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A few improvements to #5937.

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comfyanonymous
2024-12-06 05:48:34 -05:00
parent 005d2d3a13
commit 8af9a91e0c
3 changed files with 17 additions and 14 deletions
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15
comfy_extras/nodes_lt.py
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@@ -1,4 +1,3 @@
import io
import nodes
import node_helpers
import torch
@@ -33,7 +32,9 @@ class LTXVImgToVideo:
"width": ("INT", {"default": 768, "min": 64, "max": nodes.MAX_RESOLUTION, "step": 32}),
"height": ("INT", {"default": 512, "min": 64, "max": nodes.MAX_RESOLUTION, "step": 32}),
"length": ("INT", {"default": 97, "min": 9, "max": nodes.MAX_RESOLUTION, "step": 8}),
"batch_size": ("INT", {"default": 1, "min": 1, "max": 4096})}}
"batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}),
"image_noise_scale": ("FLOAT", {"default": 0.15, "min": 0, "max": 1.0, "step": 0.01, "tooltip": "Amount of noise to apply on conditioning image latent."})
}}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT")
RETURN_NAMES = ("positive", "negative", "latent")
@@ -41,12 +42,12 @@ class LTXVImgToVideo:
CATEGORY = "conditioning/video_models"
FUNCTION = "generate"
def generate(self, positive, negative, image, vae, width, height, length, batch_size):
def generate(self, positive, negative, image, vae, width, height, length, batch_size, image_noise_scale):
pixels = comfy.utils.common_upscale(image.movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
encode_pixels = pixels[:, :, :, :3]
t = vae.encode(encode_pixels)
positive = node_helpers.conditioning_set_values(positive, {"guiding_latent": t})
negative = node_helpers.conditioning_set_values(negative, {"guiding_latent": t})
positive = node_helpers.conditioning_set_values(positive, {"guiding_latent": t, "guiding_latent_noise_scale": image_noise_scale})
negative = node_helpers.conditioning_set_values(negative, {"guiding_latent": t, "guiding_latent_noise_scale": image_noise_scale})
latent = torch.zeros([batch_size, 128, ((length - 1) // 8) + 1, height // 32, width // 32], device=comfy.model_management.intermediate_device())
latent[:, :, :t.shape[2]] = t
@@ -78,7 +79,6 @@ class ModelSamplingLTXV:
return {"required": { "model": ("MODEL",),
"max_shift": ("FLOAT", {"default": 2.05, "min": 0.0, "max": 100.0, "step":0.01}),
"base_shift": ("FLOAT", {"default": 0.95, "min": 0.0, "max": 100.0, "step":0.01}),
"image_noise_scale": ("FLOAT", {"default": 0.15, "min": 0, "max": 100, "step": 0.01, "tooltip": "Amount of noise to apply on conditioning image latent."})
},
"optional": {"latent": ("LATENT",), }
}
@@ -88,7 +88,7 @@ class ModelSamplingLTXV:
CATEGORY = "advanced/model"
def patch(self, model, max_shift, base_shift, image_noise_scale, latent=None):
def patch(self, model, max_shift, base_shift, latent=None):
m = model.clone()
if latent is None:
@@ -111,7 +111,6 @@ class ModelSamplingLTXV:
model_sampling = ModelSamplingAdvanced(model.model.model_config)
model_sampling.set_parameters(shift=shift)
m.add_object_patch("model_sampling", model_sampling)
m.model_options.setdefault("transformer_options", {})["image_noise_scale"] = image_noise_scale
return (m, )