Update app.py

app.py

@@ -232,6 +232,9 @@ def generate_video(prompt, seed, image=None):
     else:
         task_type = TaskType.I2V
         model_id = "Skywork/SkyReels-V1-Hunyuan-I2V"
+        seed = 43
+        generator = torch.Generator(device="cuda").manual_seed(seed)
+
         kwargs = {
             "prompt": prompt,
             "image": Image.open(image),
@@ -240,6 +243,7 @@ def generate_video(prompt, seed, image=None):
             "num_frames": 97,
             "num_inference_steps": 30,
             "seed": seed,
+            "generator": generator,
             "guidance_scale": 6.0,
             "embedded_guidance_scale": 1.0,
             "negative_prompt": "Aerial view, low quality, bad hands",
@@ -257,20 +261,20 @@ def generate_video(prompt, seed, image=None):
                 parameters_level=True,
                 compiler_transformer=False,
             ),
-        )
+        ).to("cuda")
         _predictor.initialize()
         logger.info("Predictor initialized")
-
-    output = _predictor.infer(**kwargs)
-
-    output = (output.cpu().numpy() * 255).astype(np.uint8)
-    output = output.transpose(0, 2, 3, 4, 1)
+    with torch.no_grad():
+        output = _predictor.infer(**kwargs)
+        out_samples.extend(output.frames[0])
+    #output = (output.cpu().numpy() * 255).astype(np.uint8)
+    #output = output.transpose(0, 2, 3, 4, 1)
 
     save_dir = f"./result"
     os.makedirs(save_dir, exist_ok=True)
     video_out_file = f"{save_dir}/{seed}.mp4"
     print(f"generate video, local path: {video_out_file}")
-    export_to_video([output[0, t] for t in range(output.shape[1])], video_out_file, fps=24)
+    export_to_video(out_samples, video_out_file, fps=24)
     return video_out_file, kwargs
 
 def create_gradio_interface():