repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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RSP | RSP-main/Semantic Segmentation/tools/model_converters/twins2mmseg.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
from collections import OrderedDict
import mmcv
import torch
from mmcv.runner import CheckpointLoader
def convert_twins(args, ckpt):
new_ckpt = OrderedDict()
for k, v in list(ckpt.items()):
new_v = v
if k.... | 2,752 | 30.284091 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tools/model_converters/vit2mmseg.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
from collections import OrderedDict
import mmcv
import torch
from mmcv.runner import CheckpointLoader
def convert_vit(ckpt):
new_ckpt = OrderedDict()
for k, v in ckpt.items():
if k.startswith('head'):
... | 2,117 | 28.830986 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tools/model_converters/swin2mmseg.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
from collections import OrderedDict
import mmcv
import torch
from mmcv.runner import CheckpointLoader
def convert_swin(ckpt):
new_ckpt = OrderedDict()
def correct_unfold_reduction_order(x):
out_channel, in_channel ... | 2,728 | 30.011364 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tools/model_converters/mit2mmseg.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
from collections import OrderedDict
import mmcv
import torch
from mmcv.runner import CheckpointLoader
def convert_mit(ckpt):
new_ckpt = OrderedDict()
# Process the concat between q linear weights and kv linear weights
f... | 3,069 | 35.987952 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tools/model_converters/stdc2mmseg.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
import mmcv
import torch
from mmcv.runner import CheckpointLoader
def convert_stdc(ckpt, stdc_type):
new_state_dict = {}
if stdc_type == 'STDC1':
stage_lst = ['0', '1', '2.0', '2.1', '3.0', '3.1', '4.0', '4.1']
... | 2,307 | 31.055556 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tools/model_converters/vitjax2mmseg.py | import argparse
import os.path as osp
import mmcv
import numpy as np
import torch
def vit_jax_to_torch(jax_weights, num_layer=12):
torch_weights = dict()
# patch embedding
conv_filters = jax_weights['embedding/kernel']
conv_filters = conv_filters.permute(3, 2, 0, 1)
torch_weights['patch_embed.pr... | 4,627 | 36.626016 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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,... | 4,630 | 32.80292 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/apis/train.py | # Copyright (c) OpenMMLab. All rights reserved.
import random
import warnings
import mmcv
import numpy as np
import torch
import torch.distributed as dist
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import HOOKS, build_optimizer, build_runner, get_dist_info
from mmcv.utils impo... | 6,298 | 34.994286 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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... | 4,776 | 36.031008 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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): ... | 16,077 | 39.60101 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/necks/ic_neck.py | import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from mmseg.ops import resize
from ..builder import NECKS
class CascadeFeatureFusion(BaseModule):
"""Cascade Feature Fusion Unit in ICNet.
Args:
low_channels (int): The number of input channels for
... | 5,312 | 34.898649 | 76 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/necks/multilevel_neck.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule, xavier_init
from mmseg.ops import resize
from ..builder import NECKS
@NECKS.register_module()
class MultiLevelNeck(nn.Module):
"""MultiLevelNeck.
A neck structure connect vit backbone and decoder_heads.
... | 2,716 | 33.392405 | 76 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/necks/mla_neck.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule, build_norm_layer
from ..builder import NECKS
class MLAModule(nn.Module):
def __init__(self,
in_channels=[1024, 1024, 1024, 1024],
out_channels=256,
norm_cfg=N... | 3,873 | 31.554622 | 78 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/necks/jpu.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.ops import resize
from ..builder import NECKS
@NECKS.register_module()
class JPU(BaseModule):
"""FastFCN: Rethinking Dilat... | 5,079 | 37.484848 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/necks/fpn.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, auto_fp16
from mmseg.ops import resize
from ..builder import NECKS
@NECKS.register_module()
class FPN(BaseModule):
"""Feature Pyramid Network.
... | 9,238 | 42.172897 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/fcn_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 .decode_head import BaseDecodeHead
@HEADS.register_module()
class FCNHead(BaseDecodeHead):
"""Fully Convolution Networks for Semantic Segmentation.
This head is... | 2,845 | 33.289157 | 77 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/sep_aspp_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmseg.ops import resize
from ..builder import HEADS
from .aspp_head import ASPPHead, ASPPModule
class DepthwiseSeparableASPPModule(ASPPModule):
"""Atrous Spatial P... | 3,535 | 33.330097 | 76 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/isa_head.py | import math
import torch
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from ..builder import HEADS
from ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .decode_head import BaseDecodeHead
class SelfAttentionBlock(_SelfAttentionBlock):
"""Self-Attention Module.
Args:
i... | 4,929 | 33.475524 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/ocr_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 ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .cascade_decode_head import BaseCascadeDecodeHea... | 4,327 | 32.550388 | 76 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/stdc_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
from ..builder import HEADS
from .fcn_head import FCNHead
@HEADS.register_module()
class STDCHead(FCNHead):
"""This head is the implementation of `Rethinking BiSeNet For Real-time
Semantic Segmentation <https://arxiv... | 3,555 | 40.348837 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/psp_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 PPM(nn.ModuleList):
"""Pooling Pyramid Module used in PSPNet.
Args:
pool_scales (t... | 3,404 | 31.740385 | 78 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/setr_up_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule, build_norm_layer
from mmseg.ops import Upsample
from ..builder import HEADS
from .decode_head import BaseDecodeHead
@HEADS.register_module()
class SETRUPHead(BaseDecodeHead):
"""Naive upsampling head and Progre... | 2,962 | 35.134146 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/setr_mla_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmseg.ops import Upsample
from ..builder import HEADS
from .decode_head import BaseDecodeHead
@HEADS.register_module()
class SETRMLAHead(BaseDecodeHead):
"""Multi level feature aggretation head... | 2,177 | 33.03125 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/dpt_head.py | 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(BaseModule):
"""ViTPostProcessBlock, process c... | 10,351 | 34.210884 | 78 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/fpn_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmseg.ops import Upsample, resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
@HEADS.register_module()
class FPNHead(BaseDecodeHead):
"""Panoptic Feature Pyramid N... | 2,437 | 33.828571 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/nl_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import NonLocal2d
from ..builder import HEADS
from .fcn_head import FCNHead
@HEADS.register_module()
class NLHead(FCNHead):
"""Non-local Neural Networks.
This head is the implementation of `NLNet
<https://arxiv.org/abs/1711.07971... | 1,605 | 30.490196 | 78 | py |
RSP | RSP-main/Semantic Segmentation/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... | 4,619 | 33.736842 | 78 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
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 import accuracy
... | 10,632 | 38.973684 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/lraspp_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv import is_tuple_of
from mmcv.cnn import ConvModule
from mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
@HEADS.register_module()
class LRASPPHead(BaseDecodeHead):
"""Lite R-ASP... | 3,086 | 32.554348 | 77 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/uper_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
from .psp_head import PPM
@HEADS.register_module()
class UPerHead(BaseDecodeHead):
"""Unified Percept... | 4,037 | 30.546875 | 72 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/segmenter_mask_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 build_norm_layer
from mmcv.cnn.utils.weight_init import (constant_init, trunc_normal_,
trunc_normal_init)
from mmcv.runner import ModuleList
fr... | 4,895 | 35.537313 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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:
... | 3,467 | 30.816514 | 76 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/psa_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
try:
from mmcv.ops import PSAMask
except ModuleNotFoundError:
PSAM... | 7,532 | 37.045455 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/gc_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import ContextBlock
from ..builder import HEADS
from .fcn_head import FCNHead
@HEADS.register_module()
class GCHead(FCNHead):
"""GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond.
This head is the implementation o... | 1,639 | 32.469388 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/segformer_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmseg.models.builder import HEADS
from mmseg.models.decode_heads.decode_head import BaseDecodeHead
from mmseg.ops import resize
@HEADS.register_module()
class SegformerHead(BaseDecodeHead):
"""... | 2,044 | 29.522388 | 78 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/decode_heads/point_head.py | # Copyright (c) OpenMMLab. All rights reserved.
# Modified from https://github.com/facebookresearch/detectron2/tree/master/projects/PointRend/point_head/point_head.py # noqa
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.ops import point_sample
from mmseg.models.builder import HEADS
fro... | 15,026 | 41.092437 | 126 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/utils/embed.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import Sequence
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.runner.base_module import BaseModule
from mmcv.utils import to_2tuple
class AdaptivePadding(nn.Module):
"... | 12,216 | 35.909366 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/utils/se_layer.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch.nn as nn
from mmcv.cnn import ConvModule
from .make_divisible import make_divisible
class SELayer(nn.Module):
"""Squeeze-and-Excitation Module.
Args:
channels (int): The input (and output) channels of the SE layer.
rati... | 2,151 | 35.474576 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/utils/res_layer.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.runner import Sequential
from torch import nn as nn
class ResLayer(Sequential):
"""ResLayer to build ResNet style backbone.
Args:
block (nn.Module): block used to build ResLayer.
... | 3,395 | 34.010309 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/utils/self_attention_block.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import ConvModule, constant_init
from torch import nn as nn
from torch.nn import functional as F
class SelfAttentionBlock(nn.Module):
"""General self-attention block/non-local block.
Please refer to https://arxiv.org/abs/1706.03762 fo... | 6,173 | 37.347826 | 78 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/utils/up_conv_block.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, build_upsample_layer
class UpConvBlock(nn.Module):
"""Upsample convolution block in decoder for UNet.
This upsample convolution block consists of one upsample module
followed by one convolu... | 4,016 | 38 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/utils/inverted_residual.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import ConvModule
from torch import nn
from torch.utils import checkpoint as cp
from .se_layer import SELayer
class InvertedResidual(nn.Module):
"""InvertedResidual block for MobileNetV2.
Args:
in_channels (int): The input channels of the... | 7,162 | 32.471963 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/segmentors/base.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import mmcv
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import BaseModule, auto_fp16
class BaseSegmentor(BaseModule, metaclass=ABCMeta):
... | 11,332 | 38.487805 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/segmentors/cascade_encoder_decoder.py | # Copyright (c) OpenMMLab. All rights reserved.
from torch import nn
from mmseg.core import add_prefix
from mmseg.ops import resize
from .. import builder
from ..builder import SEGMENTORS
from .encoder_decoder import EncoderDecoder
@SEGMENTORS.register_module()
class CascadeEncoderDecoder(EncoderDecoder):
"""Cas... | 3,134 | 35.882353 | 78 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/segmentors/encoder_decoder.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmseg.core import add_prefix
from mmseg.ops import resize
from .. import builder
from ..builder import SEGMENTORS
from .base import BaseSegmentor
@SEGMENTORS.register_module()
class EncoderDecoder(... | 10,889 | 37.076923 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/losses/dice_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Modified from https://github.com/LikeLy-Journey/SegmenTron/blob/master/
segmentron/solver/loss.py (Apache-2.0 License)"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weighted_loss... | 4,928 | 34.717391 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/losses/lovasz_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Modified from https://github.com/bermanmaxim/LovaszSoftmax/blob/master/pytor
ch/lovasz_losses.py Lovasz-Softmax and Jaccard hinge loss in PyTorch Maxim
Berman 2018 ESAT-PSI KU Leuven (MIT License)"""
import mmcv
import torch
import torch.nn as nn
import torch.nn.funct... | 12,223 | 36.728395 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/losses/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import functools
import mmcv
import numpy as np
import torch.nn.functional as F
def get_class_weight(class_weight):
"""Get class weight for loss function.
Args:
class_weight (list[float] | str | None): If class_weight is a str,
take it as a... | 3,738 | 29.398374 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/losses/accuracy.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
def accuracy(pred, target, topk=1, thresh=None):
"""Calculate accuracy according to the prediction and target.
Args:
pred (torch.Tensor): The model prediction, shape (N, num_class, ...)
target (torch.Tensor): The target of ... | 3,018 | 36.7375 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/losses/focal_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
# Modified from https://github.com/open-mmlab/mmdetection
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.ops import sigmoid_focal_loss as _sigmoid_focal_loss
from ..builder import LOSSES
from .utils import weight_reduce_loss
# This method ... | 15,001 | 44.737805 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/losses/cross_entropy_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weight_reduce_loss
def cross_entropy(pred,
label,
weight=None,
class_weight=None,
... | 8,262 | 36.559091 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/mit.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
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 MultiheadAttention
from mmcv.cnn.utils.weight_init ... | 16,814 | 37.923611 | 89 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/icnet.py | 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(BaseModule):
"""ICNet for Real-Time Semantic Segmenta... | 5,839 | 34.180723 | 76 | py |
RSP | RSP-main/Semantic Segmentation/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... | 29,743 | 38.291942 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/swin_transformer.py | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu, Yutong Lin, Yixuan Wei
# --------------------------------------------------------
import warnings
from collections import OrderedDi... | 28,039 | 38.60452 | 123 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/vit.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
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,
... | 16,979 | 40.113801 | 128 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/our_resnet.py | import math
import torch
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
import os
import torchvision
torchvision.models.resnext50_32x4d()
from mmcv.cnn import (constant_init, kaiming_init)
#from ..backbones.custom_load import load_checkpoint
from mmseg.utils import get_root_logger
#from mmcv.utils.r... | 17,308 | 38.974596 | 112 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/twins.py | 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 (constant_init, normal_init,
... | 23,774 | 39.433673 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/custom_load/checkpoint.py | # Copyright (c) Open-MMLab. All rights reserved.
import io
import os
import os.path as osp
import pkgutil
import time
import warnings
from collections import OrderedDict
from importlib import import_module
from tempfile import TemporaryDirectory
import torch
import torchvision
from torch.optim import Optimizer
from to... | 21,203 | 37.906422 | 117 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/base_model.py | from functools import partial
import torch
import torch.nn as nn
from timm.models.layers import trunc_normal_
import numpy as np
from torch.nn.functional import instance_norm
from torch.nn.modules.batchnorm import BatchNorm2d
from .NormalCell import NormalCell
from .ReductionCell import ReductionCell
#from ..custom_lo... | 16,934 | 45.270492 | 199 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/swin.py | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu
# --------------------------------------------------------
import torch
import torch.nn as nn
import torch.utils.checkpoint as chec... | 24,644 | 40.559865 | 142 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/ReductionCell.py | import math
from numpy.core.fromnumeric import resize, shape
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
import numpy as np
from .token_transformer import Token_transformer
from .token_performer import Token_performer
from .SELayer... | 11,032 | 46.761905 | 179 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/NormalCell.py | # Copyright (c) [2012]-[2021] Shanghai Yitu Technology Co., Ltd.
#
# This source code is licensed under the Clear BSD License
# LICENSE file in the root directory of this file
# All rights reserved.
"""
Borrow from timm(https://github.com/rwightman/pytorch-image-models)
"""
import torch
import torch.nn as nn
import num... | 11,944 | 43.240741 | 177 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/token_performer.py | """
Take Performer as T2T Transformer
"""
import math
import torch
import torch.nn as nn
import numpy as np
class Token_performer(nn.Module):
def __init__(self, dim, in_dim, head_cnt=1, kernel_ratio=0.5, dp1=0.1, dp2 = 0.1, gamma=False, init_values=1e-4):
super().__init__()
self.head_dim = in_dim ... | 3,147 | 35.604651 | 128 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/SELayer.py | import torch
import torch.nn as nn
class SELayer(nn.Module):
def __init__(self, channel, reduction=16):
super(SELayer, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool1d(1)
self.fc = nn.Sequential(
nn.Linear(channel, channel // reduction, bias=False),
nn.ReLU(inpl... | 726 | 32.045455 | 65 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/token_transformer.py | # Copyright (c) [2012]-[2021] Shanghai Yitu Technology Co., Ltd.
#
# This source code is licensed under the Clear BSD License
# LICENSE file in the root directory of this file
# All rights reserved.
"""
Take the standard Transformer as T2T Transformer
"""
import torch
import torch.nn as nn
from timm.models.layers impor... | 2,703 | 39.358209 | 165 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/models/backbones/ViTAE_Window_NoShift/models.py | # Copyright (c) [2012]-[2021] Shanghai Yitu Technology Co., Ltd.
#
# This source code is licensed under the Clear BSD License
# LICENSE file in the root directory of this file
# All rights reserved.
"""
T2T-ViT
"""
from math import gamma
import torch
import torch.nn as nn
from timm.models.helpers import load_pretraine... | 1,657 | 38.47619 | 269 | py |
RSP | RSP-main/Semantic Segmentation/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... | 17,677 | 36.85439 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/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... | 6,868 | 35.343915 | 79 | py |
RSP | RSP-main/Semantic Segmentation/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 |
RSP | RSP-main/Semantic Segmentation/mmseg/utils/set_env.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import platform
import cv2
import torch.multiprocessing as mp
from ..utils import get_root_logger
def setup_multi_processes(cfg):
"""Setup multi-processing environment variables."""
logger = get_root_logger()
# set multi-process start method
... | 2,309 | 40.25 | 116 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/ops/wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
import torch.nn.functional as F
def resize(input,
size=None,
scale_factor=None,
mode='nearest',
align_corners=None,
warning=True):
if warning:
if size is not None a... | 1,875 | 35.076923 | 79 | py |
RSP | RSP-main/Semantic Segmentation/mmseg/ops/encoding.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn
from torch.nn import functional as F
class Encoding(nn.Module):
"""Encoding Layer: a learnable residual encoder.
Input is of shape (batch_size, channels, height, width).
Output is of shape (batch_size, num_codes, channels)... | 2,836 | 36.328947 | 78 | py |
RSP | RSP-main/Semantic Segmentation/tests/test_config.py | # Copyright (c) OpenMMLab. All rights reserved.
import glob
import os
from os.path import dirname, exists, isdir, join, relpath
from mmcv import Config
from torch import nn
from mmseg.models import build_segmentor
def _get_config_directory():
"""Find the predefined segmentor config directory."""
try:
... | 6,067 | 36.45679 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tests/test_eval_hook.py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import tempfile
from unittest.mock import MagicMock, patch
import mmcv.runner
import pytest
import torch
import torch.nn as nn
from mmcv.runner import obj_from_dict
from torch.utils.data import DataLoader, Dataset
from mmseg.apis import single_gpu_test
fr... | 7,237 | 34.307317 | 79 | py |
RSP | RSP-main/Semantic Segmentation/tests/test_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmseg.core import OHEMPixelSampler
from mmseg.models.decode_heads import FCNHead
def _context_for_ohem():
return FCNHead(in_channels=32, channels=16, num_classes=19)
def _context_for_ohem_multiple_loss():
return FCNHead(
... | 2,957 | 36.443038 | 77 | py |
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