Update app.py

app.py

@@ -1,33 +1,34 @@
 import gradio as gr
 from PIL import Image
 from vit_model_test import CustomModel
+import time
 
 # Initialize the model
 model = CustomModel()
 
 def predict(image: Image.Image):
-    
+    # סימולציה של זמן עיבוד (למשל 5 שניות)
+    time.sleep(5)  # אפשר לשנות את הזמן לפי הצורך
     label, confidence = model.predict(image)
     result = "AI image" if label == 1 else "Real image"
     return result, f"Confidence: {confidence:.2f}%"
 
-def video_identity(video):
-    return video
+# Define the Gradio interface
+with gr.Blocks() as demo:
+    image_input = gr.Image(type="pil", label="Upload an image")
+    animation = gr.Video("https://cdn-uploads.huggingface.co/production/uploads/66d6f1b3b50e35e1709bfdf7/x7Ud8PO9QPfmrTvBVcCKE.mp4", visible=False)  # הוספת הווידאו
+    output_label = gr.Textbox(label="Classification Result", interactive=False)
+    output_confidence = gr.Textbox(label="Confidence", interactive=False)
 
-demo = gr.Interface(video_identity,
-                    gr.Video(),
-                    "https://cdn-uploads.huggingface.co/production/uploads/66d6f1b3b50e35e1709bfdf7/x7Ud8PO9QPfmrTvBVcCKE.mp4",
-                    )
-    
+    def show_animation(image):
+        return animation.update(visible=True), "", ""  # להציג את האנימציה
 
-# Define the Gradio interface
-demo = gr.Interface(
-    fn=predict,
-    inputs=gr.Image(type="pil"),
-    outputs=[gr.Textbox(), gr.Textbox()],
-    title="Vision Transformer Model",
-    description="Upload an image to classify it using the Vision Transformer model."
-)
+    def hide_animation(image):
+        result, confidence = predict(image)
+        return animation.update(visible=False), result, confidence  # להסתיר את האנימציה
+
+    image_input.change(show_animation, inputs=image_input, outputs=[animation, output_label, output_confidence])
+    image_input.change(hide_animation, inputs=image_input, outputs=[animation, output_label, output_confidence])
 
 # Launch the Gradio interface
-demo.launch()
+demo.launch()