add

app.py

@@ -322,15 +322,17 @@ class BaseTrainer(object):
                     mocap_frame_rate = 30,
                 )
                 total_length += n
-                render_vid_path = other_tools_hf.render_one_sequence_no_gt(
-                    results_npz_file_save_path, 
-                    # results_save_path+"gt_"+test_seq_list.iloc[its]['id']+'.npz', 
-                    results_save_path,
-                    self.audio_path,
-                    self.args.data_path_1+"smplx_models/",
-                    use_matplotlib = False,
-                    args = self.args,
-                    )
+                render_vid_path = None
+                if self.args.render_video:
+                    render_vid_path = other_tools_hf.render_one_sequence_no_gt(
+                        results_npz_file_save_path, 
+                        # results_save_path+"gt_"+test_seq_list.iloc[its]['id']+'.npz', 
+                        results_save_path,
+                        self.audio_path,
+                        self.args.data_path_1+"smplx_models/",
+                        use_matplotlib = False,
+                        args = self.args,
+                        )
 
         result = [
             gr.Video(value=render_vid_path, visible=True),
@@ -741,15 +743,21 @@ def _warp_create_cuda_model(args,model,mean_upper,mean_hands,mean_lower,std_uppe
 
 
 @logger.catch
-def syntalker(audio_path,sample_stratege):
+def syntalker(audio_path,sample_stratege,render_video):
     args = config.parse_args()
+    args.use_ddim=True
+    args.render_video=True
     print("sample_stratege",sample_stratege)
     if sample_stratege==0:
         args.use_ddim=True
     elif sample_stratege==1:
         args.use_ddim=False
-    else:
-        args.use_ddim=True
+
+    if render_video==0:
+        args.render_video=True
+    elif render_video==1:
+        args.render_video=False
+
     print(sample_stratege)
     print(args.use_ddim)
     #os.environ['TRANSFORMERS_CACHE'] = args.data_path_1 + "hub/"
@@ -780,6 +788,7 @@ demo = gr.Interface(
         # gr.File(label="Please upload SMPL-X file with npz format here.", file_types=["npz", "NPZ"]),
         gr.Audio(),
         gr.Radio(choices=["DDIM", "DDPM"], label="Please select a sample strategy", type="index", value="DDIM"),  # 0 for DDIM, 1 for DDPM
+        gr.Radio(choices=["Yes", "No"], label="Please select whether render video or not, it will additionally take 10 mintues for rendering", type="index", value="Yes"),  # 0 for DDIM, 1 for DDPM
         # gr.File(label="Please upload textgrid format file here.", file_types=["TextGrid", "Textgrid", "textgrid"])
     ],  # input type
     outputs=[