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Zero
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from dataclasses import dataclass
from typing import List, Union
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 CogView3 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: Union[List[PIL.Image.Image], np.ndarray]
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