envs

app.py

@@ -288,7 +288,7 @@ class ImageConductor:
 
         self.blur_kernel = blur_kernel
 
-    @spaces.GPU(enable_queue=True, duration=400)
+    @spaces.GPU(enable_queue=True, duration=100)
     @torch.no_grad()
     def run(self, first_frame_path, tracking_points, prompt, drag_mode, negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps, personalized, examples_type):
         if examples_type != "":
@@ -439,10 +439,12 @@ def add_tracking_points(tracking_points, first_frame_path, drag_mode, evt: gr.Se
 
 
 def add_drag(tracking_points):
-    print("before", tracking_points.value)
-
-    tracking_points.value.append([])
-    print(tracking_points.value)
+    if not isinstance(tracking_points ,list):
+        print("before", tracking_points.value)
+        tracking_points.value.append([])
+        print(tracking_points.value)
+    else:
+        tracking_points.append([])
     return {tracking_points_var: tracking_points}
     
 
@@ -509,7 +511,7 @@ block = gr.Blocks(
             radius_size=gr.themes.sizes.radius_none,
             text_size=gr.themes.sizes.text_md
         )
-        )
+        ).queue()
 with block:
     with gr.Row():
         with gr.Column():
@@ -643,4 +645,4 @@ with block:
                                             negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps, personalized, examples_type], 
                                             [output_image, output_video])
 
-block.queue().launch()
+block.launch()

pipelines/pipeline_imagecoductor.py

@@ -318,7 +318,6 @@ class ImageConductorPipeline(DiffusionPipeline):
         latents = latents * self.scheduler.init_noise_sigma
         return latents
 
-    @spaces.GPU(enable_queue=True, duration=400)
     @torch.no_grad()
     def __call__(
         self,