Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
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mmsegmentation | mmsegmentation-master/docs/zh_cn/useful_tools.md | ## 常用工具
除了训练和测试的脚本，我们在 `tools/` 文件夹路径下还提供许多有用的工具。
### 计算参数量（params）和计算量（ FLOPs） (试验性)
我们基于 [flops-counter.pytorch](https://github.com/sovrasov/flops-counter.pytorch)
提供了一个用于计算给定模型参数量和计算量的脚本。
```shell
python tools/get_flops.py ${CONFIG_FILE} [--shape ${INPUT_SHAPE}]
```
您将得到如下的结果：
```none
=========================... | 11,291 | 27.443325 | 272 | md |
mmsegmentation | mmsegmentation-master/docs/zh_cn/_static/css/readthedocs.css | .header-logo {
background-image: url("../images/mmsegmentation.png");
background-size: 201px 40px;
height: 40px;
width: 201px;
}
| 145 | 19.857143 | 58 | css |
mmsegmentation | mmsegmentation-master/docs/zh_cn/tutorials/config.md | # 教程 1: 学习配置文件
我们整合了模块和继承设计到我们的配置里，这便于做很多实验。如果您想查看配置文件，您可以运行 `python tools/print_config.py /PATH/TO/CONFIG` 去查看完整的配置文件。您还可以传递参数
`--cfg-options xxx.yyy=zzz` 去查看更新的配置。
## 配置文件的结构
在 `config/_base_` 文件夹下面有4种基本组件类型： 数据集(dataset)，模型(model)，训练策略(schedule)和运行时的默认设置(default runtime)。许多方法都可以方便地通过组合这些组件进行实现。
这样，像 DeepLabV3, PS... | 15,785 | 40.21671 | 170 | md |
mmsegmentation | mmsegmentation-master/docs/zh_cn/tutorials/customize_datasets.md | # 教程 2: 自定义数据集
## 通过重新组织数据来定制数据集
最简单的方法是将您的数据集进行转化，并组织成文件夹的形式。
如下的文件结构就是一个例子。
```none
├── data
│ ├── my_dataset
│ │ ├── img_dir
│ │ │ ├── train
│ │ │ │ ├── xxx{img_suffix}
│ │ │ │ ├── yyy{img_suffix}
│ │ │ │ ├── zzz{img_suffix}
│ │ │ ├── val
│ │ ├── ann_dir
│ │ │ ... | 4,353 | 19.733333 | 109 | md |
mmsegmentation | mmsegmentation-master/docs/zh_cn/tutorials/customize_models.md | # 教程 4: 自定义模型
## 自定义优化器 (optimizer)
假设您想增加一个新的叫 `MyOptimizer` 的优化器，它的参数分别为 `a`, `b`, 和 `c`。
您首先需要在一个文件里实现这个新的优化器，例如在 `mmseg/core/optimizer/my_optimizer.py` 里面：
```python
from mmcv.runner import OPTIMIZERS
from torch.optim import Optimizer
@OPTIMIZERS.register_module
class MyOptimizer(Optimizer):
def __init__(... | 5,245 | 21.709957 | 158 | md |
mmsegmentation | mmsegmentation-master/docs/zh_cn/tutorials/customize_runtime.md | # 教程 6: 自定义运行设定
## 自定义优化设定
### 自定义 PyTorch 支持的优化器
我们已经支持 PyTorch 自带的所有优化器，唯一需要修改的地方是在配置文件里的 `optimizer` 域里面。
例如，如果您想使用 `ADAM` (注意如下操作可能会让模型表现下降)，可以使用如下修改：
```python
optimizer = dict(type='Adam', lr=0.0003, weight_decay=0.0001)
```
为了修改模型的学习率，使用者仅需要修改配置文件里 optimizer 的 `lr` 即可。
使用者可以参照 PyTorch 的 [API 文档](https://pyt... | 6,734 | 26.048193 | 302 | md |
mmsegmentation | mmsegmentation-master/docs/zh_cn/tutorials/data_pipeline.md | # 教程 3: 自定义数据流程
## 数据流程的设计
按照通常的惯例，我们使用 `Dataset` 和 `DataLoader` 做多线程的数据加载。`Dataset` 返回一个数据内容的字典，里面对应于模型前传方法的各个参数。
因为在语义分割中，输入的图像数据具有不同的大小，我们在 MMCV 里引入一个新的 `DataContainer` 类别去帮助收集和分发不同大小的输入数据。
更多细节，请查看[这里](https://github.com/open-mmlab/mmcv/blob/master/mmcv/parallel/data_container.py) 。
数据的准备流程和数据集是解耦的。通常一个数据集定义了如何... | 3,811 | 21.826347 | 123 | md |
mmsegmentation | mmsegmentation-master/docs/zh_cn/tutorials/training_tricks.md | # 教程 5: 训练技巧
MMSegmentation 支持如下训练技巧：
## 主干网络和解码头组件使用不同的学习率 (Learning Rate, LR)
在语义分割里，一些方法会让解码头组件的学习率大于主干网络的学习率，这样可以获得更好的表现或更快的收敛。
在 MMSegmentation 里面，您也可以在配置文件里添加如下行来让解码头组件的学习率是主干组件的10倍。
```python
optimizer=dict(
paramwise_cfg = dict(
custom_keys={
'head': dict(lr_mult=10.)}))
```
通过这种修改... | 3,274 | 33.114583 | 204 | md |
mmsegmentation | mmsegmentation-master/mmseg/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import mmcv
from packaging.version import parse
from .version import __version__, version_info
MMCV_MIN = '1.3.13'
MMCV_MAX = '1.8.0'
def digit_version(version_str: str, length: int = 4):
"""Convert a version string into a tuple of integers.
... | 1,933 | 29.698413 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/version.py | # Copyright (c) Open-MMLab. All rights reserved.
__version__ = '0.30.0'
def parse_version_info(version_str):
version_info = []
for x in version_str.split('.'):
if x.isdigit():
version_info.append(int(x))
elif x.find('rc') != -1:
patch_version = x.split('rc')
... | 502 | 25.473684 | 56 | py |
mmsegmentation | mmsegmentation-master/mmseg/apis/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .inference import inference_segmentor, init_segmentor, show_result_pyplot
from .test import multi_gpu_test, single_gpu_test
from .train import (get_root_logger, init_random_seed, set_random_seed,
train_segmentor)
__all__ = [
'get_root_logger'... | 489 | 39.833333 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/apis/inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import matplotlib.pyplot as plt
import mmcv
import torch
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmseg.datasets.pipelines import Compose
from mmseg.models import build_segmentor
def init_segmentor(config, checkpoint=None,... | 4,967 | 33.027397 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/apis/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
import mmcv
import numpy as np
import torch
from mmcv.engine import collect_results_cpu, collect_results_gpu
from mmcv.image import tensor2imgs
from mmcv.runner import get_dist_info
def np2tmp(array, temp_file_name=... | 9,246 | 38.517094 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/apis/train.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import random
import warnings
import mmcv
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import (HOOKS, DistSamplerSeedHook, EpochBasedRunner,
build_runner, get_dist_info)
from mmcv.utils import build_... | 7,455 | 35.54902 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import (OPTIMIZER_BUILDERS, build_optimizer,
build_optimizer_constructor)
from .evaluation import * # noqa: F401, F403
from .hook import * # noqa: F401, F403
from .optimizers import * # noqa: F401, F403
from .seg import * # noqa: F4... | 460 | 34.461538 | 74 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from mmcv.runner.optimizer import OPTIMIZER_BUILDERS as MMCV_OPTIMIZER_BUILDERS
from mmcv.utils import Registry, build_from_cfg
OPTIMIZER_BUILDERS = Registry(
'optimizer builder', parent=MMCV_OPTIMIZER_BUILDERS)
def build_optimizer_constructor(cfg):
... | 1,218 | 34.852941 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/evaluation/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .class_names import get_classes, get_palette
from .eval_hooks import DistEvalHook, EvalHook
from .metrics import (eval_metrics, intersect_and_union, mean_dice,
mean_fscore, mean_iou, pre_eval_to_metrics)
__all__ = [
'EvalHook', 'DistEvalHoo... | 465 | 37.833333 | 72 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/evaluation/class_names.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
def cityscapes_classes():
"""Cityscapes class names for external use."""
return [
'road', 'sidewalk', 'building', 'wall', 'fence', 'pole',
'traffic light', 'traffic sign', 'vegetation', 'terrain', 'sky',
'person', 'rider', 'ca... | 15,375 | 45.878049 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/evaluation/eval_hooks.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
import torch.distributed as dist
from mmcv.runner import DistEvalHook as _DistEvalHook
from mmcv.runner import EvalHook as _EvalHook
from torch.nn.modules.batchnorm import _BatchNorm
class EvalHook(_EvalHook):
"""Single GPU Eva... | 4,900 | 35.849624 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/evaluation/metrics.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections import OrderedDict
import mmcv
import numpy as np
import torch
def f_score(precision, recall, beta=1):
"""calculate the f-score value.
Args:
precision (float | torch.Tensor): The precision value.
recall (float | torch.Tensor): ... | 16,105 | 39.56927 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/hook/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .wandblogger_hook import MMSegWandbHook
__all__ = ['MMSegWandbHook']
| 123 | 23.8 | 47 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/hook/wandblogger_hook.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
from mmcv.runner import HOOKS
from mmcv.runner.dist_utils import master_only
from mmcv.runner.hooks.checkpoint import CheckpointHook
from mmcv.runner.hooks.logger.wandb import WandbLoggerHook
from mmseg.core import Di... | 15,592 | 41.02965 | 83 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/optimizers/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .layer_decay_optimizer_constructor import (
LayerDecayOptimizerConstructor, LearningRateDecayOptimizerConstructor)
__all__ = [
'LearningRateDecayOptimizerConstructor', 'LayerDecayOptimizerConstructor'
]
| 265 | 32.25 | 77 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/optimizers/layer_decay_optimizer_constructor.py | # Copyright (c) OpenMMLab. All rights reserved.
import json
import warnings
from mmcv.runner import DefaultOptimizerConstructor, get_dist_info
from mmseg.utils import get_root_logger
from ..builder import OPTIMIZER_BUILDERS
def get_layer_id_for_convnext(var_name, max_layer_id):
"""Get the layer id to set the di... | 8,082 | 37.490476 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/seg/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import build_pixel_sampler
from .sampler import BasePixelSampler, OHEMPixelSampler
__all__ = ['build_pixel_sampler', 'BasePixelSampler', 'OHEMPixelSampler']
| 220 | 35.833333 | 73 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/seg/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.utils import Registry, build_from_cfg
PIXEL_SAMPLERS = Registry('pixel sampler')
def build_pixel_sampler(cfg, **default_args):
"""Build pixel sampler for segmentation map."""
return build_from_cfg(cfg, PIXEL_SAMPLERS, default_args)
| 301 | 29.2 | 60 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/seg/sampler/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .base_pixel_sampler import BasePixelSampler
from .ohem_pixel_sampler import OHEMPixelSampler
__all__ = ['BasePixelSampler', 'OHEMPixelSampler']
| 198 | 32.166667 | 50 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/seg/sampler/base_pixel_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
class BasePixelSampler(metaclass=ABCMeta):
"""Base class of pixel sampler."""
def __init__(self, **kwargs):
pass
@abstractmethod
def sample(self, seg_logit, seg_label):
"""Placeholder for sample f... | 332 | 22.785714 | 47 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/seg/sampler/ohem_pixel_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import PIXEL_SAMPLERS
from .base_pixel_sampler import BasePixelSampler
@PIXEL_SAMPLERS.register_module()
class OHEMPixelSampler(BasePixelSampler):
"""Online Hard Example Mining Sample... | 3,539 | 40.162791 | 103 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/utils/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .dist_util import check_dist_init, sync_random_seed
from .misc import add_prefix
__all__ = ['add_prefix', 'check_dist_init', 'sync_random_seed']
| 199 | 32.333333 | 63 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/utils/dist_util.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info
def check_dist_init():
return dist.is_available() and dist.is_initialized()
def sync_random_seed(seed=None, device='cuda'):
"""Make sure different ranks shar... | 1,533 | 31.638298 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/core/utils/misc.py | # Copyright (c) OpenMMLab. All rights reserved.
def add_prefix(inputs, prefix):
"""Add prefix for dict.
Args:
inputs (dict): The input dict with str keys.
prefix (str): The prefix to add.
Returns:
dict: The dict with keys updated with ``prefix``.
"""
outputs = dict()
... | 419 | 21.105263 | 57 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .ade import ADE20KDataset
from .builder import DATASETS, PIPELINES, build_dataloader, build_dataset
from .chase_db1 import ChaseDB1Dataset
from .cityscapes import CityscapesDataset
from .coco_stuff import COCOStuffDataset
from .custom import CustomDataset
from .dark_... | 1,596 | 43.361111 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/ade.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class ADE20KDataset(CustomDataset):
"""ADE20K dataset.
In segmentation map annotation for AD... | 8,358 | 48.755952 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import platform
import random
from functools import partial
import numpy as np
import torch
from mmcv.parallel import collate
from mmcv.runner import get_dist_info
from mmcv.utils import Registry, build_from_cfg, digit_version
from torch.utils.data import Dat... | 7,135 | 35.22335 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/chase_db1.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class ChaseDB1Dataset(CustomDataset):
"""Chase_db1 dataset.
In segmentation map annotation for Chase_db1, 0 stands for background,
which is included in 2 categories... | 820 | 28.321429 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/cityscapes.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
from mmcv.utils import print_log
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class CityscapesDataset(CustomDataset):
"""Cityscapes dataset.
... | 8,469 | 38.395349 | 96 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/coco_stuff.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class COCOStuffDataset(CustomDataset):
"""COCO-Stuff dataset.
In segmentation map annotation for COCO-Stuff, Train-IDs of the 10k version
are from 1 to 171, where 0 ... | 6,158 | 63.831579 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/custom.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
from collections import OrderedDict
import mmcv
import numpy as np
from mmcv.utils import print_log
from prettytable import PrettyTable
from torch.utils.data import Dataset
from mmseg.core import eval_metrics, intersect_and_union, p... | 18,798 | 37.365306 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/dark_zurich.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .cityscapes import CityscapesDataset
@DATASETS.register_module()
class DarkZurichDataset(CityscapesDataset):
"""DarkZurichDataset dataset."""
def __init__(self, **kwargs):
super().__init__(
img_suffix='_rgb... | 406 | 26.133333 | 51 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/dataset_wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
import bisect
import collections
import copy
from itertools import chain
import mmcv
import numpy as np
from mmcv.utils import build_from_cfg, print_log
from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .builder import DATASETS, PIPELINES
from .c... | 10,339 | 36.194245 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/drive.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class DRIVEDataset(CustomDataset):
"""DRIVE dataset.
In segmentation map annotation for DRIVE, 0 stands for background, which is
included in 2 categories. ``reduce_... | 810 | 27.964286 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/face.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class FaceOccludedDataset(CustomDataset):
"""Face Occluded dataset.
Args:
split (str): Split txt file for Pascal VOC.
"""
CLASSES... | 623 | 25 | 76 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/hrf.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class HRFDataset(CustomDataset):
"""HRF dataset.
In segmentation map annotation for HRF, 0 stands for background, which is
included in 2 categories. ``reduce_zero_l... | 786 | 27.107143 | 77 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/imagenets.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
from PIL import Image
from mmseg.core import intersect_and_union
from mmseg.datasets.pipelines import LoadAnnotations, LoadImageFromFile
from .builder import DATASETS, PIPELINES
from .custom import CustomDataset
@PI... | 45,305 | 44.080597 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/isaid.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
from mmcv.utils import print_log
from ..utils import get_root_logger
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class iSAIDDataset(CustomDataset):
""" iSAID: A Large-scale Dataset for Instance Segmentati... | 3,283 | 38.566265 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/isprs.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class ISPRSDataset(CustomDataset):
"""ISPRS dataset.
In segmentation map annotation for LoveDA, 0 is the ignore index.
``reduce_zero_label`` should be set to True. T... | 827 | 30.846154 | 74 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/loveda.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class LoveDADataset(CustomDataset):
"""LoveDA dataset.
In segmentation map annotation for Lo... | 3,349 | 35.021505 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/night_driving.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .cityscapes import CityscapesDataset
@DATASETS.register_module()
class NightDrivingDataset(CityscapesDataset):
"""NightDrivingDataset dataset."""
def __init__(self, **kwargs):
super().__init__(
img_suffix='... | 419 | 27 | 57 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pascal_context.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class PascalContextDataset(CustomDataset):
"""PascalContext dataset.
In segmentation map annotation for PascalContext, 0 stands for background,
which is included in... | 5,239 | 49.384615 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/potsdam.py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class PotsdamDataset(CustomDataset):
"""ISPRS Potsdam dataset.
In segmentation map annotation for Potsdam dataset, 0 is the ignore index.
``reduce_zero_label`` shoul... | 848 | 31.653846 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/stare.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class STAREDataset(CustomDataset):
"""STARE dataset.
In segmentation map annotation for STARE, 0 stands for background, which is
included in 2... | 809 | 26.931034 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/voc.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class PascalVOCDataset(CustomDataset):
"""Pascal VOC dataset.
Args:
split (str): Split txt file for Pascal VOC.
"""
CLASSES = ('b... | 1,178 | 37.032258 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .compose import Compose
from .formatting import (Collect, ImageToTensor, ToDataContainer, ToTensor,
Transpose, to_tensor)
from .loading import LoadAnnotations, LoadImageFromFile
from .test_time_aug import MultiScaleFlipAug
from .transforms im... | 966 | 47.35 | 75 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/compose.py | # Copyright (c) OpenMMLab. All rights reserved.
import collections
from mmcv.utils import build_from_cfg
from ..builder import PIPELINES
@PIPELINES.register_module()
class Compose(object):
"""Compose multiple transforms sequentially.
Args:
transforms (Sequence[dict | callable]): Sequence of transfo... | 1,512 | 27.54717 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/formating.py | # Copyright (c) OpenMMLab. All rights reserved.
# flake8: noqa
import warnings
from .formatting import *
warnings.warn('DeprecationWarning: mmseg.datasets.pipelines.formating will be '
'deprecated in 2021, please replace it with '
'mmseg.datasets.pipelines.formatting.')
| 301 | 29.2 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/formatting.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections.abc import Sequence
import mmcv
import numpy as np
import torch
from mmcv.parallel import DataContainer as DC
from ..builder import PIPELINES
def to_tensor(data):
"""Convert objects of various python types to :obj:`torch.Tensor`.
Supported ty... | 9,290 | 31.037931 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/loading.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
from ..builder import PIPELINES
@PIPELINES.register_module()
class LoadImageFromFile(object):
"""Load an image from file.
Required keys are "img_prefix" and "img_info" (a dict that must contain the
key ... | 6,171 | 37.81761 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/test_time_aug.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import mmcv
from ..builder import PIPELINES
from .compose import Compose
@PIPELINES.register_module()
class MultiScaleFlipAug(object):
"""Test-time augmentation with multiple scales and flipping.
An example configuration is as followed:
.... | 5,591 | 38.104895 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/pipelines/transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import inspect
import cv2
import mmcv
import numpy as np
from mmcv.utils import deprecated_api_warning, is_tuple_of
from numpy import random
from ..builder import PIPELINES
try:
import albumentations
from albumentations import Compose
except ImportE... | 53,629 | 35.041667 | 99 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/samplers/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .distributed_sampler import DistributedSampler
__all__ = ['DistributedSampler']
| 134 | 26 | 51 | py |
mmsegmentation | mmsegmentation-master/mmseg/datasets/samplers/distributed_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
from __future__ import division
from typing import Iterator, Optional
import torch
from torch.utils.data import Dataset
from torch.utils.data import DistributedSampler as _DistributedSampler
from mmseg.core.utils import sync_random_seed
from mmseg.utils import get_devic... | 2,975 | 39.216216 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .backbones import * # noqa: F401,F403
from .builder import (BACKBONES, HEADS, LOSSES, SEGMENTORS, build_backbone,
build_head, build_loss, build_segmentor)
from .decode_heads import * # noqa: F401,F403
from .losses import * # noqa: F401,F403
f... | 537 | 37.428571 | 75 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from mmcv.cnn import MODELS as MMCV_MODELS
from mmcv.cnn.bricks.registry import ATTENTION as MMCV_ATTENTION
from mmcv.utils import Registry
MODELS = Registry('models', parent=MMCV_MODELS)
ATTENTION = Registry('attention', parent=MMCV_ATTENTION)
BACKBONE... | 1,335 | 25.72 | 71 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .beit import BEiT
from .bisenetv1 import BiSeNetV1
from .bisenetv2 import BiSeNetV2
from .cgnet import CGNet
from .erfnet import ERFNet
from .fast_scnn import FastSCNN
from .hrnet import HRNet
from .icnet import ICNet
from .mae import MAE
from .mit import MixVisionTr... | 1,104 | 33.53125 | 73 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/beit.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import build_norm_layer
from mmcv.cnn.bricks.drop import build_dropout
from mmcv.cnn.utils.weight_init import (constant_init, kaiming_init,
... | 22,986 | 40.048214 | 128 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/bisenetv1.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from mmseg.ops import resize
from ..builder import BACKBONES, build_backbone
class SpatialPath(BaseModule):
"""Spatial Path to preserve the spatial size of the ori... | 12,006 | 35.057057 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/bisenetv2.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule,
build_activation_layer, build_norm_layer)
from mmcv.runner import BaseModule
from mmseg.ops import resize
from ..builder import BACKBONES
class Deta... | 23,042 | 35.987159 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/cgnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import ConvModule, build_conv_layer, build_norm_layer
from mmcv.runner import BaseModule
from mmcv.utils.parrots_wrapper import _BatchNorm
from ..builder import BACKBONE... | 13,412 | 34.959786 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/erfnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import build_activation_layer, build_conv_layer, build_norm_layer
from mmcv.runner import BaseModule
from mmseg.ops import resize
from ..builder import BACKBONES
class DownsamplerBlock(BaseModule):
"""Downsampler blo... | 13,068 | 38.60303 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/fast_scnn.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.runner import BaseModule
from mmseg.models.decode_heads.psp_head import PPM
from mmseg.ops import resize
from ..builder import BACKBONES
from ..utils import Inverte... | 15,660 | 37.197561 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/hrnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.runner import BaseModule, ModuleList, Sequential
from mmcv.utils.parrots_wrapper import _BatchNorm
from mmseg.ops import Upsample, resize
from ..builder import BACKBO... | 25,112 | 38.055988 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/icnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from mmseg.ops import resize
from ..builder import BACKBONES, build_backbone
from ..decode_heads.psp_head import PPM
@BACKBONES.register_module()
class ICNet(BaseModul... | 5,887 | 34.257485 | 76 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/mae.py | # Copyright (c) OpenMMLab. All rights reserved.import math
import math
import torch
import torch.nn as nn
from mmcv.cnn.utils.weight_init import (constant_init, kaiming_init,
trunc_normal_)
from mmcv.runner import ModuleList, _load_checkpoint
from torch.nn.modules.batchnorm impo... | 10,647 | 39.641221 | 128 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/mit.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import Conv2d, build_activation_layer, build_norm_layer
from mmcv.cnn.bricks.drop import build_dropout
from mmcv.cnn.bricks.transformer import MultiheadAttent... | 17,527 | 37.864745 | 89 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/mobilenet_v2.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from torch.nn.modules.batchnorm import _BatchNorm
from ..builder import BACKBONES
from ..utils import InvertedResidual, make_divisible
@BACKBONES.register_module()... | 7,640 | 37.590909 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/mobilenet_v3.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import mmcv
from mmcv.cnn import ConvModule
from mmcv.cnn.bricks import Conv2dAdaptivePadding
from mmcv.runner import BaseModule
from torch.nn.modules.batchnorm import _BatchNorm
from ..builder import BACKBONES
from ..utils import InvertedResidualV3 as I... | 10,845 | 39.470149 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/mscan.py | # Copyright (c) OpenMMLab. All rights reserved.
# Originally from https://github.com/visual-attention-network/segnext
# Licensed under the Apache License, Version 2.0 (the "License")
import math
import warnings
import torch
import torch.nn as nn
from mmcv.cnn import build_activation_layer, build_norm_layer
from mmcv.c... | 16,888 | 34.934043 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/resnest.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from ..utils import ResLayer
from .resnet import Bottleneck as _Bot... | 10,259 | 31.163009 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/resnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import build_conv_layer, build_norm_layer, build_plugin_layer
from mmcv.runner import BaseModule
from mmcv.utils.parrots_wrapper import _BatchNorm
from ..builder import BACKBONES
fro... | 25,804 | 35.090909 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/resnext.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from ..utils import ResLayer
from .resnet import Bottleneck as _Bottleneck
from .resnet import ResNet
class Bottleneck(_Bottleneck):
"""Bottleneck block for ResNeXt... | 5,321 | 34.245033 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/stdc.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Modified from https://github.com/MichaelFan01/STDC-Seg."""
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner.base_module import BaseModule, ModuleList, Sequential
from mmseg.ops import resize
from ..bui... | 16,158 | 37.200946 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/swin.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from collections import OrderedDict
from copy import deepcopy
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from mmcv.cnn import build_norm_layer
from mmcv.cnn.bricks.transformer import FFN, build_d... | 29,838 | 38.417437 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/timm_backbone.py | # Copyright (c) OpenMMLab. All rights reserved.
try:
import timm
except ImportError:
timm = None
from mmcv.cnn.bricks.registry import NORM_LAYERS
from mmcv.runner import BaseModule
from ..builder import BACKBONES
@BACKBONES.register_module()
class TIMMBackbone(BaseModule):
"""Wrapper to use backbones fr... | 1,948 | 29.453125 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/twins.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import build_norm_layer
from mmcv.cnn.bricks.drop import build_dropout
from mmcv.cnn.bricks.transformer import FFN
from mmcv.cnn.utils.weight_init import (constan... | 23,822 | 39.44652 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/unet.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import (UPSAMPLE_LAYERS, ConvModule, build_activation_layer,
build_norm_layer)
from mmcv.runner import BaseModule
from mmcv.utils.parrots_wrapper import _BatchNo... | 18,611 | 41.396355 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/backbones/vit.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import build_norm_layer
from mmcv.cnn.bricks.transformer import FFN, MultiheadAttention
from mmcv.cnn.utils.weight_init import (constant_init, kaiming_init,
... | 17,876 | 39.537415 | 128 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .ann_head import ANNHead
from .apc_head import APCHead
from .aspp_head import ASPPHead
from .cc_head import CCHead
from .da_head import DAHead
from .dm_head import DMHead
from .dnl_head import DNLHead
from .dpt_head import DPTHead
from .ema_head import EMAHead
from .... | 1,626 | 37.738095 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/ann_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from ..builder import HEADS
from ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .decode_head import BaseDecodeHead
class PPMConcat(nn.ModuleList):
"""Pyramid Pooling Module that only ... | 9,222 | 36.340081 | 77 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/apc_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class ACM(nn.Module):
"""Adaptive Context Module used in APCNet.
... | 5,580 | 33.88125 | 76 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/aspp_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class ASPPModule(nn.ModuleList):
"""Atrous Spatial Pyramid Pooling (ASPP) Module.
Args:
... | 3,947 | 31.097561 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/cascade_decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from .decode_head import BaseDecodeHead
class BaseCascadeDecodeHead(BaseDecodeHead, metaclass=ABCMeta):
"""Base class for cascade decode head used in
:class:`CascadeEncoderDecoder."""
def __init__(self, *args, **kwar... | 2,399 | 39.677966 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/cc_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..builder import HEADS
from .fcn_head import FCNHead
try:
from mmcv.ops import CrissCrossAttention
except ModuleNotFoundError:
CrissCrossAttention = None
@HEADS.register_module()
class CCHead(FCNHead):
"""CCNet: Criss-Cross Attention for ... | 1,331 | 29.272727 | 71 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/da_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
from mmcv.cnn import ConvModule, Scale
from torch import nn
from mmseg.core import add_prefix
from ..builder import HEADS
from ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .decode_head import BaseDecodeHead
... | 5,593 | 30.077778 | 77 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from abc import ABCMeta, abstractmethod
import torch
import torch.nn as nn
from mmcv.runner import BaseModule, auto_fp16, force_fp32
from mmseg.core import build_pixel_sampler
from mmseg.ops import resize
from ..builder import build_loss
from ..losses im... | 12,965 | 40.42492 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/dm_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, build_activation_layer, build_norm_layer
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class DCM(nn.Module):
"""Dynamic Convolutional Module us... | 5,032 | 34.443662 | 79 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/dnl_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import NonLocal2d
from torch import nn
from ..builder import HEADS
from .fcn_head import FCNHead
class DisentangledNonLocal2d(NonLocal2d):
"""Disentangled Non-Local Blocks.
Args:
temperature (float): Temperature to adjust att... | 4,856 | 34.195652 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/dpt_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, Linear, build_activation_layer
from mmcv.runner import BaseModule
from mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class ReassembleBlocks(Ba... | 10,399 | 34.254237 | 78 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/ema_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import torch
import torch.distributed as dist
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from ..builder import HEADS
from .decode_head import BaseDecodeHead
def reduce_mean(tensor):
"""Reduce mean when distrib... | 5,824 | 33.264706 | 77 | py |
mmsegmentation | mmsegmentation-master/mmseg/models/decode_heads/enc_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, build_norm_layer
from mmseg.ops import Encoding, resize
from ..builder import HEADS, build_loss
from .decode_head import BaseDecodeHead
class EncModule(nn.Module):
"... | 6,792 | 34.941799 | 78 | py |