repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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s2anet | s2anet-master/mmdet/models/backbones/__init__.py | from .hrnet import HRNet
from .resnet import ResNet, make_res_layer
from .resnext import ResNeXt
from .ssd_vgg import SSDVGG
__all__ = ['ResNet', 'make_res_layer', 'ResNeXt', 'SSDVGG', 'HRNet']
| 195 | 27 | 68 | py |
s2anet | s2anet-master/mmdet/models/mask_heads/grid_head.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import kaiming_init, normal_init
from ..builder import build_loss
from ..registry import HEADS
from ..utils import ConvModule
@HEADS.register_module
class GridHead(nn.Module):
def __init__(self,
... | 15,429 | 41.624309 | 79 | py |
s2anet | s2anet-master/mmdet/models/mask_heads/maskiou_head.py | import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import kaiming_init, normal_init
from torch.nn.modules.utils import _pair
from mmdet.core import force_fp32
from ..builder import build_loss
from ..registry import HEADS
@HEADS.register_module
class MaskIoUHead(nn.Module):
"""Mask IoU Head.
... | 7,418 | 37.842932 | 79 | py |
s2anet | s2anet-master/mmdet/models/mask_heads/__init__.py | from .fcn_mask_head import FCNMaskHead
from .fused_semantic_head import FusedSemanticHead
from .grid_head import GridHead
from .htc_mask_head import HTCMaskHead
from .maskiou_head import MaskIoUHead
__all__ = [
'FCNMaskHead', 'HTCMaskHead', 'FusedSemanticHead', 'GridHead',
'MaskIoUHead'
]
| 299 | 26.272727 | 66 | py |
s2anet | s2anet-master/mmdet/models/mask_heads/htc_mask_head.py | from ..registry import HEADS
from ..utils import ConvModule
from .fcn_mask_head import FCNMaskHead
@HEADS.register_module
class HTCMaskHead(FCNMaskHead):
def __init__(self, *args, **kwargs):
super(HTCMaskHead, self).__init__(*args, **kwargs)
self.conv_res = ConvModule(
self.conv_out_c... | 1,178 | 29.230769 | 78 | py |
s2anet | s2anet-master/mmdet/models/mask_heads/fcn_mask_head.py | import mmcv
import numpy as np
import pycocotools.mask as mask_util
import torch
import torch.nn as nn
from torch.nn.modules.utils import _pair
from mmdet.core import auto_fp16, force_fp32, mask_target
from ..builder import build_loss
from ..registry import HEADS
from ..utils import ConvModule
@HEADS.register_module... | 7,043 | 37.703297 | 79 | py |
s2anet | s2anet-master/mmdet/models/mask_heads/fused_semantic_head.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import kaiming_init
from mmdet.core import auto_fp16, force_fp32
from ..registry import HEADS
from ..utils import ConvModule
@HEADS.register_module
class FusedSemanticHead(nn.Module):
r"""Multi-level fused semantic segmentation head.
in_1 -... | 3,554 | 32.224299 | 79 | py |
s2anet | s2anet-master/mmdet/datasets/custom.py | import os.path as osp
import mmcv
import numpy as np
from torch.utils.data import Dataset
from .pipelines import Compose
from .registry import DATASETS
@DATASETS.register_module
class CustomDataset(Dataset):
"""Custom dataset for detection.
Annotation format:
[
{
'filename': 'a.jpg'... | 5,161 | 32.738562 | 76 | py |
s2anet | s2anet-master/mmdet/datasets/voc.py | from .registry import DATASETS
from .xml_style import XMLDataset
@DATASETS.register_module
class VOCDataset(XMLDataset):
CLASSES = ('aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car',
'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedpla... | 695 | 32.142857 | 78 | py |
s2anet | s2anet-master/mmdet/datasets/registry.py | from mmdet.utils import Registry
DATASETS = Registry('dataset')
PIPELINES = Registry('pipeline')
| 98 | 18.8 | 32 | py |
s2anet | s2anet-master/mmdet/datasets/cityscapes.py | from .coco import CocoDataset
from .registry import DATASETS
@DATASETS.register_module
class CityscapesDataset(CocoDataset):
CLASSES = ('person', 'rider', 'car', 'truck', 'bus', 'train', 'motorcycle',
'bicycle')
| 234 | 22.5 | 79 | py |
s2anet | s2anet-master/mmdet/datasets/hrsc2016.py | import os
import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
import numpy as np
from DOTA_devkit.hrsc2016_evaluation import voc_eval
from mmdet.core import norm_angle
from mmdet.core import rotated_box_to_poly_single
from .builder import DATASETS
from .xml_style import XMLDataset
@DATASETS.registe... | 6,810 | 35.228723 | 119 | py |
s2anet | s2anet-master/mmdet/datasets/dataset_wrappers.py | import bisect
import math
from collections import defaultdict
import numpy as np
from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .registry import DATASETS
@DATASETS.register_module
class ConcatDataset(_ConcatDataset):
"""A wrapper of concatenated dataset.
Same as :obj:`torch.utils... | 2,315 | 29.88 | 79 | py |
s2anet | s2anet-master/mmdet/datasets/xml_style.py | import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
import numpy as np
from .custom import CustomDataset
from .registry import DATASETS
@DATASETS.register_module
class XMLDataset(CustomDataset):
def __init__(self, min_size=None, **kwargs):
super(XMLDataset, self).__init__(**kwargs)
... | 3,070 | 34.298851 | 79 | py |
s2anet | s2anet-master/mmdet/datasets/__init__.py | from .builder import build_dataset
from .cityscapes import CityscapesDataset
from .coco import CocoDataset
from .custom import CustomDataset
from .dataset_wrappers import ConcatDataset, RepeatDataset
from .loader import DistributedGroupSampler, GroupSampler, build_dataloader
from .registry import DATASETS
from .voc imp... | 773 | 34.181818 | 75 | py |
s2anet | s2anet-master/mmdet/datasets/dota.py | import os.path as osp
import mmcv
import numpy as np
from DOTA_devkit.ResultMerge_multi_process import mergebypoly
from DOTA_devkit.dota_evaluation_task1 import voc_eval
from mmdet.core import rotated_box_to_poly_single
from .custom import CustomDataset
from .registry import DATASETS
@DATASETS.register_module
class... | 3,375 | 40.170732 | 119 | py |
s2anet | s2anet-master/mmdet/datasets/builder.py | import copy
from mmdet.utils import build_from_cfg
from .dataset_wrappers import ConcatDataset, RepeatDataset
from .registry import DATASETS
def _concat_dataset(cfg, default_args=None):
ann_files = cfg['ann_file']
img_prefixes = cfg.get('img_prefix', None)
seg_prefixes = cfg.get('seg_prefixes', None)
... | 1,457 | 33.714286 | 78 | py |
s2anet | s2anet-master/mmdet/datasets/coco.py | import numpy as np
from pycocotools.coco import COCO
from .custom import CustomDataset
from .registry import DATASETS
@DATASETS.register_module
class CocoDataset(CustomDataset):
CLASSES = ('person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus',
'train', 'truck', 'boat', 'traffic_light', 'fir... | 4,304 | 37.783784 | 79 | py |
s2anet | s2anet-master/mmdet/datasets/wider_face.py | import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
from .registry import DATASETS
from .xml_style import XMLDataset
@DATASETS.register_module
class WIDERFaceDataset(XMLDataset):
"""
Reader for the WIDER Face dataset in PASCAL VOC format.
Conversion scripts can be found in
https://g... | 1,301 | 29.27907 | 65 | py |
s2anet | s2anet-master/mmdet/datasets/loader/sampler.py | from __future__ import division
import math
import numpy as np
import torch
from mmcv.runner.utils import get_dist_info
from torch.utils.data import DistributedSampler as _DistributedSampler
from torch.utils.data import Sampler
class DistributedSampler(_DistributedSampler):
def __init__(self, dataset, num_repli... | 5,832 | 34.567073 | 78 | py |
s2anet | s2anet-master/mmdet/datasets/loader/build_loader.py | import platform
from functools import partial
from mmcv.parallel import collate
from mmcv.runner import get_dist_info
from torch.utils.data import DataLoader
from .sampler import DistributedGroupSampler, DistributedSampler, GroupSampler
if platform.system() != 'Windows':
# https://github.com/pytorch/pytorch/issu... | 1,559 | 30.836735 | 78 | py |
s2anet | s2anet-master/mmdet/datasets/loader/__init__.py | from .build_loader import build_dataloader
from .sampler import DistributedGroupSampler, GroupSampler
__all__ = ['GroupSampler', 'DistributedGroupSampler', 'build_dataloader']
| 177 | 34.6 | 73 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/test_aug.py | import mmcv
from ..registry import PIPELINES
from .compose import Compose
@PIPELINES.register_module
class MultiScaleFlipAug(object):
def __init__(self, transforms, img_scale, flip=False):
self.transforms = Compose(transforms)
self.img_scale = img_scale if isinstance(img_scale,
... | 1,312 | 32.666667 | 71 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/loading.py | import os.path as osp
import warnings
import mmcv
import numpy as np
import pycocotools.mask as maskUtils
from ..registry import PIPELINES
@PIPELINES.register_module
class LoadImageFromFile(object):
def __init__(self, to_float32=False):
self.to_float32 = to_float32
def __call__(self, results):
... | 5,246 | 33.519737 | 77 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/compose.py | import collections
from mmdet.utils import build_from_cfg
from ..registry import PIPELINES
@PIPELINES.register_module
class Compose(object):
def __init__(self, transforms):
assert isinstance(transforms, collections.abc.Sequence)
self.transforms = []
for transform in transforms:
... | 1,073 | 28.833333 | 71 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/formating.py | from collections.abc import Sequence
import mmcv
import numpy as np
import torch
from mmcv.parallel import DataContainer as DC
from ..registry import PIPELINES
def to_tensor(data):
"""Convert objects of various python types to :obj:`torch.Tensor`.
Supported types are: :class:`numpy.ndarray`, :class:`torch.... | 6,008 | 31.13369 | 93 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/__init__.py | from .compose import Compose
from .formating import (Collect, ImageToTensor, ToDataContainer, ToTensor,
Transpose, to_tensor)
from .loading import LoadAnnotations, LoadImageFromFile, LoadProposals
from .test_aug import MultiScaleFlipAug
from .transforms import (Albu, Expand, MinIoURandomCrop, No... | 1,071 | 50.047619 | 79 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/transforms_rotated.py | import random
import cv2
import numpy as np
from mmdet.core import poly_to_rotated_box_np, rotated_box_to_poly_np, norm_angle
from .transforms import RandomFlip, Resize
from ..registry import PIPELINES
@PIPELINES.register_module
class RotatedRandomFlip(RandomFlip):
def bbox_flip(self, bboxes, img_shape):
... | 5,635 | 33.365854 | 96 | py |
s2anet | s2anet-master/mmdet/datasets/pipelines/transforms.py | import inspect
import albumentations
import mmcv
import numpy as np
from albumentations import Compose
from imagecorruptions import corrupt
from numpy import random
from mmdet.core.evaluation.bbox_overlaps import bbox_overlaps
from ..registry import PIPELINES
@PIPELINES.register_module
class Resize(object):
"""... | 29,903 | 34.813174 | 79 | py |
s2anet | s2anet-master/mmdet/utils/registry.py | import inspect
import mmcv
class Registry(object):
def __init__(self, name):
self._name = name
self._module_dict = dict()
def __repr__(self):
format_str = self.__class__.__name__ + '(name={}, items={})'.format(
self._name, list(self._module_dict.keys()))
return f... | 2,304 | 28.935065 | 78 | py |
s2anet | s2anet-master/mmdet/utils/flops_counter.py | # Modified from flops-counter.pytorch by Vladislav Sovrasov
# original repo: https://github.com/sovrasov/flops-counter.pytorch
# MIT License
# Copyright (c) 2018 Vladislav Sovrasov
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (th... | 14,351 | 32.069124 | 79 | py |
s2anet | s2anet-master/mmdet/utils/__init__.py | from .flops_counter import get_model_complexity_info
from .registry import Registry, build_from_cfg
__all__ = ['Registry', 'build_from_cfg', 'get_model_complexity_info']
| 171 | 33.4 | 69 | py |
s2anet | s2anet-master/mmdet/ops/context_block.py | import torch
from mmcv.cnn import constant_init, kaiming_init
from torch import nn
def last_zero_init(m):
if isinstance(m, nn.Sequential):
constant_init(m[-1], val=0)
else:
constant_init(m, val=0)
class ContextBlock(nn.Module):
def __init__(self,
inplanes,
... | 3,766 | 34.87619 | 76 | py |
s2anet | s2anet-master/mmdet/ops/__init__.py | from .context_block import ContextBlock
from .dcn import (DeformConv, DeformConvPack, DeformRoIPooling,
DeformRoIPoolingPack, ModulatedDeformConv,
ModulatedDeformConvPack, ModulatedDeformRoIPoolingPack,
deform_conv, deform_roi_pooling, modulated_deform_conv)
from .m... | 1,217 | 45.846154 | 88 | py |
s2anet | s2anet-master/mmdet/ops/dcn/deform_pool.py | import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import deform_pool_cuda
class DeformRoIPoolingFunction(Function):
@staticmethod
def forward(ctx,
data,
... | 10,212 | 39.367589 | 79 | py |
s2anet | s2anet-master/mmdet/ops/dcn/deform_conv.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import deform_conv_cuda
class DeformConvFunction(Function):
@staticmethod
def forward(ct... | 13,344 | 36.591549 | 80 | py |
s2anet | s2anet-master/mmdet/ops/dcn/__init__.py | from .deform_conv import (DeformConv, DeformConvPack, ModulatedDeformConv,
ModulatedDeformConvPack, deform_conv,
modulated_deform_conv)
from .deform_pool import (DeformRoIPooling, DeformRoIPoolingPack,
ModulatedDeformRoIPoolingPack, deform_ro... | 582 | 43.846154 | 76 | py |
s2anet | s2anet-master/mmdet/ops/orn/__init__.py | from .modules.ORConv import ORConv2d
from .functions import rotation_invariant_encoding,RotationInvariantPooling
| 113 | 37 | 75 | py |
s2anet | s2anet-master/mmdet/ops/orn/functions/active_rotating_filter.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from .. import orn_cuda
#import _C
class _ActiveRotatingFilter(Function):
@s... | 2,736 | 27.510417 | 96 | py |
s2anet | s2anet-master/mmdet/ops/orn/functions/rotation_invariant_pooling.py | import torch
from torch import nn
from torch.nn import functional as F
class RotationInvariantPooling(nn.Module):
def __init__(self, nInputPlane, nOrientation=8):
super(RotationInvariantPooling, self).__init__()
self.nInputPlane = nInputPlane
self.nOrientation = nOrientation
hiddent_dim = int(n... | 940 | 26.676471 | 76 | py |
s2anet | s2anet-master/mmdet/ops/orn/functions/__init__.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from .active_rotating_filter import active_rotating_filter
from .active_rotating_filter import ActiveRotatingFilter
from .rotation_invariant_encoding import rotation_invariant_encoding
from .rotation_invariant_encoding import RotationI... | 551 | 60.333333 | 148 | py |
s2anet | s2anet-master/mmdet/ops/orn/functions/rotation_invariant_encoding.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from .. import orn_cuda
class _RotationInvariantEncoding(Function):
@staticme... | 1,900 | 31.775862 | 106 | py |
s2anet | s2anet-master/mmdet/ops/orn/modules/ORConv.py | from __future__ import absolute_import
import math
import torch
from torch.nn.parameter import Parameter
import torch.nn.functional as F
from torch.nn.modules import Conv2d
from torch.nn.modules.utils import _pair
from ..functions import active_rotating_filter
class ORConv2d(Conv2d):
def __init__(self, in_channels,... | 3,732 | 35.960396 | 121 | py |
s2anet | s2anet-master/mmdet/ops/orn/modules/__init__.py | from .ORConv import ORConv2d
#from .ORConv_v2 import ORConv2d_v2
#__all__ = ['ORConv2d', 'ORConv2d_v2']
__all__ = ['ORConv2d']
| 128 | 20.5 | 38 | py |
s2anet | s2anet-master/mmdet/ops/box_iou_rotated/__init__.py | from .box_iou_rotated_cuda import box_iou_rotated
__all__ = ['box_iou_rotated']
| 81 | 19.5 | 49 | py |
s2anet | s2anet-master/mmdet/ops/ml_nms_rotated/__init__.py | from .ml_nms_rotated_cuda import ml_nms_rotated
__all__=['ml_nms_rotated']
| 76 | 18.25 | 47 | py |
s2anet | s2anet-master/mmdet/ops/masked_conv/masked_conv.py | import math
import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import masked_conv2d_cuda
class MaskedConv2dFunction(Function):
@staticmethod
def forward(ctx, features, mask, weight, b... | 3,375 | 36.511111 | 79 | py |
s2anet | s2anet-master/mmdet/ops/masked_conv/__init__.py | from .masked_conv import MaskedConv2d, masked_conv2d
__all__ = ['masked_conv2d', 'MaskedConv2d']
| 98 | 23.75 | 52 | py |
s2anet | s2anet-master/mmdet/ops/sigmoid_focal_loss/sigmoid_focal_loss.py | import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from . import sigmoid_focal_loss_cuda
class SigmoidFocalLossFunction(Function):
@staticmethod
def forward(ctx, input, target, gamma=2.0, alpha=0.25):
ctx.save_for_backward(input, target)... | 1,637 | 28.781818 | 77 | py |
s2anet | s2anet-master/mmdet/ops/sigmoid_focal_loss/__init__.py | from .sigmoid_focal_loss import SigmoidFocalLoss, sigmoid_focal_loss
__all__ = ['SigmoidFocalLoss', 'sigmoid_focal_loss']
| 123 | 30 | 68 | py |
s2anet | s2anet-master/mmdet/ops/roi_align/roi_align.py | import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import roi_align_cuda
class RoIAlignFunction(Function):
@staticmethod
def forward(ctx, features, rois, out_size, spatial_scale, sample_num=0):
... | 3,068 | 33.875 | 79 | py |
s2anet | s2anet-master/mmdet/ops/roi_align/gradcheck.py | import os.path as osp
import sys
import numpy as np
import torch
from torch.autograd import gradcheck
sys.path.append(osp.abspath(osp.join(__file__, '../../')))
from roi_align import RoIAlign # noqa: E402, isort:skip
feat_size = 15
spatial_scale = 1.0 / 8
img_size = feat_size / spatial_scale
num_imgs = 2
num_rois =... | 879 | 27.387097 | 76 | py |
s2anet | s2anet-master/mmdet/ops/roi_align/__init__.py | from .roi_align import RoIAlign, roi_align
__all__ = ['roi_align', 'RoIAlign']
| 80 | 19.25 | 42 | py |
s2anet | s2anet-master/mmdet/ops/box_iou_rotated_diff/box_iou_rotated_diff.py | """
Differentiable IoU calculation for rotated boxes
Most of the code is adapted from https://github.com/lilanxiao/Rotated_IoU
"""
import torch
from .box_intersection_2d import oriented_box_intersection_2d
def rotated_box_to_poly(rotated_boxes: torch.Tensor):
""" Transform rotated boxes to polygons
Args:
... | 2,207 | 32.454545 | 102 | py |
s2anet | s2anet-master/mmdet/ops/box_iou_rotated_diff/box_intersection_2d.py | '''
torch implementation of 2d oriented box intersection
author: lanxiao li
Modified by csuhan:
Remove the `batch` indice in a tensor.
This setting is more suitable for mmdet.
'''
import torch
from .sort_vertices_cuda import sort_vertices_forward
EPSILON = 1e-8
def get_intersection_points(polys1: torch.Te... | 6,963 | 35.460733 | 103 | py |
s2anet | s2anet-master/mmdet/ops/box_iou_rotated_diff/__init__.py | from .box_iou_rotated_diff import box_iou_rotated_differentiable
__all__ = ['box_iou_rotated_differentiable'] | 110 | 36 | 64 | py |
s2anet | s2anet-master/mmdet/ops/nms_rotated/__init__.py | from . import nms_rotated_cuda
__all__ = ['nms_rotated']
def nms_rotated(dets, iou_thr):
if dets.shape[0] == 0:
return dets
keep_inds = nms_rotated_cuda.nms_rotated(dets[:, :5], dets[:, 5], iou_thr)
dets = dets[keep_inds, :]
return dets, keep_inds
| 275 | 22 | 78 | py |
s2anet | s2anet-master/mmdet/ops/roi_pool/roi_pool.py | import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import roi_pool_cuda
class RoIPoolFunction(Function):
@staticmethod
def forward(ctx, features, rois, out_size, spatial_scale):
... | 2,544 | 32.486842 | 78 | py |
s2anet | s2anet-master/mmdet/ops/roi_pool/gradcheck.py | import os.path as osp
import sys
import torch
from torch.autograd import gradcheck
sys.path.append(osp.abspath(osp.join(__file__, '../../')))
from roi_pool import RoIPool # noqa: E402, isort:skip
feat = torch.randn(4, 16, 15, 15, requires_grad=True).cuda()
rois = torch.Tensor([[0, 0, 0, 50, 50], [0, 10, 30, 43, 55]... | 513 | 29.235294 | 66 | py |
s2anet | s2anet-master/mmdet/ops/roi_pool/__init__.py | from .roi_pool import RoIPool, roi_pool
__all__ = ['roi_pool', 'RoIPool']
| 75 | 18 | 39 | py |
s2anet | s2anet-master/mmdet/ops/roi_align_rotated/__init__.py | from .roi_align_rotated import RoIAlignRotated
__all__ = ['RoIAlignRotated']
| 78 | 18.75 | 46 | py |
s2anet | s2anet-master/mmdet/ops/roi_align_rotated/roi_align_rotated.py | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from .roi_align_rotated_cuda import roi_align_rotated_forward, roi_align_rotated_backward
class _RO... | 3,281 | 33.914894 | 90 | py |
s2anet | s2anet-master/mmdet/ops/nms/nms_wrapper.py | import numpy as np
import torch
from . import nms_cpu, nms_cuda
from .soft_nms_cpu import soft_nms_cpu
def nms(dets, iou_thr, device_id=None):
"""Dispatch to either CPU or GPU NMS implementations.
The input can be either a torch tensor or numpy array. GPU NMS will be used
if the input is a gpu tensor or... | 2,580 | 31.670886 | 79 | py |
s2anet | s2anet-master/mmdet/ops/nms/__init__.py | from .nms_wrapper import nms, soft_nms
__all__ = ['nms', 'soft_nms']
| 70 | 16.75 | 38 | py |
Simple-Vanilla-LSTM | Simple-Vanilla-LSTM-master/VanillaLSTM.py | import numpy as np
class RecurrentNeuralNetwork:
def __init__ (self, xs, ys, rl, eo, lr):
#initial input
self.x = np.zeros(xs)
#input size
self.xs = xs
#expected output
self.y = np.zeros(ys)
#output size
self.ys = ys
#weight matrix for ... | 10,289 | 37.977273 | 140 | py |
xaesa | xaesa-master/modified_widgets.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 2 15:02:40 2022
@author: kalinko
"""
from init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
if QTVer == 5:
from PyQt5 import QtWidgets as QtGui
from PyQt5 import QtCore
class QLineEditScroll(QtGui.QLineEdit):
... | 1,917 | 32.649123 | 73 | py |
xaesa | xaesa-master/xaesa_viewer.py | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 6 11:20:43 2018
@author: akali
"""
from init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as N... | 5,904 | 32.174157 | 104 | py |
xaesa | xaesa-master/xaesa_xes_class.py | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 2 15:07:33 2018
@author: akali
"""
from numpy import concatenate, logical_and, polyfit, where, zeros, sum
from scipy.integrate import simps
from scipy.interpolate import Rbf
class xaesa_xes_class():
def __init__(self):
self.name = ""
... | 3,276 | 29.915094 | 108 | py |
xaesa | xaesa-master/xaesa_fit.py | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 15:55:28 2016
@author: sasha
"""
import os
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToo... | 38,370 | 40.392665 | 142 | py |
xaesa | xaesa-master/xaesaGUI.py | # -*- coding: utf-8 -*-
#"""
#Created on Fri Oct 7 12:25:31 2016
#
#@author: sasha
#"""
XAESA_VERSION = "0.07"
GUI_SETTINGS_ID = "XAESA" + XAESA_VERSION
import sys
from sys import exit, argv, version
from os import path, getcwd, getpid
import matplotlib.pyplot as plt
from matplotlib import __version__ as mpl_versio... | 178,553 | 43.16374 | 174 | py |
xaesa | xaesa-master/xaesa_settings.py | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 6 11:20:43 2018
@author: akali
"""
from init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
if QTVer == 5:
from PyQt5 import QtWidgets as QtGui
from PyQt5 import QtCore
class xaesa_settings(QtGui.QWidget):
def __init__(self, parent=Non... | 2,976 | 32.449438 | 76 | py |
xaesa | xaesa-master/xaesa_lincombination.py | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 20 11:07:03 2016
@author: sasha
"""
import os
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToo... | 12,547 | 34.148459 | 105 | py |
xaesa | xaesa-master/interpolation_k2.py | # -*- coding: utf-8 -*-
"""
Created on Fri Nov 4 07:20:37 2022
@author: A.Kuzmin
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate
from scipy.interpolate import make_lsq_spline
from scipy.interpolate import InterpolatedUnivariateSpline
#, BSpline
#from scipy.interpolate import ... | 3,137 | 19.376623 | 94 | py |
xaesa | xaesa-master/xaesa_deglitch.py | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 20 11:07:03 2016
@author: sasha
"""
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as... | 12,510 | 34.242254 | 135 | py |
xaesa | xaesa-master/xaesa_exafs_class.py | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 13 11:55:12 2018
@author: akali
"""
import sys
import os
from numpy import arange, argmin, argmax, argsort, asarray, concatenate, copy, delete, \
gradient, log, logical_and, multiply, newaxis, pi, power, \
sin, cos, sqrt, sum, whe... | 24,396 | 32.93185 | 113 | py |
xaesa | xaesa-master/compare.py | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 20 11:07:03 2016
@author: sasha
"""
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as... | 7,064 | 32.966346 | 108 | py |
xaesa | xaesa-master/xaesa_pca.py | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 20 11:07:03 2016
@author: sasha
"""
import os
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToo... | 17,208 | 34.926931 | 117 | py |
xaesa | xaesa-master/xalglib.py | ###########################################################################
# ALGLIB 3.13.0 (source code generated 2017-12-29)
# Copyright (c) Sergey Bochkanov (ALGLIB project).
#
# >>> SOURCE LICENSE >>>
# This software is a non-commercial edition of ALGLIB package, which is
# licensed under ALGLIB Personal and A... | 1,703,616 | 41.946884 | 412 | py |
xaesa | xaesa-master/init.py | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 15:56:46 2016
@author: sasha
"""
QTVer = 0
def qtVersionToUse():
try:
from PyQt4 import QtGui
QTVer = 4
except:
QTVer = 0
if QTVer == 0:
try:
from PyQt5 import QtWidgets as QtGui
QTVer = 5
... | 416 | 15.038462 | 48 | py |
xaesa | xaesa-master/tooltiptexts.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 2 15:46:03 2022
@author: kalinko
"""
xas_es = 'Spectrum start energy.\n' + \
'INFO: Use mouse scroll to change value.\n' + \
'CTRL and SHIFT decrease and increase base change 10 times.'
xas_e3 = 'Spectrum end energy.\... | 454 | 29.333333 | 71 | py |
xaesa | xaesa-master/xaesa_ft.py | #import numpy as np
from numpy import sqrt, zeros, pi, arctan, asarray, arange, delete, sum, multiply, sin, cos
def FT(k, exafs, rmin, rmax, dr):
con = sqrt(2 / pi)
nn = len(k)
rx = zeros(int((rmax - rmin) / dr), float)
exafs_re = zeros(nn, float)
# exafs_im = zeros(nn, float)
# tr... | 4,173 | 21.934066 | 91 | py |
xaesa | xaesa-master/xaesa_constants_formulas.py | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 13 14:49:33 2018
@author: AKalinko
"""
from numpy import asarray, exp, zeros
#constants
me = 9.10938215* 10**-31 # kg
h = 6.626070040* 10**-34 #Js = m^2 kg / s
hev = 4.135667516 * 10**-15 #eV s
c = 299792458 #m/s
hbar = 1.054571800*10**-34
def victoreen(x, a, b):
... | 617 | 21.071429 | 63 | py |
xaesa | xaesa-master/xaesa_rxes.py | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 6 11:20:43 2018
@author: akali
"""
from init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as N... | 12,920 | 35.397183 | 134 | py |
xaesa | xaesa-master/xaesa_rdf.py | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 15:55:28 2016
@author: sasha
"""
import os
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToo... | 28,810 | 36.127577 | 148 | py |
lingua-py | lingua-py-main/scripts/benchmark.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 5,912 | 55.314286 | 198 | py |
lingua-py | lingua-py-main/scripts/memory_profiler.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 2,797 | 33.54321 | 114 | py |
lingua-py | lingua-py-main/scripts/accuracy_reporter.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 27,800 | 39.001439 | 108 | py |
lingua-py | lingua-py-main/scripts/accuracy_table_writer.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 6,510 | 34.005376 | 168 | py |
lingua-py | lingua-py-main/scripts/accuracy_plot_drawer.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 6,253 | 33.362637 | 88 | py |
lingua-py | lingua-py-main/tests/test_ngram.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 1,004 | 30.40625 | 76 | py |
lingua-py | lingua-py-main/tests/test_builder.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 4,984 | 34.607143 | 81 | py |
lingua-py | lingua-py-main/tests/test_language.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 7,939 | 28.191176 | 76 | py |
lingua-py | lingua-py-main/tests/__init__.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 608 | 39.6 | 76 | py |
lingua-py | lingua-py-main/tests/test_model.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 22,964 | 24.236264 | 88 | py |
lingua-py | lingua-py-main/tests/test_writer.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 19,704 | 33.329268 | 174 | py |
lingua-py | lingua-py-main/tests/test_detector.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 167,876 | 129.440559 | 126,405 | py |
lingua-py | lingua-py-main/lingua/writer.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 11,667 | 37.76412 | 93 | py |
lingua-py | lingua-py-main/lingua/isocode.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 10,920 | 20.798403 | 76 | py |
lingua-py | lingua-py-main/lingua/_constant.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 7,191 | 31.107143 | 88 | py |
lingua-py | lingua-py-main/lingua/_ngram.py | #
# Copyright © 2022-present Peter M. Stahl [email protected]
#
# 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 applicabl... | 1,424 | 28.6875 | 77 | py |
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