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| # Copyright 2025 HiDream-ai Team and The HuggingFace Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from dataclasses import dataclass | |
| import numpy as np | |
| import PIL.Image | |
| from ...utils import BaseOutput | |
| class HiDreamImagePipelineOutput(BaseOutput): | |
| """ | |
| Output class for HiDreamImage 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 | |