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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BLDR | BLDR-main/train.py | # -*- coding:utf-8 -*-
import torch
import torch.nn.functional as F
from torch.autograd import Variable
from data.datasets import input_dataset
from models.resnet_for_selfKD import *
from models.resnet import *
from loss import *
from utils import *
import argparse
import time
import os
import numpy as np
import copy... | 12,847 | 42.405405 | 220 | py |
BLDR | BLDR-main/models/resnet_for_selfKD.py | import torch
import torch.nn as nn
def conv3x3(in_planes, out_planes, stride=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3,
stride=stride, padding=1, bias=False)
def conv1x1(in_planes, planes, stride=1):
return nn.Conv2d(in_planes, planes, kernel_size=1, stride=stride, bia... | 8,078 | 35.890411 | 119 | py |
BLDR | BLDR-main/models/resnet.py | '''ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. arXiv:1512.03385
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
def c... | 9,581 | 38.110204 | 123 | py |
BLDR | BLDR-main/data/augmentations.py | # code in this file is adpated from rpmcruz/autoaugment
# https://github.com/rpmcruz/autoaugment/blob/master/transformations.py
import random
import PIL, PIL.ImageOps, PIL.ImageEnhance, PIL.ImageDraw
import numpy as np
import torch
random_mirror = True
def ShearX(img, v): # [-0.3, 0.3]
assert -0.3 <= v <= 0.3
... | 6,227 | 24.842324 | 75 | py |
BLDR | BLDR-main/data/utils.py | import os
import os.path
import copy
import hashlib
import errno
import numpy as np
from numpy.testing import assert_array_almost_equal
import torch
import torch.nn.functional as F
def check_integrity(fpath, md5):
if not os.path.isfile(fpath):
return False
md5o = hashlib.md5()
with open(fpath, 'rb... | 7,727 | 30.414634 | 141 | py |
BLDR | BLDR-main/data/datasets.py | import numpy as np
import torchvision.transforms as transforms
from .cifar import CIFAR10, CIFAR100
from data.augmentations import Augmentation, CutoutDefault
from data.augmentation_archive import autoaug_policy, autoaug_paper_cifar10, fa_reduced_cifar10
def input_dataset(dataset, noise_type, noise_path, is_human, c... | 3,505 | 39.298851 | 95 | py |
BLDR | BLDR-main/data/cifar.py | from __future__ import print_function
from PIL import Image
import os
import os.path
import numpy as np
import sys
if sys.version_info[0] == 2:
import cPickle as pickle
else:
import pickle
import torch
import torch.utils.data as data
from .utils import download_url, check_integrity, multiclass_noisify
class CI... | 15,002 | 42.486957 | 117 | py |
NTD | NTD-master/attention_model_logit_no_encoder.py | import unicodedata
import string
import re
import random
import time
import math
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
import torch.nn.init as tinit
USE_CUDA = True
MAX_LENGTH = 10
class EncoderRNN(nn.Module):
def __init__(s... | 7,766 | 40.31383 | 116 | py |
NTD | NTD-master/decoding_into_tree_copy.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from attention_model_copy import *
import numpy as ... | 16,719 | 31.2158 | 153 | py |
NTD | NTD-master/decoding_into_tree_masking_logit_parallel_updates.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem im... | 22,029 | 33.049459 | 159 | py |
NTD | NTD-master/pytorch_attention_seq_to_seq.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from attention_model import *
import numpy as np
im... | 8,626 | 27.852843 | 148 | py |
NTD | NTD-master/attention_model_copy.py | import unicodedata
import string
import re
import random
import time
import math
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
USE_CUDA = True
MAX_LENGTH = 10
class EncoderRNN(nn.Module):
def __init__(self, input_size, hidden_size,... | 7,318 | 38.777174 | 116 | py |
NTD | NTD-master/decoding_into_tree_exp.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from attention_model import *
import numpy as np
im... | 17,090 | 32.122093 | 153 | py |
NTD | NTD-master/decoding_into_tree_masking.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem im... | 19,179 | 32.414634 | 152 | py |
NTD | NTD-master/simple_attention_with_attention_removal.py | from keras.models import Sequential
from keras.layers import Dense, Activation, Input, Flatten, Merge, Reshape
from keras.activations import softmax
from keras.layers.merge import Dot
from keras.layers import LSTM
from keras.layers import Embedding
from keras.layers.core import RepeatVector
from keras.callbacks import ... | 8,869 | 25.878788 | 117 | py |
NTD | NTD-master/decoding_into_tree.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem im... | 19,284 | 32.952465 | 152 | py |
NTD | NTD-master/model_mtl.py | import numpy as np
from keras.preprocessing import sequence
from keras.layers import Merge, Input, Dense, merge
from keras.models import Model
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.em... | 7,194 | 42.606061 | 112 | py |
NTD | NTD-master/lstm_main.py | from keras.models import Sequential
from keras.layers import Dense, Activation, Input, Flatten
from keras.layers import LSTM
from keras.layers import Embedding
from keras.layers.core import RepeatVector
from keras.callbacks import ModelCheckpoint
from keras.layers.wrappers import TimeDistributed
import cPickle
import n... | 6,616 | 24.94902 | 147 | py |
NTD | NTD-master/decoding_into_tree_masking_logit.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem im... | 22,029 | 33.049459 | 159 | py |
NTD | NTD-master/attention_model.py | import unicodedata
import string
import re
import random
import time
import math
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
import torch.nn.init as tinit
USE_CUDA = True
MAX_LENGTH = 10
class EncoderRNN(nn.Module):
def __init__... | 7,665 | 39.347368 | 116 | py |
NTD | NTD-master/simple_attention_lstm.py | from keras.models import Sequential
from keras.layers import Dense, Activation, Input, Flatten, Merge, Reshape
from keras.activations import softmax
from keras.layers.merge import Dot
from keras.layers import LSTM
from keras.layers import Embedding
from keras.layers.core import RepeatVector
from keras.callbacks import ... | 9,104 | 26.759146 | 117 | py |
NTD | NTD-master/multilabel_lstm_main.py | from keras.models import Sequential
from keras.layers import Dense, Activation, Input, Flatten
from keras.layers import LSTM
from keras.layers import Embedding
from keras.layers.core import RepeatVector
from keras.callbacks import ModelCheckpoint
from keras.layers.wrappers import TimeDistributed
from keras.models impor... | 6,720 | 24.85 | 117 | py |
NTD | NTD-master/analyze_attention.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem im... | 8,868 | 28.662207 | 142 | py |
NTD | NTD-master/attention_model_logit.py | import unicodedata
import string
import re
import random
import time
import math
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
import torch.nn.init as tinit
USE_CUDA = True
MAX_LENGTH = 10
class EncoderRNN(nn.Module):
def __init__(s... | 7,731 | 40.347594 | 116 | py |
NTD | NTD-master/decoding_into_tree_masking_logit_no_encoder.py | import unicodedata
import string
import re
import random as rd
import time
import math
import cPickle
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch import optim
import torch.nn.functional as F
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem im... | 21,827 | 33.053042 | 158 | py |
NTD | NTD-master/simple_attention_lstm_multiclass.py | from keras.models import Sequential
from keras.layers import Dense, Activation, Input, Flatten, Merge, Reshape
from keras.activations import softmax
from keras.layers.merge import Dot
from keras.layers import LSTM
from keras.layers import Embedding
from keras.layers.core import RepeatVector
from keras.callbacks import ... | 10,167 | 26.705722 | 135 | py |
NTD | NTD-master/preprocessor.py | import numpy as np
from keras.preprocessing import sequence
from keras.layers import Merge, Input, Dense, merge
from keras.models import Model
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.em... | 3,251 | 38.658537 | 83 | py |
gluon-cv | gluon-cv-master/setup.py | #!/usr/bin/env python
import io
import os
import re
import sys
try:
from Cython.Build import cythonize
except ImportError:
cythonize = None
from setuptools import setup, find_packages, Extension
try:
import cv2
except ImportError:
cv2 = None
with_cython = False
if '--with-cython' in sys.argv:
if no... | 2,879 | 23.40678 | 82 | py |
gluon-cv | gluon-cv-master/scripts/depth/test.py | # Copyright Niantic 2019. Patent Pending. All rights reserved.
#
# This software is licensed under the terms of the Monodepth2 licence
# which allows for non-commercial use only, the full terms of which are made
# available in the LICENSE file.
from __future__ import absolute_import, division, print_function
import o... | 9,059 | 37.88412 | 103 | py |
gluon-cv | gluon-cv-master/scripts/depth/test_pose.py | # Copyright Niantic 2019. Patent Pending. All rights reserved.
#
# This software is licensed under the terms of the Monodepth2 licence
# which allows for non-commercial use only, the full terms of which are made
# available in the LICENSE file.
from __future__ import absolute_import, division, print_function
import o... | 6,359 | 39 | 96 | py |
gluon-cv | gluon-cv-master/scripts/depth/demo.py | import os
import argparse
import time
import PIL.Image as pil
import numpy as np
import mxnet as mx
from mxnet.gluon.data.vision import transforms
import gluoncv
from gluoncv.model_zoo.monodepthv2.layers import disp_to_depth
import matplotlib as mpl
import matplotlib.cm as cm
import cv2
# using cpu
ctx = mx.cpu(0)... | 7,947 | 34.801802 | 95 | py |
gluon-cv | gluon-cv-master/scripts/depth/options.py | import os
import argparse
import mxnet as mx
class MonodepthOptions:
def __init__(self):
self.parser = argparse.ArgumentParser(description="Monodepthv2 options")
# PATHS
self.parser.add_argument("--data_path",
type=str,
hel... | 10,265 | 50.58794 | 99 | py |
gluon-cv | gluon-cv-master/scripts/depth/trainer.py | from __future__ import absolute_import, division, print_function
import os
import sys
import shutil
import copy
from tqdm import tqdm
import numpy as np
import json
import mxnet as mx
from mxnet import gluon, autograd
from gluoncv.data import KITTIRAWDataset, KITTIOdomDataset
from gluoncv.data.kitti.kitti_utils imp... | 22,759 | 39.642857 | 109 | py |
gluon-cv | gluon-cv-master/scripts/instance/mask_rcnn/eval_mask_rcnn.py | from __future__ import division
import os
# disable autotune
os.environ['MXNET_CUDNN_AUTOTUNE_DEFAULT'] = '0'
import argparse
import glob
import logging
logging.basicConfig(level=logging.INFO)
import numpy as np
import mxnet as mx
from tqdm import tqdm
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluo... | 7,188 | 41.791667 | 93 | py |
gluon-cv | gluon-cv-master/scripts/instance/mask_rcnn/train_mask_rcnn.py | """Train Mask RCNN end to end."""
import argparse
import os
# disable autotune
os.environ['MXNET_CUDNN_AUTOTUNE_DEFAULT'] = '0'
os.environ['MXNET_GPU_MEM_POOL_TYPE'] = 'Round'
os.environ['MXNET_GPU_MEM_POOL_ROUND_LINEAR_CUTOFF'] = '28'
os.environ['MXNET_EXEC_BULK_EXEC_MAX_NODE_TRAIN_FWD'] = '999'
os.environ['MXNET_EXE... | 37,024 | 48.432577 | 101 | py |
gluon-cv | gluon-cv-master/scripts/instance/mask_rcnn/demo_mask_rcnn.py | """Mask RCNN Demo script."""
import os
import argparse
import mxnet as mx
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data.transforms import presets
from matplotlib import pyplot as plt
def parse_args():
parser = argparse.ArgumentParser(description='Test with Mask RCNN networks.')
parse... | 2,423 | 40.793103 | 115 | py |
gluon-cv | gluon-cv-master/scripts/classification/finetune/finetune_minc.py | import mxnet as mx
import numpy as np
import os, time, logging, argparse, shutil
from mxnet import gluon, image, init, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.utils import makedirs
... | 6,421 | 37.22619 | 102 | py |
gluon-cv | gluon-cv-master/scripts/classification/imagenet/demo_imagenet.py | import argparse
from mxnet import nd, image
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data import ImageNet1kAttr
from gluoncv.data.transforms.presets.imagenet import transform_eval
from gluoncv.model_zoo import get_model
parser = argparse.ArgumentParser(description='Predict ImageNet classes... | 1,362 | 29.288889 | 91 | py |
gluon-cv | gluon-cv-master/scripts/classification/imagenet/train_horovod.py | # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to u... | 22,082 | 40.98289 | 115 | py |
gluon-cv | gluon-cv-master/scripts/classification/imagenet/train_imagenet.py | import argparse, time, logging, os, math
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data import imagenet
from gluoncv.model_zoo import get_model
fr... | 25,317 | 48.643137 | 145 | py |
gluon-cv | gluon-cv-master/scripts/classification/imagenet/dali.py | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | 10,924 | 54.176768 | 147 | py |
gluon-cv | gluon-cv-master/scripts/classification/imagenet/train_imagenet_nasnet.py | import argparse, time, logging, os
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data import imagenet
from gluoncv.loss import MixSoftmaxCross... | 16,730 | 44.218919 | 119 | py |
gluon-cv | gluon-cv-master/scripts/classification/imagenet/verify_pretrained.py | import argparse, os, math, time, sys
import mxnet as mx
import logging
from mxnet import gluon, nd, image
from mxnet.gluon.nn import Block, HybridBlock
from mxnet.gluon.data.vision import transforms
from mxnet.contrib.quantization import *
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data impor... | 11,174 | 44.426829 | 127 | py |
gluon-cv | gluon-cv-master/scripts/classification/cifar/train_mixup_cifar10.py | """
Train on CIFAR-10 with Mixup
============================
"""
from __future__ import division
import matplotlib
matplotlib.use('Agg')
import argparse, time, logging, random, math
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from ... | 9,270 | 38.619658 | 116 | py |
gluon-cv | gluon-cv-master/scripts/classification/cifar/train_cifar10.py | import matplotlib
matplotlib.use('Agg')
import argparse, time, logging
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.mode... | 7,931 | 38.66 | 116 | py |
gluon-cv | gluon-cv-master/scripts/classification/cifar/demo_cifar10.py | import argparse
import numpy as np
import mxnet as mx
import matplotlib.pyplot as plt
from mxnet import gluon, nd, image
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.model_zoo import get_model
parser = argparse.ArgumentParser(description='Predict ... | 1,662 | 29.796296 | 90 | py |
gluon-cv | gluon-cv-master/scripts/segmentation/test.py | import os
import logging
from tqdm import tqdm
import numpy as np
import argparse
import time
import sys
import mxnet as mx
from mxnet import gluon, ndarray as nd
from mxnet.gluon.data.vision import transforms
from mxnet.contrib.quantization import *
import gluoncv
gluoncv.utils.check_version('0.6.0')
from gluoncv.mo... | 16,524 | 46.214286 | 127 | py |
gluon-cv | gluon-cv-master/scripts/segmentation/train.py | import os
import logging
import shutil
import argparse
import numpy as np
from tqdm import tqdm
import mxnet as mx
from mxnet import gluon, autograd
from mxnet.gluon.data.vision import transforms
import gluoncv
gluoncv.utils.check_version('0.6.0')
from gluoncv.loss import *
from gluoncv.utils import makedirs, LRSched... | 14,420 | 46.4375 | 96 | py |
gluon-cv | gluon-cv-master/scripts/re-id/baseline/test.py | # -*- coding: utf-8 -*-
from __future__ import print_function, division
import mxnet as mx
import numpy as np
from mxnet import gluon, nd
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
from networks import resnet18, resnet34, resnet50
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
f... | 5,011 | 31.128205 | 178 | py |
gluon-cv | gluon-cv-master/scripts/re-id/baseline/train.py | from __future__ import division
import argparse, datetime, os
import logging
logging.basicConfig(level=logging.INFO)
import mxnet as mx
from mxnet import gluon, nd
from mxnet.gluon.model_zoo import vision as models
from mxnet.gluon.data.vision import transforms
from mxnet import autograd
from networks import resnet1... | 6,755 | 38.508772 | 127 | py |
gluon-cv | gluon-cv-master/scripts/re-id/baseline/networks/resnet.py | from __future__ import absolute_import
from mxnet.gluon import nn, HybridBlock
from mxnet import init
from mxnet.gluon.model_zoo import vision
class ResNet(HybridBlock):
__factory = {
18: vision.resnet18_v1,
34: vision.resnet34_v1,
50: vision.resnet50_v1,
101: vision.resnet101_v1,... | 1,722 | 25.921875 | 92 | py |
gluon-cv | gluon-cv-master/scripts/datasets/otb2015.py | """this script is used to prepare Otb2015 dataset for tracking,
which is Single Object Tracking benchmark"""
import argparse
import tarfile
import os
import time
import json
import numpy as np
from gluoncv.utils import download, makedirs
otb50 = ['Basketball','Biker','Bird1','BlurBody','BlurCar2','BlurFace','BlurOwl'... | 3,125 | 43.657143 | 98 | py |
gluon-cv | gluon-cv-master/scripts/datasets/ade20k.py | """Prepare ADE20K dataset"""
import os
import shutil
import argparse
import zipfile
from gluoncv.utils import download, makedirs
_TARGET_DIR = os.path.expanduser('~/.mxnet/datasets/ade')
def parse_args():
parser = argparse.ArgumentParser(
description='Initialize ADE20K dataset.',
epilog='Example:... | 1,536 | 35.595238 | 127 | py |
gluon-cv | gluon-cv-master/scripts/datasets/tiny_motorbike.py | """Prepare PASCAL VOC tiny motorbike datasets"""
import os
import autogluon as ag
if __name__ == '__main__':
root = os.path.expanduser('~/.mxnet/datasets/')
if not os.path.exists(root):
os.makedirs(root)
filename_zip = ag.download('https://autogluon.s3.amazonaws.com/datasets/tiny_motorbike.zip', ... | 505 | 30.625 | 107 | py |
gluon-cv | gluon-cv-master/scripts/datasets/cityscapes.py | """Prepare Cityscapes dataset"""
import os
import shutil
import argparse
import zipfile
from gluoncv.utils import download, makedirs
from mxnet.gluon.utils import check_sha1
_TARGET_DIR = os.path.expanduser('~/.mxnet/datasets/citys')
def parse_args():
parser = argparse.ArgumentParser(
description='Initial... | 1,862 | 38.638298 | 93 | py |
gluon-cv | gluon-cv-master/scripts/datasets/ilsvrc_det.py | """this script is used to prepare DET dataset for tracking,
which is Object detection in Large Scale Visual Recognition Challenge 2015 (ILSVRC2015)
Code adapted from https://github.com/STVIR/pysot"""
import argparse
import tarfile
import os
import glob
try:
import xml.etree.cElementTree as ET
except ImportError:
... | 8,831 | 45.978723 | 114 | py |
gluon-cv | gluon-cv-master/scripts/datasets/pascal_voc.py | """Prepare PASCAL VOC datasets"""
import os
import shutil
import argparse
import tarfile
from gluoncv.utils import download, makedirs
_TARGET_DIR = os.path.expanduser(os.environ.get('MXNET_HOME', os.path.join('~', '.mxnet', 'datasets', 'voc')))
def parse_args():
parser = argparse.ArgumentParser(
descript... | 4,259 | 45.813187 | 154 | py |
gluon-cv | gluon-cv-master/scripts/datasets/somethingsomethingv2.py | """This script is for preprocessing something-something-v2 dataset.
The code is largely borrowed from https://github.com/MIT-HAN-LAB/temporal-shift-module
and https://github.com/metalbubble/TRN-pytorch/blob/master/process_dataset.py
"""
import os
import sys
import threading
import argparse
import json
def parse_args(... | 4,780 | 38.512397 | 145 | py |
gluon-cv | gluon-cv-master/scripts/datasets/mhp_v1.py | """Prepare Multi-Human Parsing V1 dataset"""
import os
import shutil
import argparse
import zipfile
from gluoncv.utils import makedirs
from gluoncv.utils.filesystem import try_import_gdfDownloader, try_import_html5lib
_TARGET_DIR = os.path.expanduser('~/.mxnet/datasets/mhp')
def parse_args():
parser = argparse.A... | 1,660 | 30.339623 | 98 | py |
gluon-cv | gluon-cv-master/scripts/datasets/ucf101.py | """This script is largely borrowed from https://github.com/open-mmlab/mmaction.
"""
import argparse
import sys
import os
import os.path as osp
import glob
import fnmatch
import random
import zipfile
from pipes import quote
from multiprocessing import Pool, current_process
def dump_frames(vid_item):
from gluoncv.... | 14,689 | 39.136612 | 133 | py |
gluon-cv | gluon-cv-master/scripts/datasets/market1501.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function, division
import json
import argparse
from os import walk
from os import path as osp
from zipfile import ZipFile
from gluoncv.utils import download, makedirs
def parse_args():
parser = argparse.ArgumentParser(
description... | 2,634 | 34.133333 | 115 | py |
gluon-cv | gluon-cv-master/scripts/datasets/hmdb51.py | """This script is for preprocessing HMDB51 dataset.
"""
import argparse
import sys
import os
import os.path as osp
import glob
import fnmatch
import random
from pipes import quote
from multiprocessing import Pool, current_process
def dump_frames(vid_item):
from gluoncv.utils.filesystem import try_import_mmcv
... | 16,853 | 38.938389 | 133 | py |
gluon-cv | gluon-cv-master/scripts/datasets/ilsvrc_vid.py | """this script is used to prepare VID dataset for tracking,
which is Object detection from video in Large Scale Visual
Recognition Challenge 2015 (ILSVRC2015)
Code adapted from https://github.com/STVIR/pysot"""
import json
import os
import glob
from concurrent import futures
import time
import argparse
try:
import ... | 11,105 | 43.424 | 135 | py |
gluon-cv | gluon-cv-master/scripts/datasets/coco_tracking.py | """this script is used to prepare COCO dataset for tracking,
which is 2017 COCO
Code adapted from https://github.com/STVIR/pysot"""
import argparse
import zipfile
import os
from concurrent import futures
import time
import json
import numpy as np
from gluoncv.utils import download, makedirs
from gluoncv.data.mscoco.uti... | 6,638 | 43.557047 | 129 | py |
gluon-cv | gluon-cv-master/scripts/datasets/imagenet.py | """Prepare the ImageNet dataset"""
import os
import argparse
import tarfile
import pickle
import gzip
import subprocess
from tqdm import tqdm
from mxnet.gluon.utils import check_sha1
from gluoncv.utils import download, makedirs
_TARGET_DIR = os.path.expanduser('~/.mxnet/datasets/imagenet')
_TRAIN_TAR = 'ILSVRC2012_img... | 5,064 | 37.082707 | 98 | py |
gluon-cv | gluon-cv-master/scripts/datasets/mscoco.py | """Prepare MS COCO datasets"""
import os
import shutil
import argparse
import zipfile
from gluoncv.utils import download, makedirs
from gluoncv.data.mscoco.utils import try_import_pycocotools
_TARGET_DIR = os.path.expanduser(os.environ.get('MXNET_HOME', os.path.join('~', '.mxnet', 'datasets', 'coco')))
def parse_args... | 2,757 | 44.213115 | 129 | py |
gluon-cv | gluon-cv-master/scripts/datasets/kinetics400.py | """This script is largely borrowed from https://github.com/open-mmlab/mmaction.
"""
import argparse
import sys
import os
import os.path as osp
import glob
import fnmatch
import random
import zipfile
from pipes import quote
from multiprocessing import Pool, current_process
import csv
def dump_frames(vid_item):
fr... | 16,665 | 38.122066 | 133 | py |
gluon-cv | gluon-cv-master/scripts/vision-language/video-language/coot/train_pytorch.py | import os
import argparse
import torch
import torch.nn as nn
import torch.distributed as dist
import torch.optim
from tensorboardX import SummaryWriter
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.data import create_datasets, create_loaders
from gluoncv.torch.utils.model_utils import deploy_model,... | 6,074 | 40.047297 | 108 | py |
gluon-cv | gluon-cv-master/scripts/pose/directpose/demo_directpose.py | import os
import argparse
from gluoncv.torch import model_zoo
from gluoncv.torch.engine.config import get_cfg_defaults
from gluoncv.torch.utils.model_utils import download
from gluoncv.torch.utils.visualizer import ColorMode, Visualizer
from gluoncv.torch.data.registry.catalog import MetadataCatalog
from PIL import Ima... | 4,812 | 46.653465 | 128 | py |
gluon-cv | gluon-cv-master/scripts/pose/directpose/export_directpose_tvm.py | import os
import argparse
import numpy as np
from gluoncv.torch import model_zoo
from gluoncv.torch.engine.config import get_cfg_defaults
from gluoncv.torch.utils.tvm_utils.nms import nms
import torch
import torchvision.transforms as T
from PIL import Image
import tvm
from tvm import relay
from tvm.contrib.download imp... | 4,593 | 40.387387 | 124 | py |
gluon-cv | gluon-cv-master/scripts/pose/directpose/train_ddp_directpose.py | import os
import argparse
import torch
import torch.nn as nn
import torch.distributed as dist
import torch.optim
from tensorboardX import SummaryWriter
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.model_zoo.pose import directpose_resnet_lpf_fpn
from gluoncv.torch.data.pose import build_pose_train_l... | 2,851 | 39.169014 | 126 | py |
gluon-cv | gluon-cv-master/scripts/pose/directpose/tvm_evaluation/evaluate_pose.py | import json
import numpy as np
import os
from pose_model import PoseEstimationInferenceModel
import cv2
from PIL import Image
from tqdm import tqdm
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
DATASET_INFO = {
'MSCOCOPerson2017_val': {
"img_dir": os.path.expanduser('~/.mxnet/dat... | 9,184 | 42.122066 | 145 | py |
gluon-cv | gluon-cv-master/scripts/pose/directpose/tvm_evaluation/pose_model.py | import tvm
from tvm.contrib import graph_runtime
from typing import List
import cv2
import numpy as np
try:
import torch
except ImportError:
torch = None
class PoseEstimationInferenceModel():
def __init__(
self,
model_prefix,
gpu_id,
image_width=1280,
... | 9,833 | 40.319328 | 176 | py |
gluon-cv | gluon-cv-master/scripts/pose/simple_pose/cam_demo.py | from __future__ import division
import argparse, time, logging, os, math, tqdm, cv2
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
from gluoncv.data import mscoco
fr... | 2,604 | 41.704918 | 105 | py |
gluon-cv | gluon-cv-master/scripts/pose/simple_pose/validate.py | import argparse, time, logging, os, math, sys
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
from mxnet.contrib.quantization import *
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
fro... | 11,112 | 43.810484 | 118 | py |
gluon-cv | gluon-cv-master/scripts/pose/simple_pose/demo.py | from __future__ import division
import argparse
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
import matplotlib.pyplot as plt
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
from gluoncv.model_zoo import get_model
from gluoncv.data.transforms.pose import det... | 1,749 | 37.888889 | 93 | py |
gluon-cv | gluon-cv-master/scripts/pose/simple_pose/train_simple_pose.py | from __future__ import division
import argparse, time, logging, os, math
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.dat... | 10,811 | 44.05 | 109 | py |
gluon-cv | gluon-cv-master/scripts/pose/alpha_pose/validate_tools.py | import sys
from tqdm import tqdm
import mxnet as mx
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data import mscoco
from gluoncv.data.transforms.pose import (flip_heatmap,
heatmap_to_coord_alpha_pose)
from gluoncv.data.transforms.presets.alpha_pose impo... | 2,989 | 34.176471 | 107 | py |
gluon-cv | gluon-cv-master/scripts/pose/alpha_pose/cam_demo.py | from __future__ import division
import argparse, time, logging, os, math, tqdm, cv2
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
from mxnet.gluon.data.vision import transforms
import matplotlib.pyplot as plt
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
f... | 2,662 | 39.348485 | 94 | py |
gluon-cv | gluon-cv-master/scripts/pose/alpha_pose/train_alpha_pose.py | from __future__ import division
import argparse, time, logging, os, math
from tqdm import tqdm
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.... | 11,817 | 44.10687 | 113 | py |
gluon-cv | gluon-cv-master/scripts/pose/alpha_pose/validate.py | import argparse, time, logging, os, math
import numpy as np
import mxnet as mx
from mxnet import gluon, nd
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data import mscoco
from gluoncv.mode... | 5,399 | 40.860465 | 116 | py |
gluon-cv | gluon-cv-master/scripts/pose/alpha_pose/demo.py | from __future__ import division
import argparse
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
import matplotlib.pyplot as plt
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
from gluoncv.model_zoo import get_model
from gluoncv.data.transforms.pose import det... | 1,774 | 38.444444 | 92 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/feat_extract_pytorch.py | import os
import time
import argparse
import numpy as np
import torch
import torch.nn as nn
from gluoncv.torch.utils.utils import build_log_dir
from gluoncv.torch.engine.config import get_cfg_defaults
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.data import VideoClsDataset
def main(cfg, save_pat... | 2,721 | 37.338028 | 104 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/inference.py | import os
import time
import argparse
import logging
import gc
from gluoncv.utils.filesystem import try_import_decord
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet.gluon.data.vision import transforms
from gluoncv.data import Kinetics400Attr, UCF101Attr, SomethingSomethingV2Attr, HMDB51Attr, Vi... | 11,629 | 46.860082 | 134 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/get_fps.py | """
Script to compute latency and fps of a model
"""
import os
import argparse
import time
import torch
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.engine.config import get_cfg_defaults
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Compute FLOPs of a model.')
p... | 1,857 | 36.918367 | 118 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/feat_extract.py | import os
import sys
import time
import argparse
import logging
import math
import gc
import json
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet.gluon.data.vision import transforms
from gluoncv.data.transforms import video
from gluoncv.model_zoo import get_model
from gluoncv.data import VideoCls... | 10,219 | 46.314815 | 134 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/test_ddp_pytorch.py | import os
import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.distributed as dist
import torch.optim
from tensorboardX import SummaryWriter
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.utils.model_utils import deploy_model, load_model
from gluoncv.torch.data import b... | 3,662 | 31.131579 | 91 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/train_ddp_pytorch.py | import os
import argparse
import torch
import torch.nn as nn
import torch.distributed as dist
import torch.optim
from tensorboardX import SummaryWriter
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.data import build_dataloader
from gluoncv.torch.utils.model_utils import deploy_model, load_model, sa... | 4,180 | 40.39604 | 129 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/train_ddp_shortonly_pytorch.py | import os
import argparse
import torch
import torch.nn as nn
import torch.distributed as dist
import torch.optim
from tensorboardX import SummaryWriter
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.data import build_dataloader
from gluoncv.torch.utils.model_utils import deploy_model, load_model, sa... | 3,990 | 41.913978 | 129 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/get_flops.py | """
Script to compute FLOPs of a model
"""
import os
import argparse
import torch
from gluoncv.torch.model_zoo import get_model
from gluoncv.torch.engine.config import get_cfg_defaults
from thop import profile, clever_format
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Compute FLOPs ... | 1,055 | 33.064516 | 111 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/test_recognizer.py | import argparse, time, logging, os, sys, math
import gc
import numpy as np
import mxnet as mx
import mxnet.ndarray as F
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from mxnet import gluon, nd, gpu, init, context
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import ... | 23,463 | 55.676329 | 159 | py |
gluon-cv | gluon-cv-master/scripts/action-recognition/train_recognizer.py | import argparse, time, logging, os, sys, math
import numpy as np
import mxnet as mx
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from mxnet import gluon, nd, init, context
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import transforms
from mxboard import SummaryWri... | 33,974 | 60.106115 | 178 | py |
gluon-cv | gluon-cv-master/scripts/detection/demo_webcam_run.py | import argparse
import time
import gluoncv as gcv
gcv.utils.check_version('0.4.0')
from gluoncv.utils import try_import_cv2
cv2 = try_import_cv2()
import mxnet as mx
parser = argparse.ArgumentParser(description="Webcam object detection script",
formatter_class=argparse.ArgumentDefault... | 1,467 | 28.959184 | 135 | py |
gluon-cv | gluon-cv-master/scripts/detection/ssd/eval_ssd.py | from __future__ import division
from __future__ import print_function
import argparse
import logging
logging.basicConfig(level=logging.INFO)
import time
import sys
import numpy as np
import mxnet as mx
from tqdm import tqdm
from mxnet import nd
from mxnet import gluon
import gluoncv as gcv
gcv.utils.check_version('0.6... | 10,289 | 46.860465 | 120 | py |
gluon-cv | gluon-cv-master/scripts/detection/ssd/demo_ssd.py | """SSD Demo script."""
import os
import argparse
import mxnet as mx
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data.transforms import presets
from matplotlib import pyplot as plt
def parse_args():
parser = argparse.ArgumentParser(description='Test with SSD networks.')
parser.add_argume... | 2,312 | 41.054545 | 92 | py |
gluon-cv | gluon-cv-master/scripts/detection/ssd/train_ssd.py | """Train SSD"""
import argparse
import os
import logging
import warnings
import time
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet import gluon
from mxnet import autograd
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data as gdata
from gluoncv import utils as gutils
... | 20,224 | 47.04038 | 132 | py |
gluon-cv | gluon-cv-master/scripts/detection/center_net/train_center_net.py | """Train CenterNet"""
import argparse
import os
import logging
import warnings
import time
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet import gluon
from mxnet import autograd
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data as gdata
from gluoncv import utils as g... | 15,220 | 49.234323 | 134 | py |
gluon-cv | gluon-cv-master/scripts/detection/center_net/eval_center_net.py | from __future__ import division
from __future__ import print_function
import argparse
import logging
logging.basicConfig(level=logging.INFO)
import time
import numpy as np
import mxnet as mx
from tqdm import tqdm
from mxnet import nd
from mxnet import gluon
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from g... | 5,433 | 43.178862 | 113 | py |
gluon-cv | gluon-cv-master/scripts/detection/center_net/demo_center_net.py | """CenterNet Demo script."""
import os
import argparse
import mxnet as mx
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.data.transforms import presets
from matplotlib import pyplot as plt
def parse_args():
parser = argparse.ArgumentParser(description='Test with CenterNet networks.')
parse... | 2,360 | 41.927273 | 92 | py |
gluon-cv | gluon-cv-master/scripts/detection/faster_rcnn/eval_faster_rcnn.py | from __future__ import division
from __future__ import print_function
import os
# disable autotune
os.environ['MXNET_CUDNN_AUTOTUNE_DEFAULT'] = '0'
import argparse
import glob
import logging
logging.basicConfig(level=logging.INFO)
import time
import numpy as np
import mxnet as mx
from tqdm import tqdm
from mxnet impor... | 7,430 | 43.76506 | 143 | py |
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