diff --git a/comfy/model_base.py b/comfy/model_base.py index ce29fdc49..56a6798be 100644 --- a/comfy/model_base.py +++ b/comfy/model_base.py @@ -1110,9 +1110,10 @@ class WAN21(BaseModel): shape_image[1] = extra_channels image = torch.zeros(shape_image, dtype=noise.dtype, layout=noise.layout, device=noise.device) else: + latent_dim = self.latent_format.latent_channels image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center") - for i in range(0, image.shape[1], 16): - image[:, i: i + 16] = self.process_latent_in(image[:, i: i + 16]) + for i in range(0, image.shape[1], latent_dim): + image[:, i: i + latent_dim] = self.process_latent_in(image[:, i: i + latent_dim]) image = utils.resize_to_batch_size(image, noise.shape[0]) if extra_channels != image.shape[1] + 4: @@ -1245,18 +1246,14 @@ class WAN22_S2V(WAN21): out['reference_motion'] = reference_motion.shape return out -class WAN22(BaseModel): +class WAN22(WAN21): def __init__(self, model_config, model_type=ModelType.FLOW, image_to_video=False, device=None): - super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.wan.model.WanModel) + super(WAN21, self).__init__(model_config, model_type, device=device, unet_model=comfy.ldm.wan.model.WanModel) self.image_to_video = image_to_video def extra_conds(self, **kwargs): out = super().extra_conds(**kwargs) - cross_attn = kwargs.get("cross_attn", None) - if cross_attn is not None: - out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn) - - denoise_mask = kwargs.get("concat_mask", kwargs.get("denoise_mask", None)) + denoise_mask = kwargs.get("denoise_mask", None) if denoise_mask is not None: out["denoise_mask"] = comfy.conds.CONDRegular(denoise_mask) return out diff --git a/comfy_api/latest/_input_impl/video_types.py b/comfy_api/latest/_input_impl/video_types.py index 28de9651d..f646504c8 100644 --- a/comfy_api/latest/_input_impl/video_types.py +++ b/comfy_api/latest/_input_impl/video_types.py @@ -8,6 +8,7 @@ import av import io import json import numpy as np +import math import torch from comfy_api.latest._util import VideoContainer, VideoCodec, VideoComponents @@ -282,8 +283,6 @@ class VideoFromComponents(VideoInput): if self.__components.audio: audio_sample_rate = int(self.__components.audio['sample_rate']) audio_stream = output.add_stream('aac', rate=audio_sample_rate) - audio_stream.sample_rate = audio_sample_rate - audio_stream.format = 'fltp' # Encode video for i, frame in enumerate(self.__components.images): @@ -298,27 +297,12 @@ class VideoFromComponents(VideoInput): output.mux(packet) if audio_stream and self.__components.audio: - # Encode audio - samples_per_frame = int(audio_sample_rate / frame_rate) - num_frames = self.__components.audio['waveform'].shape[2] // samples_per_frame - for i in range(num_frames): - start = i * samples_per_frame - end = start + samples_per_frame - # TODO(Feature) - Add support for stereo audio - chunk = ( - self.__components.audio["waveform"][0, 0, start:end] - .unsqueeze(0) - .contiguous() - .numpy() - ) - audio_frame = av.AudioFrame.from_ndarray(chunk, format='fltp', layout='mono') - audio_frame.sample_rate = audio_sample_rate - audio_frame.pts = i * samples_per_frame - for packet in audio_stream.encode(audio_frame): - output.mux(packet) - - # Flush audio - for packet in audio_stream.encode(None): - output.mux(packet) - + waveform = self.__components.audio['waveform'] + waveform = waveform[:, :, :math.ceil((audio_sample_rate / frame_rate) * self.__components.images.shape[0])] + frame = av.AudioFrame.from_ndarray(waveform.movedim(2, 1).reshape(1, -1).float().numpy(), format='flt', layout='mono' if waveform.shape[1] == 1 else 'stereo') + frame.sample_rate = audio_sample_rate + frame.pts = 0 + output.mux(audio_stream.encode(frame)) + # Flush encoder + output.mux(audio_stream.encode(None)) diff --git a/comfy_extras/nodes_latent.py b/comfy_extras/nodes_latent.py index 247d886a1..0f90cf60c 100644 --- a/comfy_extras/nodes_latent.py +++ b/comfy_extras/nodes_latent.py @@ -1,6 +1,7 @@ import comfy.utils import comfy_extras.nodes_post_processing import torch +import nodes def reshape_latent_to(target_shape, latent, repeat_batch=True): @@ -137,6 +138,41 @@ class LatentConcat: samples_out["samples"] = torch.cat(c, dim=dim) return (samples_out,) +class LatentCut: + @classmethod + def INPUT_TYPES(s): + return {"required": {"samples": ("LATENT",), + "dim": (["x", "y", "t"], ), + "index": ("INT", {"default": 0, "min": -nodes.MAX_RESOLUTION, "max": nodes.MAX_RESOLUTION, "step": 1}), + "amount": ("INT", {"default": 1, "min": 1, "max": nodes.MAX_RESOLUTION, "step": 1})}} + + RETURN_TYPES = ("LATENT",) + FUNCTION = "op" + + CATEGORY = "latent/advanced" + + def op(self, samples, dim, index, amount): + samples_out = samples.copy() + + s1 = samples["samples"] + + if "x" in dim: + dim = s1.ndim - 1 + elif "y" in dim: + dim = s1.ndim - 2 + elif "t" in dim: + dim = s1.ndim - 3 + + if index >= 0: + index = min(index, s1.shape[dim] - 1) + amount = min(s1.shape[dim] - index, amount) + else: + index = max(index, -s1.shape[dim]) + amount = min(-index, amount) + + samples_out["samples"] = torch.narrow(s1, dim, index, amount) + return (samples_out,) + class LatentBatch: @classmethod def INPUT_TYPES(s): @@ -312,6 +348,7 @@ NODE_CLASS_MAPPINGS = { "LatentMultiply": LatentMultiply, "LatentInterpolate": LatentInterpolate, "LatentConcat": LatentConcat, + "LatentCut": LatentCut, "LatentBatch": LatentBatch, "LatentBatchSeedBehavior": LatentBatchSeedBehavior, "LatentApplyOperation": LatentApplyOperation, diff --git a/comfy_extras/nodes_wan.py b/comfy_extras/nodes_wan.py index 2cbc93ceb..4f73369f5 100644 --- a/comfy_extras/nodes_wan.py +++ b/comfy_extras/nodes_wan.py @@ -139,16 +139,21 @@ class Wan22FunControlToVideo(io.ComfyNode): @classmethod def execute(cls, positive, negative, vae, width, height, length, batch_size, ref_image=None, start_image=None, control_video=None) -> io.NodeOutput: - latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device()) - concat_latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device()) - concat_latent = comfy.latent_formats.Wan21().process_out(concat_latent) + spacial_scale = vae.spacial_compression_encode() + latent_channels = vae.latent_channels + latent = torch.zeros([batch_size, latent_channels, ((length - 1) // 4) + 1, height // spacial_scale, width // spacial_scale], device=comfy.model_management.intermediate_device()) + concat_latent = torch.zeros([batch_size, latent_channels, ((length - 1) // 4) + 1, height // spacial_scale, width // spacial_scale], device=comfy.model_management.intermediate_device()) + if latent_channels == 48: + concat_latent = comfy.latent_formats.Wan22().process_out(concat_latent) + else: + concat_latent = comfy.latent_formats.Wan21().process_out(concat_latent) concat_latent = concat_latent.repeat(1, 2, 1, 1, 1) mask = torch.ones((1, 1, latent.shape[2] * 4, latent.shape[-2], latent.shape[-1])) if start_image is not None: start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1) concat_latent_image = vae.encode(start_image[:, :, :, :3]) - concat_latent[:,16:,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]] + concat_latent[:,latent_channels:,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]] mask[:, :, :start_image.shape[0] + 3] = 0.0 ref_latent = None @@ -159,11 +164,11 @@ class Wan22FunControlToVideo(io.ComfyNode): if control_video is not None: control_video = comfy.utils.common_upscale(control_video[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1) concat_latent_image = vae.encode(control_video[:, :, :, :3]) - concat_latent[:,:16,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]] + concat_latent[:,:latent_channels,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]] mask = mask.view(1, mask.shape[2] // 4, 4, mask.shape[3], mask.shape[4]).transpose(1, 2) - positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent, "concat_mask": mask, "concat_mask_index": 16}) - negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent, "concat_mask": mask, "concat_mask_index": 16}) + positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent, "concat_mask": mask, "concat_mask_index": latent_channels}) + negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent, "concat_mask": mask, "concat_mask_index": latent_channels}) if ref_latent is not None: positive = node_helpers.conditioning_set_values(positive, {"reference_latents": [ref_latent]}, append=True) @@ -201,7 +206,8 @@ class WanFirstLastFrameToVideo(io.ComfyNode): @classmethod def execute(cls, positive, negative, vae, width, height, length, batch_size, start_image=None, end_image=None, clip_vision_start_image=None, clip_vision_end_image=None) -> io.NodeOutput: - latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device()) + spacial_scale = vae.spacial_compression_encode() + latent = torch.zeros([batch_size, vae.latent_channels, ((length - 1) // 4) + 1, height // spacial_scale, width // spacial_scale], device=comfy.model_management.intermediate_device()) if start_image is not None: start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1) if end_image is not None: diff --git a/comfyui_version.py b/comfyui_version.py index 7034953fd..36777e285 100644 --- a/comfyui_version.py +++ b/comfyui_version.py @@ -1,3 +1,3 @@ # This file is automatically generated by the build process when version is # updated in pyproject.toml. -__version__ = "0.3.54" +__version__ = "0.3.55" diff --git a/pyproject.toml b/pyproject.toml index 9f9ac1e21..04514b4a8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "ComfyUI" -version = "0.3.54" +version = "0.3.55" readme = "README.md" license = { file = "LICENSE" } requires-python = ">=3.9" diff --git a/requirements.txt b/requirements.txt index 97074c124..32afcb286 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,5 @@ comfyui-frontend-package==1.25.11 -comfyui-workflow-templates==0.1.68 +comfyui-workflow-templates==0.1.70 comfyui-embedded-docs==0.2.6 comfyui_manager==4.0.1b2 torch