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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WSAD | WSAD-main/experiments/baseline/DevNet/run.py | # -*- coding: utf-8 -*-
"""
@author: Guansong Pang
The algorithm was implemented using Python 3.6.6, Keras 2.2.2 and TensorFlow 1.10.1.
More details can be found in our KDD19 paper.
Guansong Pang, Chunhua Shen, and Anton van den Hengel. 2019.
Deep Anomaly Detection with Deviation Networks.
In The 25th ACM SIGKDDConfere... | 10,292 | 41.709544 | 127 | py |
WSAD | WSAD-main/experiments/baseline/PReNet/fit.py | import torch
from torch.autograd import Variable
from baseline.PReNet.utils import sampler_pairs
def fit(X_train_tensor, y_train, model, optimizer, epochs, batch_num, batch_size,
s_a_a, s_a_u, s_u_u, device=None):
# epochs
for epoch in range(epochs):
# generate the batch samples
X_trai... | 1,189 | 37.387097 | 109 | py |
WSAD | WSAD-main/experiments/baseline/PReNet/utils.py | import numpy as np
from tqdm import tqdm
import torch
from myutils import Utils
utils = Utils()
'''
from the original paper, when implement stratified random sampling
batch / 2 is from the (u,u) pair, batch / 4 is from the (a,a) pair and batch / 2 is from the (a,u) pair
where u is the unlabeled data and a is the lab... | 2,779 | 35.103896 | 106 | py |
WSAD | WSAD-main/experiments/baseline/PReNet/model.py | import torch
from torch import nn
class prenet(nn.Module):
def __init__(self, input_size, act_fun):
super(prenet, self).__init__()
self.feature = nn.Sequential(
nn.Linear(input_size, 20),
act_fun
)
self.reg = nn.Linear(40, 1)
#the input vector of prene... | 679 | 26.2 | 65 | py |
WSAD | WSAD-main/experiments/baseline/PReNet/run.py | import torch
from torch import nn
import numpy as np
from myutils import Utils
from baseline.PReNet.model import prenet
from baseline.PReNet.fit import fit
'''
The unofficial implement (with PyTorch) of the PReNet model in the paper "Deep Weakly-supervised Anomaly Detection"
The default hyper-parameter is the same as... | 2,840 | 30.921348 | 121 | py |
WSAD | WSAD-main/experiments/baseline/REPEN/model.py | # -*- coding: utf-8 -*-
import numpy as np
import os
import warnings;
warnings.simplefilter("ignore")
from sklearn.neighbors import KDTree
from sklearn.utils.random import sample_without_replacement
from keras import backend as K
from keras.models import Model
from keras.layers import Input, Dense, Layer
from keras.... | 12,318 | 42.376761 | 109 | py |
WSAD | WSAD-main/experiments/baseline/FEAWAD/run.py | # -*- coding: utf-8 -*-
"""
@author：Xucheng Song
The algorithm was implemented using Python 3.6.12, Keras 2.3.1 and TensorFlow 1.13.1 based on the code (https://github.com/GuansongPang/deviation-network).
The major contributions are summarized as follows.
This code adds a feature encoder to encode the input data and u... | 18,210 | 47.692513 | 155 | py |
compas_vol | compas_vol-main/docs/conf.py | # flake8: noqa
# -*- coding: utf-8 -*-
# If your documentation needs a minimal Sphinx version, state it here.
#
# needs_sphinx = "1.0"
import sys
import os
import inspect
import importlib
import sphinx_compas_theme
from sphinx.ext.napoleon.docstring import NumpyDocstring
sys.path.insert(0, os.path.join(os.path.dirn... | 4,603 | 24.72067 | 90 | py |
MuSe2021 | MuSe2021-main/main.py | import argparse
import os
import sys
import torch
import numpy
import random
from datetime import datetime
from dateutil import tz
from torch.nn import CrossEntropyLoss
import config
from utils import Logger, seed_worker
from train import train_model
from eval import evaluate
from model import Model
from loss import ... | 10,238 | 49.688119 | 123 | py |
MuSe2021 | MuSe2021-main/late_fusion.py | import argparse
import os
import glob
import sys
import torch
import numpy as np
import random
import pandas as pd
from datetime import datetime
from dateutil import tz
from torch.nn import CrossEntropyLoss
import config
from loss import CCCLoss
from utils import Logger
from train import train_model
from eval import e... | 11,544 | 45.552419 | 123 | py |
MuSe2021 | MuSe2021-main/loss.py | import torch
import torch.nn as nn
class CCCLoss(nn.Module):
def __init__(self):
super(CCCLoss, self).__init__()
def forward(self, y_pred, y_true, seq_lens=None):
if seq_lens is not None:
mask = torch.ones_like(y_true, device=y_true.device)
for i, seq_len in enumerate(... | 2,130 | 41.62 | 113 | py |
MuSe2021 | MuSe2021-main/utils.py | import sys
import torch
import numpy
import random
class Logger(object):
def __init__(self, log_file="log_file.log"):
self.terminal = sys.stdout
self.file = open(log_file, "w")
def write(self, message):
self.terminal.write(message)
self.file.write(message)
self.flush()... | 512 | 19.52 | 48 | py |
MuSe2021 | MuSe2021-main/model.py | import torch.nn as nn
from torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence
class RNN(nn.Module):
def __init__(self, d_in, d_out, n_layers=1, bi=True, dropout=0.2):
super(RNN, self).__init__()
self.rnn = nn.LSTM(input_size=d_in, hidden_size=d_out, bidirectional=bi, num_layers=n_... | 1,780 | 35.346939 | 118 | py |
MuSe2021 | MuSe2021-main/dataset.py | import torch
from torch.utils.data.dataset import Dataset
from torch.nn.utils.rnn import pad_sequence
class MuSeDataset(Dataset):
def __init__(self, data, partition):
super(MuSeDataset, self).__init__()
self.partition = partition
features, labels = data[partition]['feature'], data[partitio... | 1,669 | 36.954545 | 118 | py |
MuSe2021 | MuSe2021-main/eval.py | import numpy as np
import os
import pandas as pd
import torch
from sklearn.metrics import f1_score
from loss import get_segment_wise_logits, get_segment_wise_labels
def calc_ccc(preds, labels):
preds = np.row_stack(preds)[:, 0]
labels = np.row_stack(labels)[:, 0]
preds_mean, labels_mean = np.mean(preds)... | 6,397 | 36.197674 | 117 | py |
MuSe2021 | MuSe2021-main/train.py | import time
import os
import numpy as np
import torch
import torch.optim as optim
from eval import evaluate
from loss import get_segment_wise_logits, get_segment_wise_labels
def train(task, model, train_loader, epoch, optimizer, criterion, use_gpu=False):
start_time = time.time()
report_loss, report_size = 0... | 3,742 | 34.311321 | 119 | py |
EvidentialTuringProcess | EvidentialTuringProcess-main/etp.py | import torch as th
import torch.nn.functional as F
from scipy.special import digamma
from torch import nn
from torch.distributions import Dirichlet, Normal, Gamma
from torch.distributions.kl import kl_divergence
from copy import deepcopy
import math
import numpy as np
class ETPHyperParams:
def __init__(self, n_cl... | 4,654 | 37.471074 | 119 | py |
EvidentialTuringProcess | EvidentialTuringProcess-main/VBLayer.py | import numpy as np
import torch as th
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.utils import _pair
import math
class VBLinear(nn.Module):
def __init__(self, in_features, out_features, prior_prec=10, map=True):
super(VBLinear, self)... | 2,334 | 30.986301 | 88 | py |
EvidentialTuringProcess | EvidentialTuringProcess-main/script.py | import os
import numpy as np
import torch as th
from dataprep import prepare_data
from architectures import LeNet5
from etp import EvidentialTuringProcess
import argparse
import time
from datetime import timedelta
import json
from utils import get_results
def train(model, train_loader, ood_loader, epoch, opt, iscuda... | 6,494 | 27.866667 | 100 | py |
EvidentialTuringProcess | EvidentialTuringProcess-main/dataprep.py | from torch.utils.data import DataLoader
from torchvision import datasets, transforms
import numpy as np
from torch.utils import data
def prepare_for_training_with_ood(train_dataset, ood_dataset):
if len(train_dataset) < len(ood_dataset):
id_ratio = np.ceil(float(len(ood_dataset)) / float(len(train_dataset... | 3,518 | 30.419643 | 87 | py |
EvidentialTuringProcess | EvidentialTuringProcess-main/scores.py | import numpy as np
import torch as th
import torch.nn.functional as F
from sklearn.metrics import roc_auc_score
def nll(preds, target, minibatch=True):
logpred = th.log(preds + 1e-8)
if minibatch:
return -(logpred * target).sum(1)
else:
return -(logpred * target).sum(1).mean()
def err(pr... | 3,851 | 30.57377 | 88 | py |
EvidentialTuringProcess | EvidentialTuringProcess-main/architectures.py | import torch as th
import torch.nn.functional as F
from torch import nn
from torchvision import models
from VBLayer import VBLinear
class LeNet5(nn.Module):
def __init__(
self,
n_channels=1,
n_classes=10,
mcdrop=True,
isvb=False,
has_context=False,
prior_pr... | 2,301 | 30.534247 | 88 | py |
HumanDensePose | HumanDensePose-main/setup.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import glob
import os
import shutil
from os import path
from setuptools import find_packages, setup
from typing import List
import torch
from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
from torch.u... | 6,940 | 33.02451 | 97 | py |
HumanDensePose | HumanDensePose-main/tools/benchmark.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
A script to benchmark builtin models.
Note: this script has an extra dependency of psutil.
"""
import itertools
import logging
import psutil
import torch
import tqdm
from fvcore.common.timer import Timer
from torch.nn.par... | 5,051 | 29.071429 | 107 | py |
HumanDensePose | HumanDensePose-main/tools/visualize_data.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import argparse
import os
from itertools import chain
import cv2
import tqdm
from detectron2.config import get_cfg
from detectron2.data import DatasetCatalog, MetadataCatalog, build_detection_train_loader
from detectron2.data ... | 3,572 | 37.010638 | 94 | py |
HumanDensePose | HumanDensePose-main/tools/plain_train_net.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Detectron2 training script with a plain training loop.
This script reads a given config file and runs the training or evaluation.
It is an entry point that is able to train standard models in detectron2.
In order to let o... | 8,548 | 34.920168 | 99 | py |
HumanDensePose | HumanDensePose-main/tools/convert-torchvision-to-d2.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import pickle as pkl
import sys
import torch
"""
Usage:
# download one of the ResNet{18,34,50,101,152} models from torchvision:
wget https://download.pytorch.org/models/resnet50-19c8e357.pth -O r50.pth
# run the convers... | 1,628 | 27.578947 | 87 | py |
HumanDensePose | HumanDensePose-main/tools/train_net.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Detection Training Script.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is made to train standard models in detectron2.
In order to let one script support training ... | 6,361 | 36.204678 | 99 | py |
HumanDensePose | HumanDensePose-main/tools/deploy/caffe2_converter.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import argparse
import os
import onnx
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import get_cfg
from detectron2.data import build_detection_test_loader
from detectron2.evaluation import COC... | 3,963 | 39.44898 | 96 | py |
HumanDensePose | HumanDensePose-main/detectron2/model_zoo/model_zoo.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import os
import pkg_resources
import torch
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import get_cfg
from detectron2.modeling import build_model
class _ModelZooUrls(object):
"""
Mapping from names to o... | 8,324 | 53.769737 | 114 | py |
HumanDensePose | HumanDensePose-main/detectron2/solver/lr_scheduler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
from bisect import bisect_right
from typing import List
import torch
# NOTE: PyTorch's LR scheduler interface uses names that assume the LR changes
# only on epoch boundaries. We typically use iteration based schedules instead.
# As a r... | 4,154 | 34.512821 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/solver/build.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from enum import Enum
from typing import Any, Callable, Dict, Iterable, List, Set, Type, Union
import torch
from detectron2.config import CfgNode
from .lr_scheduler import WarmupCosineLR, WarmupMultiStepLR
_GradientClipperInput = Union[torch.Tens... | 5,831 | 34.13253 | 94 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/lvis_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import itertools
import json
import logging
import os
import pickle
from collections import OrderedDict
import torch
from fvcore.common.file_io import PathManager
import detectron2.utils.comm as comm
from detectron2.data import Metadata... | 13,757 | 38.196581 | 150 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/cityscapes_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import glob
import logging
import numpy as np
import os
import tempfile
from collections import OrderedDict
import torch
from fvcore.common.file_io import PathManager
from PIL import Image
from detectron2.data import MetadataCatalog
from detectron2... | 7,904 | 41.047872 | 139 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/evaluator.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import datetime
import logging
import time
from collections import OrderedDict
from contextlib import contextmanager
import torch
from detectron2.utils.comm import get_world_size, is_main_process
from detectron2.utils.logger import log_every_n_seco... | 10,286 | 37.1 | 119 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/sem_seg_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import json
import logging
import numpy as np
import os
from collections import OrderedDict
import PIL.Image as Image
import pycocotools.mask as mask_util
import torch
from fvcore.common.file_io import PathManager
from detectron2.d... | 7,119 | 41.130178 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/pascal_voc_evaluation.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import os
import tempfile
import xml.etree.ElementTree as ET
from collections import OrderedDict, defaultdict
from functools import lru_cache
import torch
from fvcore.common.file_io import P... | 10,697 | 35.141892 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/rotated_coco_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import json
import numpy as np
import os
import torch
from fvcore.common.file_io import PathManager
from pycocotools.cocoeval import COCOeval, maskUtils
from detectron2.structures import BoxMode, RotatedBoxes, pairwise_iou_rotated
... | 7,573 | 35.946341 | 94 | py |
HumanDensePose | HumanDensePose-main/detectron2/evaluation/coco_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
import pickle
from collections import OrderedDict
import pycocotools.mask as mask_util
import torch
from fvcore.common.file_io import Pa... | 21,070 | 39.211832 | 168 | py |
HumanDensePose | HumanDensePose-main/detectron2/checkpoint/c2_model_loading.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import re
import torch
from fvcore.common.checkpoint import (
get_missing_parameters_message,
get_unexpected_parameters_message,
)
def convert_basic_c2_names(original_keys):
"""
Apply some basic name conv... | 14,790 | 46.105096 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/checkpoint/detection_checkpoint.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import pickle
from fvcore.common.checkpoint import Checkpointer
from fvcore.common.file_io import PathManager
import detectron2.utils.comm as comm
from .c2_model_loading import align_and_update_state_dicts
class DetectionCheckpointer(Checkpointe... | 3,074 | 40.554054 | 91 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/nms.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import List
import torch
from torchvision.ops import boxes as box_ops
from torchvision.ops import nms # BC-compat
def batched_nms(
boxes: torch.Tensor, scores: torch.Tensor, idxs: torch.Tensor, iou_thresho... | 6,679 | 43.533333 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/batch_norm.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import torch
import torch.distributed as dist
from torch import nn
from torch.autograd.function import Function
from torch.nn import functional as F
from detectron2.utils import comm, env
from .wrappers import BatchNorm2d
class Fr... | 9,855 | 39.896266 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/deform_conv.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
from functools import lru_cache
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 detectron2 import _C
from .wrap... | 16,056 | 31.438384 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/aspp.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from .batch_norm import get_norm
from .wrappers import Conv2d
class ASPP(nn.Module):
"""
Atrous Spatial Pyramid Pooling (A... | 4,835 | 38 | 137 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/roi_align.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from torch import nn
from torchvision.ops import roi_align as tv_roi_align
try:
from torchvision import __version__
version = tuple(int(x) for x in __version__.split(".")[:2])
USE_TORCHVISION = version >= (0, 7) # https://github.com/p... | 4,626 | 38.211864 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/shape_spec.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from collections import namedtuple
class ShapeSpec(namedtuple("_ShapeSpec", ["channels", "height", "width", "stride"])):
"""
A simple structure that contains basic shape specification about a tensor.
It is often... | 672 | 31.047619 | 85 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/wrappers.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Wrappers around on some nn functions, mainly to support empty tensors.
Ideally, add support directly in PyTorch to empty tensors in those functions.
These can be removed once https://github.com/pytorch/pytorch/issues/12013
is implemented
"""
... | 8,009 | 34.286344 | 97 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/mask_ops.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import torch
from PIL import Image
from torch.nn import functional as F
__all__ = ["paste_masks_in_image"]
BYTES_PER_FLOAT = 4
# TODO: This memory limit may be too much or too little. It would be better to
# determine it based ... | 9,840 | 38.522088 | 97 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/roi_align_rotated.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from detectron2 import _C
class _ROIAlignRotated(Function):
@staticmethod
def forwar... | 3,140 | 34.292135 | 90 | py |
HumanDensePose | HumanDensePose-main/detectron2/layers/blocks.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from torch import nn
from .batch_norm import FrozenBatchNorm2d
class CNNBlockBase(nn.Module):
"""
A CNN block is assumed to have input channels, output channels and a stride.
The input and output of `forward()... | 1,380 | 27.183673 | 82 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/caffe2_export.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import io
import logging
import numpy as np
from typing import List
import onnx
import torch
from caffe2.proto import caffe2_pb2
from caffe2.python import core
from caffe2.python.onnx.backend import Caffe2Backend
from tabulate import ta... | 7,723 | 36.678049 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/torchscript.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import importlib.util
import os
import sys
import tempfile
from contextlib import contextmanager
from typing import Dict
import torch
# fmt: off
from detectron2.modeling.proposal_generator import RPN
# need an explicit import due to https://github... | 5,188 | 32.477419 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/caffe2_modeling.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import functools
import io
import struct
import types
import torch
from detectron2.modeling import meta_arch
from detectron2.modeling.box_regression import Box2BoxTransform
from detectron2.modeling.meta_arch.panoptic_fpn import combine_semantic_an... | 20,965 | 41.100402 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/c10.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import math
import torch
import torch.nn.functional as F
from detectron2.layers import cat
from detectron2.layers.roi_align_rotated import ROIAlignRotated
from detectron2.modeling import poolers
from detectron2.modeling.proposal_generator import ... | 19,733 | 38.154762 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/api.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import copy
import logging
import os
import torch
from caffe2.proto import caffe2_pb2
from torch import nn
from detectron2.config import CfgNode as CN
from .caffe2_inference import ProtobufDetectionModel
from .caffe2_modeling import META_ARCH_CAF... | 10,160 | 34.404181 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/shared.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import collections
import contextlib
import copy
import functools
import logging
import mock
import numpy as np
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import caffe2.python.utils as putils
import torch
import ... | 38,083 | 35.796135 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/patcher.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import contextlib
import mock
import torch
from detectron2.modeling import poolers
from detectron2.modeling.proposal_generator import rpn
from detectron2.modeling.roi_heads import keypoint_head, mask_head
from detectron2.modeling.roi_heads.fast_rc... | 5,037 | 31.714286 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/export/caffe2_inference.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import collections
import logging
import numpy as np
import torch
from caffe2.proto import caffe2_pb2
from caffe2.python import core
from .caffe2_modeling import META_ARCH_CAFFE2_EXPORT_TYPE_MAP, convert_batched_inputs_to_c2_format
from .shared im... | 5,845 | 41.671533 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/engine/hooks.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import datetime
import itertools
import logging
import os
import tempfile
import time
from collections import Counter
import torch
from fvcore.common.checkpoint import PeriodicCheckpointer as _PeriodicCheckpointer
from fvcor... | 15,050 | 34.248244 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/engine/launch.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from detectron2.utils import comm
__all__ = ["launch"]
def _find_free_port():
import socket
sock = socket.socket(socket.AF_INET, socket.SOCK... | 3,640 | 37.326316 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/engine/defaults.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
This file contains components with some default boilerplate logic user may need
in training / testing. They will not work for everyone, but many users may find them useful.
The behavior of functions/classes in this file... | 22,262 | 37.651042 | 111 | py |
HumanDensePose | HumanDensePose-main/detectron2/engine/train_loop.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import contextlib
import logging
import numpy as np
import time
import weakref
import torch
import detectron2.utils.comm as comm
from detectron2.utils.events import EventStorage
__all__ = ["HookBase", "TrainerBase", "Simpl... | 9,621 | 32.17931 | 96 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/events.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import datetime
import json
import logging
import os
import time
from collections import defaultdict
from contextlib import contextmanager
import torch
from fvcore.common.file_io import PathManager
from fvcore.common.history_buffer import HistoryBuf... | 15,044 | 33.745958 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/memory.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import logging
from contextlib import contextmanager
from functools import wraps
import torch
__all__ = ["retry_if_cuda_oom"]
@contextmanager
def _ignore_torch_cuda_oom():
"""
A context which ignores CUDA OOM exception from pytorch.
... | 2,604 | 29.647059 | 95 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/comm.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
"""
import functools
import logging
import numpy as np
import pickle
import torch
import torch.distributed as dist
_LOCAL_PROCESS_GROUP ... | 7,750 | 28.359848 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/collect_env.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import importlib
import numpy as np
import os
import re
import subprocess
import sys
from collections import defaultdict
import PIL
import torch
import torchvision
from tabulate import tabulate
__all__ = ["collect_env_info"]
def collect_torch_env... | 6,068 | 31.983696 | 96 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/analysis.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# -*- coding: utf-8 -*-
import logging
import typing
import torch
from fvcore.nn import activation_count, flop_count, parameter_count, parameter_count_table
from torch import nn
from detectron2.structures import BitMasks, Boxes, ImageList, Instanc... | 5,355 | 31.460606 | 96 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/visualizer.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import colorsys
import logging
import math
import numpy as np
from enum import Enum, unique
import cv2
import matplotlib as mpl
import matplotlib.colors as mplc
import matplotlib.figure as mplfigure
import pycocotools.mask as mask_util
import torch
... | 46,706 | 38.98887 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/utils/env.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import importlib
import importlib.util
import logging
import numpy as np
import os
import random
import sys
from datetime import datetime
import torch
__all__ = ["seed_all_rng"]
TORCH_VERSION = tuple(int(x) for x in torch.__version__.split(".")[:... | 3,798 | 29.886179 | 93 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/dataset_mapper.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import numpy as np
from typing import List, Optional, Union
import torch
from detectron2.config import configurable
from . import detection_utils as utils
from . import transforms as T
"""
This file contains the default... | 8,073 | 42.408602 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/detection_utils.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Common data processing utilities that are used in a
typical object detection data pipeline.
"""
import logging
import numpy as np
import pycocotools.mask as mask_util
import torch
from fvcore.common.file_io import PathMa... | 20,694 | 34.135823 | 105 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/common.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import numpy as np
import pickle
import random
import torch.utils.data as data
from detectron2.utils.serialize import PicklableWrapper
__all__ = ["MapDataset", "DatasetFromList", "AspectRatioGroupedDataset"]
class MapD... | 5,308 | 34.393333 | 97 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/build.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import logging
import numpy as np
import operator
import pickle
import torch.utils.data
from fvcore.common.file_io import PathManager
from tabulate import tabulate
from termcolor import colored
from detectron2.structures import Box... | 15,176 | 35.927007 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/datasets/lvis_v0_5_categories.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# Autogen with
# with open("lvis_v0.5_val.json", "r") as f:
# a = json.load(f)
# c = a["categories"]
# for x in c:
# del x["image_count"]
# del x["instance_count"]
# LVIS_CATEGORIES = repr(c) + " # noqa"
# fmt: off
LVIS_CATEGORIES = [{... | 223,777 | 15,983.142857 | 223,466 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/datasets/lvis_v1_categories.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# Autogen with
# with open("lvis_v1_val.json", "r") as f:
# a = json.load(f)
# c = a["categories"]
# for x in c:
# del x["image_count"]
# del x["instance_count"]
# LVIS_CATEGORIES = repr(c) + " # noqa"
# with open("/tmp/lvis_categories.... | 219,197 | 12,893 | 218,738 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/samplers/grouped_batch_sampler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from torch.utils.data.sampler import BatchSampler, Sampler
class GroupedBatchSampler(BatchSampler):
"""
Wraps another sampler to yield a mini-batch of indices.
It enforces that the batch only contain elements from th... | 1,964 | 39.9375 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/samplers/distributed_sampler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import math
from collections import defaultdict
from typing import Optional
import torch
from torch.utils.data.sampler import Sampler
from detectron2.utils import comm
class TrainingSampler(Sampler):
"""
In training, we o... | 8,142 | 39.512438 | 97 | py |
HumanDensePose | HumanDensePose-main/detectron2/data/transforms/transform.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# File: transform.py
import numpy as np
import torch
import torch.nn.functional as F
from fvcore.transforms.transform import (
CropTransform,
HFlipTransform,
NoOpTransform,
Transform,
TransformList,
)
fro... | 11,654 | 34.972222 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/box_regression.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
from typing import Tuple
import torch
# Value for clamping large dw and dh predictions. The heuristic is that we clamp
# such that dw and dh are no larger than what would transform a 16px box into a
# 1000px box (based on a small anchor... | 9,110 | 40.040541 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/test_time_augmentation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import numpy as np
from contextlib import contextmanager
from itertools import count
import torch
from fvcore.transforms import HFlipTransform, NoOpTransform
from torch import nn
from torch.nn.parallel import DistributedDataParallel
fro... | 11,921 | 39.828767 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/anchor_generator.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
from typing import List
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.layers import ShapeSpec
from detectron2.structures import Boxes, RotatedBoxes
from detectron2.utils.registry import Reg... | 15,181 | 39.058047 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/matcher.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import List
import torch
from detectron2.layers import nonzero_tuple
class Matcher(object):
"""
This class assigns to each predicted "element" (e.g., a box) a ground-truth
element. Each predicted element will have exactly ... | 6,252 | 48.23622 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/sampling.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from detectron2.layers import nonzero_tuple
__all__ = ["subsample_labels"]
def subsample_labels(
labels: torch.Tensor, num_samples: int, positive_fraction: float, bg_label: int
):
"""
Return `num_samples` (or fewer, if n... | 2,354 | 41.818182 | 94 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/poolers.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import math
from typing import List
import torch
from torch import nn
from torchvision.ops import RoIPool
from detectron2.layers import ROIAlign, ROIAlignRotated, cat, nonzero_tuple
from detectron2.structures import Boxes
"""
To export ROIPooler ... | 10,608 | 42.126016 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/postprocessing.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch.nn import functional as F
from detectron2.layers import paste_masks_in_image
from detectron2.structures import Instances
from detectron2.utils.memory import retry_if_cuda_oom
def detector_postprocess(results, output_height... | 3,675 | 36.510204 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/backbone/resnet.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.layers import (
CNNBlockBase,
Conv2d,
DeformConv,
ModulatedDeformConv,
... | 21,601 | 32.543478 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/backbone/backbone.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from abc import ABCMeta, abstractmethod
import torch.nn as nn
from detectron2.layers import ShapeSpec
__all__ = ["Backbone"]
class Backbone(nn.Module, metaclass=ABCMeta):
"""
Abstract base class for network backbones.
"""
def __... | 1,556 | 27.833333 | 97 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/backbone/fpn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
import fvcore.nn.weight_init as weight_init
import torch.nn.functional as F
from torch import nn
from detectron2.layers import Conv2d, ShapeSpec, get_norm
from .backbone import Backbone
from .build import BACKBONE_REGISTRY
from .resnet... | 10,374 | 37.568773 | 99 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/backbone/res2net.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.layers import (
CNNBlockBase,
Conv2d,
DeformConv,
ModulatedDeformConv,
ShapeSpec,
... | 22,034 | 32.185241 | 97 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/meta_arch/rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
from typing import Optional, Tuple
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.data.detection_utils import convert_image_to_rgb
from detectron2.structures import Ima... | 12,230 | 39.77 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/meta_arch/retinanet.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
import numpy as np
from typing import List
import torch
from fvcore.nn import sigmoid_focal_loss_jit, smooth_l1_loss
from torch import nn
from torch.nn import functional as F
from detectron2.data.detection_utils import convert_image_to_... | 19,734 | 42.953229 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/meta_arch/panoptic_fpn.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from detectron2.structures import ImageList
from ..backbone import build_backbone
from ..postprocessing import detector_postprocess, sem_seg_postprocess
from ..proposal_generator import bu... | 8,442 | 37.552511 | 98 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/meta_arch/semantic_seg.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from typing import Dict
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.layers import Conv2d, ShapeSpec
from detectron2.structures import ImageLis... | 7,243 | 37.531915 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/meta_arch/build.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from detectron2.utils.registry import Registry
META_ARCH_REGISTRY = Registry("META_ARCH") # noqa F401 isort:skip
META_ARCH_REGISTRY.__doc__ = """
Registry for meta-architectures, i.e. the whole model.
The registered object will be c... | 729 | 29.416667 | 83 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/roi_heads/fast_rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
from typing import Dict, Union
import torch
from fvcore.nn import giou_loss, smooth_l1_loss
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import Linear, Sh... | 24,854 | 42.835979 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/roi_heads/cascade_rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import List
import torch
from torch import nn
from torch.autograd.function import Function
from detectron2.config import configurable
from detectron2.layers import ShapeSpec
from detectron2.structures import Boxes, Instances, pairwise_i... | 12,961 | 42.351171 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/roi_heads/box_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from typing import List
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import Conv2d, Linear, S... | 3,943 | 32.423729 | 95 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/roi_heads/keypoint_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import Conv2d, ConvTranspose2d, cat, interpolate
from detectron2.structures import Inst... | 10,406 | 38.570342 | 100 | py |
HumanDensePose | HumanDensePose-main/detectron2/modeling/roi_heads/roi_heads.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import inspect
import logging
import numpy as np
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, nonzero_tuple
from detectro... | 35,211 | 42.204908 | 100 | py |
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