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b8c861f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | from dataclasses import dataclass
import numpy as np
import PIL.Image
import torch
from diffusers.utils import BaseOutput, get_logger
logger = get_logger(__name__)
@dataclass
class CosmosPipelineOutput(BaseOutput):
r"""
Output class for Cosmos any-to-world/video pipelines.
Args:
frames (`torch.Tensor`, `np.ndarray`, or list[list[PIL.Image.Image]]):
list of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing
denoised PIL image sequences of length `num_frames.` It can also be a NumPy array or Torch tensor of shape
`(batch_size, num_frames, channels, height, width)`.
"""
frames: torch.Tensor
@dataclass
class CosmosImagePipelineOutput(BaseOutput):
"""
Output class for Cosmos any-to-image pipelines.
Args:
images (`list[PIL.Image.Image]` or `np.ndarray`)
list of denoised PIL images of length `batch_size` or numpy array of shape `(batch_size, height, width,
num_channels)`. PIL images or numpy array present the denoised images of the diffusion pipeline.
"""
images: list[PIL.Image.Image] | np.ndarray
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