_image(image):
-    results = predict_class(image)
-    print(results)
-    output = {labels.get(i): float(results[i]) for i in range(len(results))}
-    result = output if max(output.values()) >=0.98 else {"NO_CIFAR10_CLASS": 1}
-    return result
+# def classify_image(image):
+#     results = predict_class(image)
+#     print(results)
+#     output = {labels.get(i): float(results[i]) for i in range(len(results))}
+#     result = output if max(output.values()) >=0.98 else {"NO_CIFAR10_CLASS": 1}
+#     return result
 
 
 inputs = gr.inputs.Image(type="pil", label="Upload an image")
-# outputs = gr.outputs.HTML() #uncomment for single class output 
-outputs = gr.outputs.Label(num_top_classes=4)
+outputs = gr.outputs.HTML() #uncomment for single class output 
+#outputs = gr.outputs.Label(num_top_classes=4)
 
 title = "<h1 style='text-align: center;'>Image Classifier</h1>"
 description = "Upload an image and get the predicted class."