diff --git a/examples/wanvideo/train_wan_t2v.py b/examples/wanvideo/train_wan_t2v.py
index 45a026f..cdf0d67 100644
--- a/examples/wanvideo/train_wan_t2v.py
+++ b/examples/wanvideo/train_wan_t2v.py
@@ -12,7 +12,7 @@ import numpy as np
 
 
 class TextVideoDataset(torch.utils.data.Dataset):
-    def __init__(self, base_path, metadata_path, max_num_frames=81, frame_interval=1, num_frames=81, height=480, width=832, is_i2v=False):
+    def __init__(self, base_path, metadata_path, max_num_frames=81, frame_interval=1, num_frames=81, height=480, width=832, is_i2v=False, target_fps=None):
         metadata = pd.read_csv(metadata_path)
         self.path = [os.path.join(base_path, "train", file_name) for file_name in metadata["file_name"]]
         self.text = metadata["text"].to_list()
@@ -23,6 +23,7 @@ class TextVideoDataset(torch.utils.data.Dataset):
         self.height = height
         self.width = width
         self.is_i2v = is_i2v
+        self.target_fps = target_fps
             
         self.frame_process = v2.Compose([
             v2.CenterCrop(size=(height, width)),
@@ -71,8 +72,15 @@ class TextVideoDataset(torch.utils.data.Dataset):
 
 
     def load_video(self, file_path):
-        start_frame_id = torch.randint(0, self.max_num_frames - (self.num_frames - 1) * self.frame_interval, (1,))[0]
-        frames = self.load_frames_using_imageio(file_path, self.max_num_frames, start_frame_id, self.frame_interval, self.num_frames, self.frame_process)
+        start_frame_id = 0
+        if self.target_fps is None:
+            frame_interval = self.frame_interval
+        else:
+            reader = imageio.get_reader(file_path)
+            fps = reader.get_meta_data()["fps"]
+            reader.close()
+            frame_interval = max(round(fps / self.target_fps), 1)
+        frames = self.load_frames_using_imageio(file_path, self.max_num_frames, start_frame_id, frame_interval, self.num_frames, self.frame_process)
         return frames