56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from typing import Optional, Sequence
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import mmcv
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from mmengine import Config, FileClient
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from torch.utils.data import Dataset
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from mmdeploy.apis import build_task_processor
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class QuantizationImageDataset(Dataset):
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def __init__(
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self,
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path: str,
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deploy_cfg: Config,
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model_cfg: Config,
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file_client_args: Optional[dict] = None,
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extensions: Sequence[str] = ('.jpg', '.jpeg', '.png', '.ppm', '.bmp',
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'.pgm', '.tif'),
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):
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super().__init__()
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task_processor = build_task_processor(model_cfg, deploy_cfg, 'cpu')
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self.task_processor = task_processor
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self.samples = []
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self.extensions = tuple(set([i.lower() for i in extensions]))
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self.file_client = FileClient.infer_client(file_client_args, path)
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self.path = path
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assert self.file_client.isdir(path)
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files = list(
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self.file_client.list_dir_or_file(
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path,
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list_dir=False,
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list_file=True,
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recursive=False,
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))
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for file in files:
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if self.is_valid_file(self.file_client.join_path(file)):
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path = self.file_client.join_path(self.path, file)
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self.samples.append(path)
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def __len__(self):
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return len(self.samples)
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def __getitem__(self, index):
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sample = self.samples[index]
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image = mmcv.imread(sample)
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data = self.task_processor.create_input(image)
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return data[0]
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def is_valid_file(self, filename: str) -> bool:
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"""Check if a file is a valid sample."""
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return filename.lower().endswith(self.extensions)
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