nodes/kijai-ComfyUI-DynamiCrafterWrapper
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Update nodes.py

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kijai
2024-08-16 00:14:08 +03:00
parent c55b6b8a20
commit df0f87f020
1 changed files with 4 additions and 11 deletions
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nodes.py
+4 -11
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@@ -11,7 +11,6 @@ import comfy.utils
from contextlib import nullcontext
from .lvdm.models.samplers.ddim import DDIMSampler
from .lvdm.modules.networks.openaimodel3d import ControlNet
from .utils.enhanced_clip_vision import encode_image_masked
from contextlib import nullcontext
try:
@@ -557,9 +556,8 @@ class DynamiCrafterI2V:
self.model.image_proj_model.to(device)
text_emb = positive[0][0].to(device)
#cond_images = clip_vision.encode_image(image.permute(0, 2, 3, 1))['last_hidden_state'].to(device)
cond_images = encode_image_masked(clip_vision, image.permute(0, 2, 3, 1), batch_size=0, tiles=4, ratio=0.1).last_hidden_state.to(device)
#cond_images = torch.sum(cond_images, dim=0).unsqueeze(0)
cond_images = clip_vision.encode_image(image.permute(0, 2, 3, 1))['last_hidden_state'].to(device)
cond_images = torch.sum(cond_images, dim=0).unsqueeze(0)
cond_images = torch.mean(cond_images, dim=0).unsqueeze(0)
img_emb = self.model.image_proj_model(cond_images)
@@ -863,16 +861,11 @@ class ToonCrafterInterpolation:
text_emb = positive[0][0].to(device)
#cond_images = clip_vision.encode_image(image.permute(0, 2, 3, 1))["last_hidden_state"].to(device)
#cond_images2 = clip_vision.encode_image(image2.permute(0, 2, 3, 1))["last_hidden_state"].to(device)
self.model.image_proj_model.to(device)
cond_images = encode_image_masked(clip_vision, image.permute(0, 2, 3, 1), batch_size=0, tiles=4, ratio=1).last_hidden_state.to(device)
cond_images = torch.sum(cond_images, dim=0).unsqueeze(0)
cond_images = clip_vision.encode_image(image.permute(0, 2, 3, 1))["last_hidden_state"].to(device)
img_emb = self.model.image_proj_model(cond_images)
if len(images) !=1:
cond_images2 = encode_image_masked(clip_vision, image2.permute(0, 2, 3, 1), batch_size=0, tiles=4, ratio=1).last_hidden_state.to(device)
cond_images2 = torch.sum(cond_images2, dim=0).unsqueeze(0)
cond_images2 = clip_vision.encode_image(image2.permute(0, 2, 3, 1))["last_hidden_state"].to(device)
img_emb2 = self.model.image_proj_model(cond_images2)
img_embeds = img_emb * image_embed_ratio + img_emb2 * (1.0 - image_embed_ratio)
else: