add lerp

app.py

@@ -97,7 +97,7 @@ norm = transforms.Normalize(means,stds)
 norms = torch.tensor(means)[None,:,None,None].cuda()
 stds = torch.tensor(stds)[None,:,None,None].cuda()
 
-def inference_step(vid, start_sec, duration, out_fps):
+def inference_step(vid, start_sec, duration, out_fps, interpolate):
     clip = vid.get_clip(start_sec, start_sec + duration)
     video_arr = torch.from_numpy(clip['video']).permute(3, 0, 1, 2)
     audio_arr = np.expand_dims(clip['audio'], 0)
@@ -114,12 +114,12 @@ def inference_step(vid, start_sec, duration, out_fps):
         output = (output * stds + norms).clip(0, 1) * 255.
 
         output_video = output.permute(0, 2, 3, 1).float().detach().cpu().numpy()
-        output_video[1:] = output_video[1:]*(0.5) + output_video[:-1]*(0.5)
+        if interpolate == 'Yes': output_video[1:] = output_video[1:]*(0.5) + output_video[:-1]*(0.5)
     
     return output_video, audio_arr, out_fps, audio_fps
 
 
-def predict_fn(filepath, start_sec, duration, out_fps):
+def predict_fn(filepath, start_sec, duration, out_fps, interpolate):
     # out_fps=12
     vid = EncodedVideo.from_path(filepath)
     for i in range(duration):
@@ -127,7 +127,8 @@ def predict_fn(filepath, start_sec, duration, out_fps):
             vid = vid,
             start_sec = i + start_sec,
             duration = 1,
-            out_fps = out_fps
+            out_fps = out_fps,
+            interpolate = interpolate
         )
         gc.collect()
         if i == 0:
@@ -159,7 +160,7 @@ article = "<div style='text-align: center;'>ArcaneGan by <a href='https://twitte
 
 gr.Interface(
     predict_fn,
-    inputs=[gr.inputs.Video(), gr.inputs.Slider(minimum=0, maximum=300, step=1, default=0), gr.inputs.Slider(minimum=1, maximum=10, step=1, default=2), gr.inputs.Slider(minimum=12, maximum=30, step=6, default=24)],
+    inputs=[gr.inputs.Video(), gr.inputs.Slider(minimum=0, maximum=300, step=1, default=0), gr.inputs.Slider(minimum=1, maximum=10, step=1, default=2), gr.inputs.Slider(minimum=12, maximum=30, step=6, default=24), gr.inputs.Radio(choices=['Yes','No'], type="value", default='Yes', label='Remove flickering'],
     outputs=gr.outputs.Video(),
     title='ArcaneGAN On Videos',
     description = description,