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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imgclsmob | imgclsmob-master/chainer_/chainercv2/models/spnasnet.py | """
Single-Path NASNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours,'
https://arxiv.org/abs/1904.02877.
"""
__all__ = ['SPNASNet', 'spnasnet']
import os
import chainer.functions as F
import chainer.links as L
from cha... | 10,918 | 31.987915 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/fastscnn.py | """
Fast-SCNN for image segmentation, implemented in Chainer.
Original paper: 'Fast-SCNN: Fast Semantic Segmentation Network,' https://arxiv.org/abs/1902.04502.
"""
__all__ = ['FastSCNN', 'fastscnn_cityscapes']
import os
import chainer.functions as F
from chainer import Chain
from functools import partial
fro... | 16,053 | 29.992278 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/darknet.py | """
DarkNet for ImageNet-1K, implemented in Chainer.
Original source: 'Darknet: Open source neural networks in c,' https://github.com/pjreddie/darknet.
"""
__all__ = ['DarkNet', 'darknet_ref', 'darknet_tiny', 'darknet19']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Ch... | 8,597 | 31.692015 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/ror_cifar.py | """
RoR-3 for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Residual Networks of Residual Networks: Multilevel Residual Networks,'
https://arxiv.org/abs/1608.02908.
"""
__all__ = ['CIFARRoR', 'ror3_56_cifar10', 'ror3_56_cifar100', 'ror3_56_svhn', 'ror3_110_cifar10', 'ror3_110_cifar100',
'... | 17,097 | 32.071567 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/dicenet.py | """
DiCENet for ImageNet-1K, implemented in Chainer.
Original paper: 'DiCENet: Dimension-wise Convolutions for Efficient Networks,' https://arxiv.org/abs/1906.03516.
"""
__all__ = ['DiceNet', 'dicenet_wd5', 'dicenet_wd2', 'dicenet_w3d4', 'dicenet_w1', 'dicenet_w5d4', 'dicenet_w3d2',
'dicenet_w7d8', ... | 24,993 | 30.678074 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/nvpattexp.py | """
Neural Voice Puppetry Audio-to-Expression net for speech-driven facial animation, implemented in Chainer.
Original paper: 'Neural Voice Puppetry: Audio-driven Facial Reenactment,' https://arxiv.org/abs/1912.05566.
"""
__all__ = ['NvpAttExp', 'nvpattexp116bazel76']
import os
from functools import partial
i... | 9,004 | 33.76834 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/octresnet.py | """
Oct-ResNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave
Convolution,' https://arxiv.org/abs/1904.05049.
"""
__all__ = ['OctResNet', 'octresnet10_ad2', 'octresnet50b_ad2', 'OctResUnit']
import os
from ... | 28,431 | 33.379686 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/alexnet.py | """
AlexNet for ImageNet-1K, implemented in Chainer.
Original paper: 'One weird trick for parallelizing convolutional neural networks,'
https://arxiv.org/abs/1404.5997.
"""
__all__ = ['AlexNet', 'alexnet', 'alexnetb']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Ch... | 9,402 | 28.850794 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/mobilenet_cub.py | """
MobileNet & FD-MobileNet for CUB-200-2011, implemented in Chainer.
Original papers:
- 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications,'
https://arxiv.org/abs/1704.04861.
- 'FD-MobileNet: Improved MobileNet with A Fast Downsampling Strategy,' https://arxiv.o... | 6,926 | 34.891192 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/wrn.py | """
WRN for ImageNet-1K, implemented in Chainer.
Original paper: 'Wide Residual Networks,' https://arxiv.org/abs/1605.07146.
"""
__all__ = ['WRN', 'wrn50_2']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial
from chainer.serializers impor... | 11,832 | 27.444712 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/inceptionv3.py | """
InceptionV3 for ImageNet-1K, implemented in Chainer.
Original paper: 'Rethinking the Inception Architecture for Computer Vision,'
https://arxiv.org/abs/1512.00567.
"""
__all__ = ['InceptionV3', 'inceptionv3', 'MaxPoolBranch', 'AvgPoolBranch', 'Conv1x1Branch', 'ConvSeqBranch']
import os
import chainer.... | 23,987 | 32.178423 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/fdmobilenet.py | """
FD-MobileNet for ImageNet-1K, implemented in Chainer.
Original paper: 'FD-MobileNet: Improved MobileNet with A Fast Downsampling Strategy,'
https://arxiv.org/abs/1802.03750.
"""
__all__ = ['fdmobilenet_w1', 'fdmobilenet_w3d4', 'fdmobilenet_wd2', 'fdmobilenet_wd4', 'get_fdmobilenet']
import os
from cha... | 4,627 | 29.853333 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/others/__init__.py | 0 | 0 | 0 | py | |
imgclsmob | imgclsmob-master/chainer_/metrics/seg_metrics_np.py | """
Routines for segmentation metrics on numpy.
"""
import numpy as np
__all__ = ['seg_pixel_accuracy_np', 'segm_mean_accuracy_hmasks', 'segm_mean_accuracy', 'seg_mean_iou_np',
'segm_mean_iou2', 'seg_mean_iou_imasks_np', 'segm_fw_iou_hmasks', 'segm_fw_iou']
def seg_pixel_accuracy_np(label_imask,
... | 11,447 | 25.5 | 109 | py |
imgclsmob | imgclsmob-master/chainer_/metrics/seg_metrics.py | """
Evaluation Metrics for Semantic Segmentation.
"""
import numpy as np
from .metric import EvalMetric
from .seg_metrics_np import seg_pixel_accuracy_np, seg_mean_iou_imasks_np
__all__ = ['PixelAccuracyMetric', 'MeanIoUMetric']
class PixelAccuracyMetric(EvalMetric):
"""
Computes the pixel-wise accuracy.
... | 8,639 | 31.603774 | 86 | py |
imgclsmob | imgclsmob-master/chainer_/metrics/cls_metrics.py | """
Evaluation Metrics for Image Classification.
"""
import numpy as np
from chainer.backends import cuda
from .metric import EvalMetric
__all__ = ['Top1Error', 'TopKError']
class Accuracy(EvalMetric):
"""
Computes accuracy classification score.
Parameters:
----------
axis : int, default 1
... | 7,114 | 31.340909 | 95 | py |
imgclsmob | imgclsmob-master/chainer_/metrics/__init__.py | 0 | 0 | 0 | py | |
imgclsmob | imgclsmob-master/chainer_/metrics/det_metrics.py | """
Evaluation Metrics for Object Detection.
"""
import warnings
import numpy as np
import mxnet as mx
__all__ = ['CocoDetMApMetric']
class CocoDetMApMetric(mx.metric.EvalMetric):
"""
Detection metric for COCO bbox task.
Parameters:
----------
img_height : int
Processed image height.
... | 8,392 | 38.219626 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/metrics/hpe_metrics.py | """
Evaluation Metrics for Human Pose Estimation.
"""
import numpy as np
from .metric import EvalMetric
__all__ = ['CocoHpeOksApMetric']
class CocoHpeOksApMetric(EvalMetric):
"""
Detection metric for COCO bbox task.
Parameters:
----------
coco_annotations_file_path : str
COCO anotation ... | 3,975 | 31.859504 | 98 | py |
imgclsmob | imgclsmob-master/chainer_/metrics/metric.py | """
Several base metrics.
"""
__all__ = ['EvalMetric', 'CompositeEvalMetric', 'check_label_shapes']
from collections import OrderedDict
def check_label_shapes(labels, preds, shape=False):
"""
Helper function for checking shape of label and prediction.
Parameters:
----------
labels : list of... | 9,257 | 27.22561 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/imagenet1k_cls_dataset.py | """
ImageNet-1K classification dataset.
"""
import os
import math
import numpy as np
from PIL import Image
from chainer.dataset import DatasetMixin
from chainercv.transforms import random_crop
from chainercv.transforms import random_flip
from chainercv.transforms import pca_lighting
from chainercv.transforms impor... | 6,447 | 35.022346 | 95 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/coco_hpe1_dataset.py | """
COCO keypoint detection (2D single human pose estimation) dataset.
"""
import os
import copy
import cv2
import numpy as np
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe1Dataset(GetterDataset):
"""
COCO keypoint ... | 30,881 | 33.85553 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/ade20k_seg_dataset.py | import os
import numpy as np
from PIL import Image
from .seg_dataset import SegDataset
from .voc_seg_dataset import VOCMetaInfo
class ADE20KSegDataset(SegDataset):
"""
ADE20K semantic segmentation dataset.
Parameters:
----------
root : str
Path to a folder with `ADEChallengeData2016` subf... | 3,946 | 33.622807 | 93 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/dataset_metainfo.py | """
Base dataset metainfo class.
"""
import os
class DatasetMetaInfo(object):
def __init__(self):
self.use_imgrec = False
self.label = None
self.root_dir_name = None
self.root_dir_path = None
self.dataset_class = None
self.num_training_samples = None
se... | 2,131 | 29.028169 | 72 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/seg_dataset.py | import random
import numpy as np
from PIL import Image, ImageOps, ImageFilter
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
class SegDataset(GetterDataset):
"""
Segmentation base dataset.
Parameters:
----------
root : str
Path to data folder.
mode : str
... | 3,474 | 33.405941 | 89 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/coco_hpe2_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for Lightweight OpenPose).
"""
import os
import json
import math
import cv2
from operator import itemgetter
import numpy as np
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
from .dataset_metainfo import DatasetMe... | 20,988 | 39.597679 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/svhn_cls_dataset.py | """
SVHN classification dataset.
"""
import os
from chainer.dataset import DatasetMixin
from chainer.datasets.svhn import get_svhn
from .cifar10_cls_dataset import CIFAR10MetaInfo
class SVHN(DatasetMixin):
"""
SVHN image classification dataset from http://ufldl.stanford.edu/housenumbers/.
Each sample... | 1,587 | 29.538462 | 93 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/coco_hpe3_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for IBPPose).
"""
import os
import math
import cv2
import numpy as np
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe3Dataset(GetterDataset):
"""
... | 23,313 | 39.830123 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/cifar10_cls_dataset.py | """
CIFAR-10 classification dataset.
"""
import os
import numpy as np
from chainer.dataset import DatasetMixin
from chainer.datasets.cifar import get_cifar10
from chainercv.transforms import random_crop
from chainercv.transforms import random_flip
from .dataset_metainfo import DatasetMetaInfo
class CIFAR10(Datas... | 3,307 | 30.207547 | 77 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/__init__.py | 0 | 0 | 0 | py | |
imgclsmob | imgclsmob-master/chainer_/datasets/cub200_2011_cls_dataset.py | """
CUB-200-2011 classification dataset.
"""
import os
import numpy as np
import pandas as pd
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
from chainercv.utils import read_image
from .imagenet1k_cls_dataset import ImageNet1KMetaInfo
class CUB200_2011(GetterDataset):
"""
CUB... | 5,271 | 34.621622 | 94 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/cityscapes_seg_dataset.py | import os
import numpy as np
from PIL import Image
from .seg_dataset import SegDataset
from .voc_seg_dataset import VOCMetaInfo
class CityscapesSegDataset(SegDataset):
"""
Cityscapes semantic segmentation dataset.
Parameters:
----------
root : str
Path to a folder with `leftImg8bit` and `... | 4,878 | 36.530769 | 105 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/coco_seg_dataset.py | """
COCO semantic segmentation dataset.
"""
import os
import logging
import numpy as np
from PIL import Image
from tqdm import trange
from .seg_dataset import SegDataset
from .voc_seg_dataset import VOCMetaInfo
class CocoSegDataset(SegDataset):
"""
COCO semantic segmentation dataset.
Parameters:
... | 5,768 | 33.753012 | 112 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/voc_seg_dataset.py | """
Pascal VOC2012 semantic segmentation dataset.
"""
import os
import numpy as np
from PIL import Image
from chainer import get_dtype
from .seg_dataset import SegDataset
from .dataset_metainfo import DatasetMetaInfo
class VOCSegDataset(SegDataset):
"""
Pascal VOC2012 semantic segmentation dataset.
... | 6,790 | 31.966019 | 90 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/cifar100_cls_dataset.py | """
CIFAR-100 classification dataset.
"""
import os
from chainer.dataset import DatasetMixin
from chainer.datasets.cifar import get_cifar100
from .cifar10_cls_dataset import CIFAR10MetaInfo
class CIFAR100(DatasetMixin):
"""
CIFAR-100 image classification dataset.
Parameters:
----------
root... | 1,375 | 26.52 | 76 | py |
imgclsmob | imgclsmob-master/tensorflow2/dataset_utils.py | """
Dataset routines.
"""
__all__ = ['get_dataset_metainfo', 'get_train_data_source', 'get_val_data_source', 'get_test_data_source']
import tensorflow as tf
from .datasets.imagenet1k_cls_dataset import ImageNet1KMetaInfo
from .datasets.cub200_2011_cls_dataset import CUB200MetaInfo
from .datasets.cifar10_cls_datas... | 4,740 | 28.08589 | 106 | py |
imgclsmob | imgclsmob-master/tensorflow2/setup.py | from setuptools import setup, find_packages
from os import path
from io import open
here = path.abspath(path.dirname(__file__))
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='tf2cv',
version='0.0.18',
description='Image classification models fo... | 1,287 | 38.030303 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/utils.py | __all__ = ['prepare_model']
import os
import logging
import tensorflow as tf
from .tf2cv.model_provider import get_model
from .metrics.metric import EvalMetric, CompositeEvalMetric
from .metrics.cls_metrics import Top1Error, TopKError
from .metrics.seg_metrics import PixelAccuracyMetric, MeanIoUMetric
from .metrics.de... | 5,931 | 31.773481 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/__init__.py | 0 | 0 | 0 | py | |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/__init__.py | 0 | 0 | 0 | py | |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/model_provider.py | from .models.alexnet import *
from .models.zfnet import *
from .models.vgg import *
from .models.bninception import *
from .models.resnet import *
from .models.preresnet import *
from .models.resnext import *
from .models.seresnet import *
from .models.sepreresnet import *
from .models.seresnext import *
from .models.s... | 35,437 | 35.458848 | 95 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/airnext.py | """
AirNeXt for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Attention Inspiring Receptive-Fields Network for Learning Invariant Representations,'
https://ieeexplore.ieee.org/document/8510896.
"""
__all__ = ['AirNeXt', 'airnext50_32x4d_r2', 'airnext101_32x4d_r2', 'airnext101_32x4d_r16']
import... | 12,866 | 31.087282 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pspnet.py | """
PSPNet for image segmentation, implemented in TensorFlow.
Original paper: 'Pyramid Scene Parsing Network,' https://arxiv.org/abs/1612.01105.
"""
__all__ = ['PSPNet', 'pspnet_resnetd50b_voc', 'pspnet_resnetd101b_voc', 'pspnet_resnetd50b_coco',
'pspnet_resnetd101b_coco', 'pspnet_resnetd50b_ade20k'... | 22,270 | 38.487589 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/dla.py | """
DLA for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep Layer Aggregation,' https://arxiv.org/abs/1707.06484.
"""
__all__ = ['DLA', 'dla34', 'dla46c', 'dla46xc', 'dla60', 'dla60x', 'dla60xc', 'dla102', 'dla102x', 'dla102x2', 'dla169']
import os
import tensorflow as tf
import tensorflow.keras... | 22,786 | 31.599428 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/proxylessnas.py | """
ProxylessNAS for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware,'
https://arxiv.org/abs/1812.00332.
"""
__all__ = ['ProxylessNAS', 'proxylessnas_cpu', 'proxylessnas_gpu', 'proxylessnas_mobile', 'proxylessnas_mobile14'... | 15,845 | 35.178082 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/shufflenetv2.py | """
ShuffleNet V2 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design,'
https://arxiv.org/abs/1807.11164.
"""
__all__ = ['ShuffleNetV2', 'shufflenetv2_wd2', 'shufflenetv2_w1', 'shufflenetv2_w3d2', 'shufflenetv2_w2']
import ... | 13,783 | 32.784314 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/hrnet.py | """
HRNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep High-Resolution Representation Learning for Visual Recognition,'
https://arxiv.org/abs/1908.07919.
"""
__all__ = ['HRNet', 'hrnet_w18_small_v1', 'hrnet_w18_small_v2', 'hrnetv2_w18', 'hrnetv2_w30', 'hrnetv2_w32',
'hrnetv2... | 25,313 | 34.703808 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fcn8sd.py | """
FCN-8s(d) for image segmentation, implemented in TensorFlow.
Original paper: 'Fully Convolutional Networks for Semantic Segmentation,' https://arxiv.org/abs/1411.4038.
"""
__all__ = ['FCN8sd', 'fcn8sd_resnetd50b_voc', 'fcn8sd_resnetd101b_voc', 'fcn8sd_resnetd50b_coco',
'fcn8sd_resnetd101b_coco',... | 19,136 | 40.154839 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/selecsls.py | """
SelecSLS for ImageNet-1K, implemented in TensorFlow.
Original paper: 'XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera,'
https://arxiv.org/abs/1907.00837.
"""
__all__ = ['SelecSLS', 'selecsls42', 'selecsls42b', 'selecsls60', 'selecsls60b', 'selecsls84']
import os
import ... | 13,913 | 33.698254 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionv4.py | """
InceptionV4 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning,'
https://arxiv.org/abs/1602.07261.
"""
__all__ = ['InceptionV4', 'inceptionv4']
import os
import tensorflow as tf
import tensorflow.keras.layers a... | 23,613 | 31.303694 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/regnet.py | """
RegNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Designing Network Design Spaces,' https://arxiv.org/abs/2003.13678.
"""
__all__ = ['RegNet', 'regnetx002', 'regnetx004', 'regnetx006', 'regnetx008', 'regnetx016', 'regnetx032', 'regnetx040',
'regnetx064', 'regnetx080', 'regnetx1... | 25,743 | 33.978261 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/icnet.py | """
ICNet for image segmentation, implemented in TensorFlow.
Original paper: 'ICNet for Real-Time Semantic Segmentation on High-Resolution Images,'
https://arxiv.org/abs/1704.08545.
"""
__all__ = ['ICNet', 'icnet_resnetd50b_cityscapes']
import os
import tensorflow as tf
import tensorflow.keras.layers as n... | 15,700 | 31.985294 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenetb.py | """
MobileNet(B) with simplified depthwise separable convolution block for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications,'
https://arxiv.org/abs/1704.04861.
"""
__all__ = ['mobilenetb_w1', 'mobilenetb_w3d4', 'mobi... | 3,684 | 34.095238 | 114 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionresnetv1.py | """
InceptionResNetV1 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning,'
https://arxiv.org/abs/1602.07261.
"""
__all__ = ['InceptionResNetV1', 'inceptionresnetv1', 'InceptionAUnit', 'InceptionBUnit', 'InceptionCUn... | 20,969 | 32.127962 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/scnet.py | """
SCNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Improving Convolutional Networks with Self-Calibrated Convolutions,'
http://mftp.mmcheng.net/Papers/20cvprSCNet.pdf.
"""
__all__ = ['SCNet', 'scnet50', 'scnet101', 'scneta50', 'scneta101']
import os
import tensorflow as tf
import tenso... | 17,161 | 31.751908 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/igcv3.py | """
IGCV3 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks,'
https://arxiv.org/abs/1806.00178.
"""
__all__ = ['IGCV3', 'igcv3_w1', 'igcv3_w3d4', 'igcv3_wd2', 'igcv3_wd4']
import os
import tensorflow as tf
import ... | 10,739 | 32.667712 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnet_cifar.py | """
SE-ResNet for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['CIFARSEResNet', 'seresnet20_cifar10', 'seresnet20_cifar100', 'seresnet20_svhn',
'seresnet56_cifar10', 'seresnet56_cifar100', 'seresnet56_svhn'... | 23,745 | 36.692063 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnetd.py | """
ResNet(D) with dilation for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNetD', 'resnetd50b', 'resnetd101b', 'resnetd152b']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn... | 10,194 | 34.034364 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/quartznet.py | """
QuartzNet for ASR, implemented in TensorFlow.
Original paper: 'QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions,'
https://arxiv.org/abs/1910.10261.
"""
__all__ = ['quartznet5x5_en_ls', 'quartznet15x5_en', 'quartznet15x5_en_nr', 'quartznet15x5_fr', 'quartznet15x5_... | 13,642 | 43.439739 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/preresnet.py | """
PreResNet for ImageNet-1K, implemented in TensorFlow.
Original papers: 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
"""
__all__ = ['PreResNet', 'preresnet10', 'preresnet12', 'preresnet14', 'preresnetbc14b', 'preresnet16', 'preresnet18_wd4',
'preresnet18_wd2', ... | 28,922 | 33.107311 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/lednet.py | """
LEDNet for image segmentation, implemented in TensorFlow.
Original paper: 'LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation,'
https://arxiv.org/abs/1905.02423.
"""
__all__ = ['LEDNet', 'lednet_cityscapes']
import os
import tensorflow as tf
import tensorflow.keras.layer... | 22,964 | 31.94835 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibndensenet.py | """
IBN-DenseNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,'
https://arxiv.org/abs/1807.09441.
"""
__all__ = ['IBNDenseNet', 'ibn_densenet121', 'ibn_densenet161', 'ibn_densenet169', 'ibn_densenet201']
import os
im... | 14,434 | 32.414352 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/hardnet.py | """
HarDNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'HarDNet: A Low Memory Traffic Network,' https://arxiv.org/abs/1909.00948.
"""
__all__ = ['HarDNet', 'hardnet39ds', 'hardnet68ds', 'hardnet68', 'hardnet85']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .comm... | 24,226 | 35.213752 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/sinet.py | """
SINet for image segmentation, implemented in TensorFlow.
Original paper: 'SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and
Information Blocking Decoder,' https://arxiv.org/abs/1911.09099.
"""
__all__ = ['SINet', 'sinet_cityscapes']
import os
import tensorflow ... | 41,973 | 33.014587 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/shufflenetv2b.py | """
ShuffleNet V2 for ImageNet-1K, implemented in TensorFlow. The alternative version.
Original paper: 'ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design,'
https://arxiv.org/abs/1807.11164.
"""
__all__ = ['ShuffleNetV2b', 'shufflenetv2b_wd2', 'shufflenetv2b_w1', 'shufflenetv2b_w3d2'... | 14,161 | 32.559242 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/menet.py | """
MENet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications,'
https://arxiv.org/abs/1803.09127.
"""
__all__ = ['MENet', 'menet108_8x1_g3', 'menet128_8x1_g4', 'menet160_8x1_g8', 'menet228_12x1_g3', 'menet256_12... | 18,147 | 33.112782 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/voca.py | """
VOCA for speech-driven facial animation, implemented in TensorFlow.
Original paper: 'Capture, Learning, and Synthesis of 3D Speaking Styles,' https://arxiv.org/abs/1905.03079.
"""
__all__ = ['VOCA', 'voca8flame']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import Ba... | 8,094 | 32.589212 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/wrn_cifar.py | """
WRN for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Wide Residual Networks,' https://arxiv.org/abs/1605.07146.
"""
__all__ = ['CIFARWRN', 'wrn16_10_cifar10', 'wrn16_10_cifar100', 'wrn16_10_svhn', 'wrn28_10_cifar10',
'wrn28_10_cifar100', 'wrn28_10_svhn', 'wrn40_8_cifar10', 'wrn40_8_ci... | 11,768 | 34.342342 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionresnetv2.py | """
InceptionResNetV2 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning,'
https://arxiv.org/abs/1602.07261.
"""
__all__ = ['InceptionResNetV2', 'inceptionresnetv2']
import os
import tensorflow as tf
import tensorf... | 11,470 | 33.038576 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ghostnet.py | """
GhostNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'GhostNet: More Features from Cheap Operations,' https://arxiv.org/abs/1911.11907.
"""
__all__ = ['GhostNet', 'ghostnet']
import os
import math
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import round_channe... | 15,092 | 32.614699 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/efficientnet.py | """
EfficientNet for ImageNet-1K, implemented in TensorFlow.
Original papers:
- 'EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,' https://arxiv.org/abs/1905.11946,
- 'Adversarial Examples Improve Image Recognition,' https://arxiv.org/abs/1911.09665.
"""
__all__ = ['EfficientNe... | 40,223 | 36.804511 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pnasnet.py | """
PNASNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Progressive Neural Architecture Search,' https://arxiv.org/abs/1712.00559.
"""
__all__ = ['PNASNet', 'pnasnet5large']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import MaxPool2d, conv1x1, SimpleS... | 23,512 | 31.253772 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/efficientnetedge.py | """
EfficientNet-Edge for ImageNet-1K, implemented in TensorFlow.
Original paper: 'EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,'
https://arxiv.org/abs/1905.11946.
"""
__all__ = ['EfficientNetEdge', 'efficientnet_edge_small_b', 'efficientnet_edge_medium_b', 'efficientnet_edge_la... | 15,845 | 37 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibnresnext.py | """
IBN-ResNeXt for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Aggregated Residual Transformations for Deep Neural Networks,' http://arxiv.org/abs/1611.05431.
"""
__all__ = ['IBNResNeXt', 'ibn_resnext50_32x4d', 'ibn_resnext101_32x4d', 'ibn_resnext101_64x4d']
import os
import math
import tensorfl... | 12,035 | 32.620112 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/squeezenext.py | """
SqueezeNext for ImageNet-1K, implemented in TensorFlow.
Original paper: 'SqueezeNext: Hardware-Aware Neural Network Design,' https://arxiv.org/abs/1803.10615.
"""
__all__ = ['SqueezeNext', 'sqnxt23_w1', 'sqnxt23_w3d2', 'sqnxt23_w2', 'sqnxt23v5_w1', 'sqnxt23v5_w3d2', 'sqnxt23v5_w2']
import os
import tensor... | 13,713 | 32.367397 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/grmiposelite_coco.py | """
GRMIPose (Google PoseNet) for COCO Keypoint, implemented in TensorFlow (Lite).
Original paper: 'Towards Accurate Multi-person Pose Estimation in the Wild,' https://arxiv.org/abs/1701.01779.
"""
__all__ = ['GRMIPoseLite', 'grmiposelite_mobilenet_w1_coco']
import math
import numpy as np
import tensorflow as... | 6,726 | 32.137931 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/bisenet.py | """
BiSeNet for CelebAMask-HQ, implemented in TensorFlow.
Original paper: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation,'
https://arxiv.org/abs/1808.00897.
"""
__all__ = ['BiSeNet', 'bisenet_resnet18_celebamaskhq']
import os
import tensorflow as tf
import tensorflow.keras.la... | 17,516 | 32.429389 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnet.py | """
ResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNet', 'resnet10', 'resnet12', 'resnet14', 'resnetbc14b', 'resnet16', 'resnet18_wd4', 'resnet18_wd2',
'resnet18_w3d4', 'resnet18'... | 27,599 | 32.948339 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/simpleposemobile_coco.py | """
SimplePose(Mobile) for COCO Keypoint, implemented in TensorFlow.
Original paper: 'Simple Baselines for Human Pose Estimation and Tracking,' https://arxiv.org/abs/1804.06208.
"""
__all__ = ['SimplePoseMobile', 'simplepose_mobile_resnet18_coco', 'simplepose_mobile_resnet50b_coco',
'simplepose_mobi... | 15,320 | 41.558333 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/cbamresnet.py | """
CBAM-ResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'CBAM: Convolutional Block Attention Module,' https://arxiv.org/abs/1807.06521.
"""
__all__ = ['CbamResNet', 'cbam_resnet18', 'cbam_resnet34', 'cbam_resnet50', 'cbam_resnet101', 'cbam_resnet152']
import os
import tensorflow as tf
impo... | 15,596 | 30.830612 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/diracnetv2.py | """
DiracNetV2 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'DiracNets: Training Very Deep Neural Networks Without Skip-Connections,'
https://arxiv.org/abs/1706.00388.
"""
__all__ = ['DiracNetV2', 'diracnet18v2', 'diracnet34v2']
import os
import tensorflow as tf
import tensorflow.keras.laye... | 9,781 | 30.152866 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/sepreresnet_cifar.py | """
SE-PreResNet for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['CIFARSEPreResNet', 'sepreresnet20_cifar10', 'sepreresnet20_cifar100', 'sepreresnet20_svhn',
'sepreresnet56_cifar10', 'sepreresnet56_cifar10... | 24,762 | 37.511664 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/danet.py | """
DANet for image segmentation, implemented in TensorFlow.
Original paper: 'Dual Attention Network for Scene Segmentation,' https://arxiv.org/abs/1809.02983.
"""
__all__ = ['DANet', 'danet_resnetd50b_cityscapes', 'danet_resnetd101b_cityscapes']
import os
import tensorflow as tf
import tensorflow.keras.layer... | 18,175 | 34.156673 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenetv2.py | """
MobileNetV2 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks,' https://arxiv.org/abs/1801.04381.
"""
__all__ = ['MobileNetV2', 'mobilenetv2_w1', 'mobilenetv2_w3d4', 'mobilenetv2_wd2', 'mobilenetv2_wd4', 'mobilenetv2b_w1',
'mobile... | 13,837 | 34.121827 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/squeezenet.py | """
SqueezeNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size,'
https://arxiv.org/abs/1602.07360.
"""
__all__ = ['SqueezeNet', 'squeezenet_v1_0', 'squeezenet_v1_1', 'squeezeresnet_v1_0', 'squeezeresnet_v1_1']
... | 13,417 | 32.212871 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/vgg.py | """
VGG for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Very Deep Convolutional Networks for Large-Scale Image Recognition,'
https://arxiv.org/abs/1409.1556.
"""
__all__ = ['VGG', 'vgg11', 'vgg13', 'vgg16', 'vgg19', 'bn_vgg11', 'bn_vgg13', 'bn_vgg16', 'bn_vgg19', 'bn_vgg11b',
'bn_vg... | 14,207 | 31 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnet_cub.py | """
ResNet for CUB-200-2011, implemented in TensorFlow.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['resnet10_cub', 'resnet12_cub', 'resnet14_cub', 'resnetbc14b_cub', 'resnet16_cub', 'resnet18_cub',
'resnet26_cub', 'resnetbc26b_cub... | 14,084 | 35.489637 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/bagnet.py | """
BagNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet,'
https://openreview.net/pdf?id=SkfMWhAqYQ.
"""
__all__ = ['BagNet', 'bagnet9', 'bagnet17', 'bagnet33']
import os
import tensorflow as tf
import ... | 12,719 | 31.868217 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/airnet.py | """
AirNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Attention Inspiring Receptive-Fields Network for Learning Invariant Representations,'
https://ieeexplore.ieee.org/document/8510896.
"""
__all__ = ['AirNet', 'airnet50_1x64d_r2', 'airnet50_1x64d_r16', 'airnet101_1x64d_r2', 'AirBlock', '... | 14,996 | 31.182403 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mnasnet.py | """
MnasNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MnasNet: Platform-Aware Neural Architecture Search for Mobile,' https://arxiv.org/abs/1807.11626.
"""
__all__ = ['MnasNet', 'mnasnet_b1', 'mnasnet_a1', 'mnasnet_small']
import os
import tensorflow as tf
import tensorflow.keras.layers as ... | 15,818 | 33.997788 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pyramidnet_cifar.py | """
PyramidNet for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
"""
__all__ = ['CIFARPyramidNet', 'pyramidnet110_a48_cifar10', 'pyramidnet110_a48_cifar100', 'pyramidnet110_a48_svhn',
'pyramidnet110_a84_cifar10', 'pyramid... | 24,103 | 32.711888 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/preresnet_cifar.py | """
PreResNet for CIFAR/SVHN, implemented in TensorFlow.
Original papers: 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
"""
__all__ = ['CIFARPreResNet', 'preresnet20_cifar10', 'preresnet20_cifar100', 'preresnet20_svhn',
'preresnet56_cifar10', 'preresnet56_cifar100'... | 24,758 | 36.11994 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/alphapose_coco.py | """
AlphaPose for COCO Keypoint, implemented in TensorFlow.
Original paper: 'RMPE: Regional Multi-person Pose Estimation,' https://arxiv.org/abs/1612.00137.
"""
__all__ = ['AlphaPose', 'alphapose_fastseresnet101b_coco']
import os
import tensorflow as tf
from .common import conv3x3, PixelShuffle, DucBlock, Hea... | 7,571 | 34.886256 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pyramidnet.py | """
PyramidNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
"""
__all__ = ['PyramidNet', 'pyramidnet101_a360', 'PyrUnit']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import Conv2d, Batc... | 13,503 | 30.699531 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnet.py | """
SE-ResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNet', 'seresnet10', 'seresnet12', 'seresnet14', 'seresnet16', 'seresnet18', 'seresnet26',
'seresnetbc26b', 'seresnet34', 'seresnetbc38b'... | 19,070 | 32.694346 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnet_cub.py | """
SE-ResNet for CUB-200-2011, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['seresnet10_cub', 'seresnet12_cub', 'seresnet14_cub', 'seresnetbc14b_cub', 'seresnet16_cub',
'seresnet18_cub', 'seresnet26_cub', 'seresnetbc2... | 14,111 | 35.942408 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/densenet.py | """
DenseNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Densely Connected Convolutional Networks,' https://arxiv.org/abs/1608.06993.
"""
__all__ = ['DenseNet', 'densenet121', 'densenet161', 'densenet169', 'densenet201', 'DenseUnit', 'TransitionBlock']
import os
import tensorflow as tf
import... | 11,289 | 32.011696 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnext.py | """
SE-ResNeXt for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNeXt', 'seresnext50_32x4d', 'seresnext101_32x4d', 'seresnext101_64x4d']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
fr... | 9,503 | 31.772414 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/drn.py | """
DRN for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Dilated Residual Networks,' https://arxiv.org/abs/1705.09914.
"""
__all__ = ['DRN', 'drnc26', 'drnc42', 'drnc58', 'drnd22', 'drnd38', 'drnd54', 'drnd105']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common im... | 21,693 | 30.44058 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mixnet.py | """
MixNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MixConv: Mixed Depthwise Convolutional Kernels,' https://arxiv.org/abs/1907.09595.
"""
__all__ = ['MixNet', 'mixnet_s', 'mixnet_m', 'mixnet_l']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import rou... | 23,110 | 34.886646 | 116 | py |
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