Update app.py

app.py

@@ -25,11 +25,10 @@ import gradio as gr
 import numpy as np
 
 from mmdet.apis import init_detector, inference_detector
-from utils import show_result
+from utils import make_gif, show_result
 from mmcv import Config
 import openpsg
 
-
 DESCRIPTION = '''# ECCV'22 | Panoptic Scene Graph Generation
 
 
@@ -55,7 +54,6 @@ Inference takes 10-30 seconds per image. The model is PSGTR (60 epochs).
 '''
 FOOTER = '<img id="visitor-badge" src="https://visitor-badge.glitch.me/badge?page_id=c-liangyu.openpsg" alt="visitor badge" />'
 
-
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser()
     parser.add_argument('--device', type=str, default='cpu')
@@ -88,12 +86,14 @@ class Model:
 
     def infer(self, input_image, num_rel):
         result = inference_detector(self.model, input_image)
-        return show_result(input_image,
+        displays = show_result(input_image,
                             result,
                             is_one_stage=True,
                             num_rel=num_rel,
                             show=True
                             )
+        gif = make_gif(displays[:10] if len(displays) > 10 else displays)
+        return gif, displays
 
 
 def main():
@@ -121,7 +121,9 @@ def main():
                     run_button = gr.Button(value='Run')
             with gr.Column():
                 with gr.Row():
-                    result = gr.Gallery(label='PSGTR Result', type='numpy')
+                    gif = gr.Image(label='Top Relations')
+                with gr.Row():
+                    displays = gr.Gallery(label='PSGTR Result', type='numpy')
 
         with gr.Row():
             paths = sorted(pathlib.Path('images').rglob('*.jpg'))
@@ -139,7 +141,7 @@ def main():
                          inputs=[
                             input_image, num_rel
                          ],
-                         outputs=result)
+                         outputs=[gif, displays])
 
         example_images.click(fn=set_example_image,
                              inputs=example_images,