update

app.py

@@ -30,7 +30,7 @@ def set_seed(seed):
 model_paths = {
     "sd3": "stabilityai/stable-diffusion-3-medium-diffusers",
     "sd3.5": "stabilityai/stable-diffusion-3.5-large",
-    # "wan-t2v": "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
+    "wan-t2v": "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
 }
 
 # Global variable for current model
@@ -81,10 +81,8 @@ def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps
             video1_path = os.path.join(OUTPUT_DIR, f"{seed}_CFG-Zero-Star.mp4")
             export_to_video(video1_frames, video1_path, fps=16)
 
-            if use_cfg_zero_star:
-                return None, None, video1_path, None, seed
-            else:
-                return None, None, None, video1_path, seed
+            return None, None, video1_path, seed
+
         
             # set_seed(seed)
             # video2_frames = model(
@@ -131,7 +129,7 @@ def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps
             use_zero_init=use_zero_init,
             zero_steps=zero_steps
         ).images[0]
-        return image1, image2, seed
+        return image1, image2, None, seed
         #return image1, image2, None, None, seed
     else:
         image = model(
@@ -143,9 +141,9 @@ def generate_content(prompt, model_name, guidance_scale=7.5, num_inference_steps
             zero_steps=zero_steps
         ).images[0]
         if use_cfg_zero_star:
-            return image, None, seed
+            return image, None, None, seed
         else:
-            return None, image, seed
+            return None, image, None, seed
         # if use_cfg_zero_star:
         #     return image, None, None, None, seed
         # else:
@@ -179,6 +177,7 @@ with gr.Blocks() as demo:
         outputs=[
             gr.Image(type="pil", label="CFG-Zero* Image"),
             gr.Image(type="pil", label="CFG Image"),
+            gr.Video(label="Video"),
             gr.Textbox(label="Used Seed")
         ],
         #title="CFG-Zero*: Improved Classifier-Free Guidance for Flow Matching Models",