add video for visualization

app.py

@@ -121,6 +121,7 @@ with gr.Blocks() as demo:
                         fn=generate_model,
                         outputs=out_lst)
 
+            out_vid = gr.Video(label="Image + Normal + Recon + Refined Recon")
             out_vid_download = gr.File(
                 label="Download Video, welcome share on Twitter with #ICON")
 
@@ -140,7 +141,7 @@ with gr.Blocks() as demo:
                 label="Download refined clothed human mesh")
 
     out_lst = [out_smpl, out_smpl_download, out_smpl_npy_download, out_recon, out_recon_download,
-               out_final, out_final_download, out_vid_download, overlap_inp]
+               out_final, out_final_download, out_vid, out_vid_download, overlap_inp]
 
     btn_submit.click(fn=generate_model, inputs=[
                      inp, radio_choice], outputs=out_lst)

apps/infer.py

@@ -453,4 +453,4 @@ def generate_model(in_path, model_type):
     gc.collect()
     torch.cuda.empty_cache()
     
-    return [smpl_path, smpl_path, smpl_npy_path, recon_path, recon_path, refine_path, refine_path, video_path, overlap_path]
+    return [smpl_path, smpl_path, smpl_npy_path, recon_path, recon_path, refine_path, refine_path, video_path, video_path, overlap_path]

gradio_cached_examples/13/log.csv

@@ -1,9 +0,0 @@
-'flag','username','timestamp'
-'','','2022-08-01 22:47:24.908073'
-'','','2022-08-01 22:48:20.753663'
-'','','2022-08-01 22:49:15.504871'
-'','','2022-08-01 22:50:16.762017'
-'','','2022-08-01 22:51:09.444531'
-'','','2022-08-01 22:52:09.357219'
-'','','2022-08-01 22:53:02.217347'
-'','','2022-08-01 22:54:11.545178'

lib/common/render.py

@@ -34,7 +34,7 @@ from pytorch3d.renderer import (
 from pytorch3d.renderer.mesh import TexturesVertex
 from pytorch3d.structures import Meshes
 
-import os
+import os, subprocess
 
 from lib.dataset.mesh_util import SMPLX, get_visibility
 import lib.common.render_utils as util
@@ -327,6 +327,8 @@ class Render:
 
     def get_rendered_video(self, images, save_path):
         
+        tmp_path = save_path.replace('cloth', 'tmp')
+        
         self.cam_pos = []
         for angle in range(0, 360, 3):
             self.cam_pos.append(
@@ -343,7 +345,7 @@ class Render:
 
         fourcc = cv2.VideoWriter_fourcc(*"mp4v")
         video = cv2.VideoWriter(
-            save_path, fourcc, 30, (self.size * len(self.meshes) +
+            tmp_path, fourcc, 30, (self.size * len(self.meshes) +
                                     new_shape[1] * len(images), self.size)
         )
 
@@ -373,6 +375,8 @@ class Render:
             video.write(final_img)
 
         video.release()
+        
+        os.system(f'ffmpeg -y -loglevel quiet -stats -i {tmp_path} -c:v libx264 {save_path}')
 
     def get_silhouette_image(self, cam_ids=[0, 2]):