Upload app.py

app.py

@@ -190,13 +190,38 @@ def predict(img):
 
 
 """gradio interface"""
-demo = gr.Interface(
+"""demo = gr.Interface(
     fn=predict,
     inputs=gr.Image(type="pil", width=244, height=244),  
     outputs="label", 
     title="Animal Classifier",
     description="Classify 30 animal categories: antelope, buffalo, chimpanzee, cow, deer, dolphin, elephant, fox, giant+panda, giraffe, gorilla, grizzly+bear, hamster, hippopotamus, horse, humpback+whale, leopard, lion, moose, otter, ox, pig, polar+bear, rabbit, rhinoceros, seal, sheep, squirrel, tiger, zebra"
 )
+"""
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Animal Classifier")
+    gr.Markdown("Classify 30 animal categories: antelope, buffalo, chimpanzee, cow, deer, dolphin, elephant, fox, giant+panda, giraffe, gorilla, grizzly+bear, hamster, hippopotamus, horse, humpback+whale, leopard, lion, moose, otter, ox, pig, polar+bear, rabbit, rhinoceros, seal, sheep, squirrel, tiger, zebra")
+    with gr.Row():
+        upload = gr.File(
+            file_count="multiple",
+            file_types=["image"],
+            label="Upload Images"
+        )
+        submit = gr.Button("Classify")
+    
+    with gr.Row():
+        gallery = gr.Gallery(label="Uploaded Images")
+        predictions = gr.Textbox(label="Predictions", interactive=False)
+    
+    submit.click(
+        fn=lambda files: (
+            [f.name for f in files],
+            ", ".join([predict([file]) for file in files])
+        ),
+        inputs=upload,
+        outputs=[gallery, predictions]
+    )
 
 """launch interface"""
 if __name__ == "__main__":