Update app.py

app.py

@@ -44,21 +44,25 @@ title = "CIFAR10 trained on ResNet18 Model with GradCAM"
 description = "Gradio interface to infer on ResNet18 model, and get GradCAM results"
 examples = [["cat.jpg", 0.5, -1], ["dog.jpg", 0.5, -1]]
 demo = gr.Interface(
-    inference, 
-    inputs = [gr.Image(shape=(32, 32), label="Input Image"), gr.Slider(0, 1, value = 0.5, label="Opacity of GradCAM"), gr.Slider(-2, -1, value = -2, step=1, label="Which Layer?")], 
+    # inference, 
+    # inputs = [gr.Image(shape=(32, 32), label="Input Image"), gr.Slider(0, 1, value = 0.5, label="Opacity of GradCAM"), gr.Slider(-2, -1, value = -2, step=1, label="Which Layer?")], 
+    # outputs = [gr.Label(num_top_classes=3), gr.Image(shape=(32, 32), label="Output").style(width=128, height=128)],
+    # title = title,
+    # description = description,
+    # examples = examples,
+    fn=None,  # We'll add the function later after defining all functions
+    inputs=[
+        gr.InterfaceChoice(["Yes", "No"], label="View GradCAM images?"),
+        gr.InterfaceNumber(label="Number of GradCAM images to view", default=5, min=1, max=10),
+        gr.InterfaceText(label="Layer name for GradCAM visualization", default="layer4", lines=1),
+        gr.InterfaceSlider(label="Opacity", min=0.1, max=1.0, default=0.5, step=0.1),
+        gr.InterfaceChoice(["Yes", "No"], label="View misclassified images?"),
+        gr.InterfaceNumber(label="Number of misclassified images to view", default=5, min=1, max=10),
+        gr.InterfaceChoice(["Upload New Images", "Example Images"], label="Select images source"),
+        gr.InterfaceImage("file" if "Interface" in gr.__file__ else "image", label="Uploaded image" if "Interface" in gr.__file__ else "Image"),
+        gr.InterfaceButton("Submit", label="View Images")
+        ],
     outputs = [gr.Label(num_top_classes=3), gr.Image(shape=(32, 32), label="Output").style(width=128, height=128)],
-    title = title,
-    description = description,
-    examples = examples,
+    live=True
 )
 demo.launch()
-
-demo = gr.Interface(
-    inference, 
-    inputs = [gr.Image(shape=(32, 32), label="Input Image"), gr.Slider(0, 1, value = 0.5, label="Opacity of GradCAM"), gr.Slider(-2, -1, value = -2, step=1, label="Which Layer?")], 
-    outputs = [gr.Label(num_top_classes=3), gr.Image(shape=(32, 32), label="Output").style(width=128, height=128)],
-    title = title,
-    description = description,
-    examples = examples,
-)
-demo.launch()