.

options/Video_model/Model.py

@@ -7,7 +7,6 @@ from .tdd_svd_scheduler import TDDSVDStochasticIterativeScheduler
 from .utils import load_lora_weights, save_video
 from typing import Optional
 from glob import glob
-import torchvision.transforms as transforms
 
 svd_path = 'stabilityai/stable-video-diffusion-img2vid-xt-1-1'
 lora_repo_path = 'RED-AIGC/TDD'
@@ -47,11 +46,9 @@ def Video(
     os.makedirs(output_folder, exist_ok=True)
     base_count = len(glob(os.path.join(output_folder, "*.mp4")))
     video_path = os.path.join(output_folder, f"{base_count:06d}.mp4")
+    
 
-    if isinstance(image, Image.Image):
-        image = transforms.ToTensor()(image).unsqueeze(0).to(device)
-
-    with torch.autocast(device,dtype=torch.float32):
+    with torch.autocast(device):
         frames = pipeline(
             image, height = height, width = width,
             num_inference_steps = num_inference_steps,