nodes/raindrop313-ComfyUI-WanVideoStartEndFrames
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge pull request #7 from facok/main

Browse Source 
feat: add start and end frame weight controls for video transitions
This commit is contained in:
raindrop313
2025-03-20 10:32:34 +08:00
committed by GitHub
parent 9b6c34f2df eb0f46e9e2
commit 43d223ffa2
1 changed files with 16 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files
nodes.py
+16 -5
View File
@@ -984,7 +984,10 @@ class WanVideoStartEndImageClipEncode_2frames:
"tooltip": "Additional clip embed multiplier"}),
"adjust_resolution": ("BOOLEAN", {"default": True,
"tooltip": "Performs the same resolution adjustment as in the original code"}),
"start_frame_weight": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01,
"tooltip": "Weight for the start frame. Higher values (>1.0) make the starting image more influential throughout the video, resulting in stronger adherence to the start frame's features. Lower values (<1.0) reduce its influence, allowing more creative freedom. Set to 0 to completely ignore the start frame."}),
"end_frame_weight": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01,
"tooltip": "Weight for the end frame. Higher values (>1.0) make the ending image more influential, causing the video to transition more strongly toward the end frame's characteristics. Lower values (<1.0) reduce its influence. Balancing with start_frame_weight allows control over transition speed and style."}),
}
}
@@ -993,9 +996,9 @@ class WanVideoStartEndImageClipEncode_2frames:
FUNCTION = "process"
CATEGORY = "WanVideoStartEndFrame"
def process(self, clip_vision, vae, start,end, num_frames, generation_width, generation_height, force_offload=True,
noise_aug_strength=0.0,
latent_strength=1.0, clip_embed_strength=1.0, adjust_resolution=True):
def process(self, clip_vision, vae, start, end, num_frames, generation_width, generation_height, force_offload=True,
noise_aug_strength=0.0, latent_strength=1.0, clip_embed_strength=1.0, adjust_resolution=True,
start_frame_weight=1.0, end_frame_weight=1.0):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
@@ -1042,6 +1045,10 @@ class WanVideoStartEndImageClipEncode_2frames:
# Step 1: Create initial mask with ones for first frame, zeros for others
mask = torch.ones(1, num_frames+1, lat_h, lat_w, device=device)
mask[:, 1:-1] = 0
# No longer applying weights to the mask - this should improve transition smoothness
# mask[:, 0] *= start_frame_weight
# mask[:, -1] *= end_frame_weight
# Step 2: Repeat first frame 4 times and concatenate with remaining frames
first_frame_repeated = torch.repeat_interleave(mask[:, 0:1], repeats=4, dim=1)
@@ -1075,6 +1082,10 @@ class WanVideoStartEndImageClipEncode_2frames:
resized_start_image = add_noise_to_reference_video(resized_start_image, ratio=noise_aug_strength)
resized_end_image = add_noise_to_reference_video(resized_end_image, ratio=noise_aug_strength)
# Apply start and end frame weights to image data
resized_start_image = resized_start_image * start_frame_weight
resized_end_image = resized_end_image * end_frame_weight
# Step 2: Create zero padding frames
zero_frames = torch.zeros(3, num_frames - 1, h, w, device=device)
@@ -1088,7 +1099,7 @@ class WanVideoStartEndImageClipEncode_2frames:
vae.model.clear_cache()
vae.to(offload_device)
# clip_context单图像的编码
# clip_context contains the encoding of a single image
image_embeds = {
"image_embeds": y,
"clip_context": clip_context,