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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imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnesta.py | """
ResNeSt(A) with average downsampling for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ResNeSt: Split-Attention Networks,' https://arxiv.org/abs/2004.08955.
"""
__all__ = ['ResNeStA', 'resnestabc14', 'resnesta18', 'resnestabc26', 'resnesta50', 'resnesta101', 'resnesta152',
'resnesta20... | 19,800 | 32.561017 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/senet.py | """
SENet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SENet', 'senet16', 'senet28', 'senet40', 'senet52', 'senet103', 'senet154', 'SEInitBlock']
import os
import math
import tensorflow as tf
import tensorflow.... | 15,060 | 30.574423 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/simplepose_coco.py | """
SimplePose for COCO Keypoint, implemented in TensorFlow.
Original paper: 'Simple Baselines for Human Pose Estimation and Tracking,' https://arxiv.org/abs/1804.06208.
"""
__all__ = ['SimplePose', 'simplepose_resnet18_coco', 'simplepose_resnet50b_coco', 'simplepose_resnet101b_coco',
'simplepose_re... | 15,180 | 40.252717 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/vovnet.py | """
VoVNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection,'
https://arxiv.org/abs/1904.09730.
"""
__all__ = ['VoVNet', 'vovnet27s', 'vovnet39', 'vovnet57']
import os
import tensorflow as tf
import tensorf... | 11,511 | 31.519774 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/espnetv2.py | """
ESPNetv2 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network,'
https://arxiv.org/abs/1811.11431.
NB: not ready.
"""
__all__ = ['ESPNetv2', 'espnetv2_wd2', 'espnetv2_w1', 'espnetv2_w5d4', 'espnetv2_w... | 20,454 | 32.260163 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/shufflenet.py | """
ShuffleNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices,'
https://arxiv.org/abs/1707.01083.
"""
__all__ = ['ShuffleNet', 'shufflenet_g1_w1', 'shufflenet_g2_w1', 'shufflenet_g3_w1', 'shufflenet_g4_w1',
... | 17,521 | 33.089494 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/bamresnet.py | """
BAM-ResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'BAM: Bottleneck Attention Module,' https://arxiv.org/abs/1807.06514.
"""
__all__ = ['BamResNet', 'bam_resnet18', 'bam_resnet34', 'bam_resnet50', 'bam_resnet101', 'bam_resnet152']
import os
import tensorflow as tf
import tensorflow.ker... | 15,973 | 30.757455 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/centernet.py | """
CenterNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Objects as Points,' https://arxiv.org/abs/1904.07850.
"""
__all__ = ['CenterNet', 'centernet_resnet18_voc', 'centernet_resnet18_coco', 'centernet_resnet50b_voc',
'centernet_resnet50b_coco', 'centernet_resnet101b_voc', 'center... | 20,073 | 35.039497 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/proxylessnas_cub.py | """
ProxylessNAS for CUB-200-2011, implemented in TensorFlow.
Original paper: 'ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware,'
https://arxiv.org/abs/1812.00332.
"""
__all__ = ['proxylessnas_cpu_cub', 'proxylessnas_gpu_cub', 'proxylessnas_mobile_cub', 'proxylessnas_mobile14_cub... | 4,145 | 34.741379 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibnresnet.py | """
IBN-ResNet 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__ = ['IBNResNet', 'ibn_resnet50', 'ibn_resnet101', 'ibn_resnet152']
import os
import tensorflow as tf
import t... | 14,465 | 31.290179 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/common.py | """
Common routines for models in TensorFlow 2.0.
"""
__all__ = ['is_channels_first', 'get_channel_axis', 'round_channels', 'get_im_size', 'interpolate_im', 'BreakBlock',
'ReLU6', 'HSwish', 'PReLU2', 'get_activation_layer', 'flatten', 'MaxPool2d', 'AvgPool2d', 'GlobalAvgPool2d',
'BatchNorm', ... | 116,234 | 32.858142 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/lwopenpose_cmupan.py | """
Lightweight OpenPose 2D/3D for CMU Panoptic, implemented in TensorFlow.
Original paper: 'Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose,'
https://arxiv.org/abs/1811.12004.
"""
__all__ = ['LwOpenPose', 'lwopenpose2d_mobilenet_cmupan_coco', 'lwopenpose3d_mobilenet_cmupan_coco',
... | 26,896 | 34.344284 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/jasperdr.py | """
Jasper DR (Dense Residual) for ASR, implemented in TensorFlow.
Original paper: 'Jasper: An End-to-End Convolutional Neural Acoustic Model,' https://arxiv.org/abs/1904.03288.
"""
__all__ = ['jasperdr10x5_en', 'jasperdr10x5_en_nr']
from .jasper import get_jasper
from .common import is_channels_first
def j... | 3,268 | 33.410526 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/deeplabv3.py | """
DeepLabv3 for image segmentation, implemented in TensorFlow.
Original paper: 'Rethinking Atrous Convolution for Semantic Image Segmentation,' https://arxiv.org/abs/1706.05587.
"""
__all__ = ['DeepLabv3', 'deeplabv3_resnetd50b_voc', 'deeplabv3_resnetd101b_voc', 'deeplabv3_resnetd152b_voc',
'deepl... | 26,559 | 40.178295 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fpenet.py | """
FPENet for image segmentation, implemented in TensorFlow.
Original paper: 'Feature Pyramid Encoding Network for Real-time Semantic Segmentation,'
https://arxiv.org/abs/1909.08599.
"""
__all__ = ['FPENet', 'fpenet_cityscapes']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from ... | 15,897 | 31.378819 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fastseresnet.py | """
Fast-SE-ResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['FastSEResNet', 'fastseresnet101b']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import conv1x1_block, SEBlo... | 10,194 | 31.887097 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibnbresnet.py | """
IBN(b)-ResNet 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__ = ['IBNbResNet', 'ibnb_resnet50', 'ibnb_resnet101', 'ibnb_resnet152']
import os
import tensorflow as tf
i... | 13,824 | 31.377049 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/polynet.py | """
PolyNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'PolyNet: A Pursuit of Structural Diversity in Very Deep Networks,'
https://arxiv.org/abs/1611.05725.
"""
__all__ = ['PolyNet', 'polynet']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import MaxP... | 37,828 | 30.576795 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnet_cifar.py | """
ResNet for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['CIFARResNet', 'resnet20_cifar10', 'resnet20_cifar100', 'resnet20_svhn',
'resnet56_cifar10', 'resnet56_cifar100', 'resnet56_svhn',
... | 23,420 | 35.883465 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/nasnet.py | """
NASNet-A for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Learning Transferable Architectures for Scalable Image Recognition,'
https://arxiv.org/abs/1707.07012.
"""
__all__ = ['NASNet', 'nasnet_4a1056', 'nasnet_6a4032', 'nasnet_dual_path_sequential']
import os
import tensorflow as tf
impor... | 52,300 | 31.047181 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnext_cifar.py | """
ResNeXt for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Aggregated Residual Transformations for Deep Neural Networks,' http://arxiv.org/abs/1611.05431.
"""
__all__ = ['CIFARResNeXt', 'resnext20_1x64d_cifar10', 'resnext20_1x64d_cifar100', 'resnext20_1x64d_svhn',
'resnext20_2x32d_cifar... | 65,482 | 38.904327 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/densenet_cifar.py | """
DenseNet for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Densely Connected Convolutional Networks,' https://arxiv.org/abs/1608.06993.
"""
__all__ = ['CIFARDenseNet', 'densenet40_k12_cifar10', 'densenet40_k12_cifar100', 'densenet40_k12_svhn',
'densenet40_k12_bc_cifar10', 'densenet40_k... | 30,185 | 37.16182 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/bninception.py | """
BN-Inception for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift,'
https://arxiv.org/abs/1502.03167.
"""
__all__ = ['BNInception', 'bninception']
import os
import tensorflow as tf
import tensorflow.ke... | 19,733 | 31.726368 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/zfnet.py | """
ZFNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Visualizing and Understanding Convolutional Networks,' https://arxiv.org/abs/1311.2901.
"""
__all__ = ['zfnet', 'zfnetb']
import os
import tensorflow as tf
from .alexnet import AlexNet
def get_zfnet(version="a",
model_name=... | 3,844 | 29.275591 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/peleenet.py | """
PeleeNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Pelee: A Real-Time Object Detection System on Mobile Devices,' https://arxiv.org/abs/1804.06882.
"""
__all__ = ['PeleeNet', 'peleenet']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import conv1x1_b... | 13,598 | 30.552204 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibppose_coco.py | """
IBPPose for COCO Keypoint, implemented in TensorFlow.
Original paper: 'Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation,'
https://arxiv.org/abs/1911.10529.
"""
__all__ = ['IbpPose', 'ibppose_coco']
import os
import tensorflow as tf
import tensorflow.keras.lay... | 22,000 | 31.402062 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/xception.py | """
Xception for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Xception: Deep Learning with Depthwise Separable Convolutions,' https://arxiv.org/abs/1610.02357.
"""
__all__ = ['Xception', 'xception']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import Conv2d, ... | 14,191 | 30.191209 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/darknet53.py | """
DarkNet-53 for ImageNet-1K, implemented in TensorFlow.
Original source: 'YOLOv3: An Incremental Improvement,' https://arxiv.org/abs/1804.02767.
"""
__all__ = ['DarkNet53', 'darknet53']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import conv1x1_block, conv3x3_block, ... | 7,225 | 31.54955 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenet.py | """
MobileNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications,'
https://arxiv.org/abs/1704.04861.
"""
__all__ = ['MobileNet', 'mobilenet_w1', 'mobilenet_w3d4', 'mobilenet_wd2', 'mobilenet_wd4', 'get_mobilenet']
... | 8,450 | 33.493878 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/dpn.py | """
DPN for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Dual Path Networks,' https://arxiv.org/abs/1707.01629.
"""
__all__ = ['DPN', 'dpn68', 'dpn68b', 'dpn98', 'dpn107', 'dpn131']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import MaxPool2d, GlobalAvgPool2... | 23,478 | 30.056878 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/sknet.py | """
SKNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Selective Kernel Networks,' https://arxiv.org/abs/1903.06586.
"""
__all__ = ['SKNet', 'sknet50', 'sknet101', 'sknet152']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import conv1x1, conv1x1_block, con... | 13,222 | 31.09466 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/spnasnet.py | """
Single-Path NASNet for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as nn
... | 12,190 | 32.491758 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fastscnn.py | """
Fast-SCNN for image segmentation, implemented in TensorFlow.
Original paper: 'Fast-SCNN: Fast Semantic Segmentation Network,' https://arxiv.org/abs/1902.04502.
"""
__all__ = ['FastSCNN', 'fastscnn_cityscapes']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import conv1... | 19,829 | 31.831126 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/darknet.py | """
DarkNet for ImageNet-1K, implemented in TensorFlow.
Original source: 'Darknet: Open source neural networks in c,' https://github.com/pjreddie/darknet.
"""
__all__ = ['DarkNet', 'darknet_ref', 'darknet_tiny', 'darknet19']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common i... | 8,916 | 32.148699 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/dicenet.py | """
DiCENet for ImageNet-1K, implemented in TensorFlow.
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... | 29,544 | 31.431394 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/nvpattexp.py | """
Neural Voice Puppetry Audio-to-Expression net for speech-driven facial animation, implemented in TensorFlow.
Original paper: 'Neural Voice Puppetry: Audio-driven Facial Reenactment,' https://arxiv.org/abs/1912.05566.
"""
__all__ = ['NvpAttExp', 'nvpattexp116bazel76']
import os
import tensorflow as tf
impo... | 10,488 | 34.435811 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/alexnet.py | """
AlexNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'One weird trick for parallelizing convolutional neural networks,'
https://arxiv.org/abs/1404.5997.
"""
__all__ = ['AlexNet', 'alexnet', 'alexnetb']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common i... | 10,247 | 29.960725 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenet_cub.py | """
MobileNet & FD-MobileNet for CUB-200-2011, implemented in TensorFlow.
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://arxi... | 7,245 | 35.969388 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/wrn.py | """
WRN for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Wide Residual Networks,' https://arxiv.org/abs/1605.07146.
"""
__all__ = ['WRN', 'wrn50_2']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import Conv2d, MaxPool2d, SimpleSequential, flatten, is_channels_... | 13,742 | 28.941176 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionv3.py | """
InceptionV3 for ImageNet-1K, implemented in TensorFlow.
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 tenso... | 26,989 | 31.715152 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fdmobilenet.py | """
FD-MobileNet for ImageNet-1K, implemented in TensorFlow.
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
impor... | 4,966 | 31.677632 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/metrics/cls_metrics.py | """
Evaluation Metrics for Image Classification.
"""
import tensorflow as tf
from .metric import EvalMetric
__all__ = ['Top1Error', 'TopKError']
class Accuracy(EvalMetric):
"""
Computes accuracy classification score.
Parameters:
----------
axis : int, default 1
The axis that represents ... | 6,552 | 29.621495 | 95 | py |
imgclsmob | imgclsmob-master/tensorflow2/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/tensorflow2/datasets/imagenet1k_cls_dataset.py | """
ImageNet-1K classification dataset.
"""
__all__ = ['ImageNet1KMetaInfo', 'load_image_imagenet1k_val']
import os
import math
import cv2
import numpy as np
from PIL import Image
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import keras_preprocessing as keras_prep
from .dataset_metainfo im... | 11,999 | 30.496063 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/coco_hpe1_dataset.py | """
COCO keypoint detection (2D single human pose estimation) dataset.
"""
import os
import threading
import copy
import cv2
import numpy as np
from tensorflow.keras.preprocessing.image import ImageDataGenerator, DirectoryIterator
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe1Dataset(object):
"... | 37,195 | 33.282028 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/seg_dataset.py | import random
import threading
import numpy as np
from PIL import Image, ImageOps, ImageFilter
from tensorflow.keras.preprocessing.image import ImageDataGenerator, DirectoryIterator
class SegDataset(object):
"""
Segmentation base dataset.
Parameters:
----------
root : str
Path to data fol... | 7,631 | 33.378378 | 89 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/coco_hpe2_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for Lightweight OpenPose).
"""
import os
import json
import math
import threading
import cv2
from operator import itemgetter
import numpy as np
from tensorflow.keras.preprocessing.image import ImageDataGenerator, DirectoryIterator
from .datas... | 27,367 | 37.011111 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/coco_hpe3_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for IBPPose).
"""
import os
import threading
import math
import cv2
import numpy as np
from tensorflow.keras.preprocessing.image import ImageDataGenerator, DirectoryIterator
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe3Datase... | 29,689 | 37.408797 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/cifar10_cls_dataset.py | """
CIFAR-10 classification dataset.
"""
from tensorflow.keras.datasets import cifar10
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from .dataset_metainfo import DatasetMetaInfo
from .cls_dataset import img_normalization
class CIFAR10MetaInfo(DatasetMetaInfo):
def __init__(self):
... | 4,434 | 27.798701 | 67 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/cub200_2011_cls_dataset.py | """
CUB-200-2011 classification dataset.
"""
import os
import numpy as np
import pandas as pd
import threading
from tensorflow.keras.preprocessing.image import ImageDataGenerator, DirectoryIterator
from .cls_dataset import img_normalization
from .imagenet1k_cls_dataset import ImageNet1KMetaInfo
class CUBDirector... | 10,350 | 32.070288 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/datasets/cifar100_cls_dataset.py | """
CIFAR-100 classification dataset.
"""
from tensorflow.keras.datasets import cifar100
from .cifar10_cls_dataset import CIFAR10MetaInfo
class CIFAR100MetaInfo(CIFAR10MetaInfo):
def __init__(self):
super(CIFAR100MetaInfo, self).__init__()
self.label = "CIFAR100"
self.root_dir_name = ... | 1,963 | 24.179487 | 55 | py |
imgclsmob | imgclsmob-master/examples/convert_tf2_to_tfl.py | """
Script for converting trained model from TensorFlow 2.0 to TensorFlow Lite.
"""
import argparse
import numpy as np
import tensorflow as tf
from tf2cv.model_provider import get_model as tf2cv_get_model
from tensorflow2.utils import prepare_model
def parse_args():
"""
Create python script parameters.
... | 3,835 | 29.204724 | 106 | py |
imgclsmob | imgclsmob-master/examples/demo_pt.py | """
Script for evaluating trained model on PyTorch / ImageNet-1K (demo mode).
"""
import math
import argparse
import numpy as np
import cv2
import torch
from gluoncv.data import ImageNet1kAttr
from pytorchcv.model_provider import get_model as ptcv_get_model
def parse_args():
"""
Create python script para... | 3,876 | 27.094203 | 119 | py |
imgclsmob | imgclsmob-master/examples/demo_gl.py | """
Script for evaluating trained model on MXNet/Gluon / ImageNet-1K (demo mode).
"""
import math
import argparse
import numpy as np
import cv2
import mxnet as mx
from gluoncv.data import ImageNet1kAttr
from gluoncv2.model_provider import get_model as glcv2_get_model
def parse_args():
"""
Create python s... | 3,841 | 27.887218 | 119 | py |
imgclsmob | imgclsmob-master/other/train_pt_cifar-.py | import argparse
import time
import logging
import os
import warnings
import random
import numpy as np
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.utils.data
from common.logger_utils import initialize_logging
from common.train_log_param_saver import TrainLogParamSaver
from pytorch.cifar1 im... | 15,172 | 30.092213 | 105 | py |
imgclsmob | imgclsmob-master/other/train_gl_seg.py | import os
import shutil
import argparse
from tqdm import tqdm
import mxnet as mx
from mxnet import gluon, autograd
from mxnet.gluon.data.vision import transforms
import gluoncv
from gluoncv.loss import MixSoftmaxCrossEntropyLoss
from gluoncv.utils import LRScheduler
from gluoncv.model_zoo.segbase import get_segmentat... | 9,856 | 43.201794 | 120 | py |
imgclsmob | imgclsmob-master/other/train_gl_cifar-.py | import argparse
import time
import logging
import os
import numpy as np
import random
import mxnet as mx
from mxnet import gluon
from mxnet import autograd as ag
from common.logger_utils import initialize_logging
from common.train_log_param_saver import TrainLogParamSaver
from gluon.lr_scheduler import LRScheduler
fr... | 22,007 | 31.798808 | 119 | py |
imgclsmob | imgclsmob-master/other/eval_pt_seg-.py | import argparse
import time
import logging
from common.logger_utils import initialize_logging
from pytorch.model_stats import measure_model
from pytorch.seg_utils import add_dataset_parser_arguments, get_test_data_loader, get_metainfo, validate1
from pytorch.utils import prepare_pt_context, prepare_model, calc_net_wei... | 7,218 | 33.706731 | 111 | py |
imgclsmob | imgclsmob-master/other/eval_gl_mch.py | """
Script for evaluating trained image matching model on MXNet/Gluon (under development).
"""
import os
import time
import logging
import argparse
import numpy as np
import mxnet as mx
from mxnet.gluon.utils import split_and_load
from common.logger_utils import initialize_logging
from gluon.utils import prepare_m... | 9,800 | 30.213376 | 116 | py |
imgclsmob | imgclsmob-master/other/eval_gl_seg-.py | import os
import argparse
import time
import logging
import mxnet as mx
from common.logger_utils import initialize_logging
from gluon.utils import prepare_mx_context, prepare_model, calc_net_weight_count
from gluon.model_stats import measure_model
from gluon.seg_utils1 import add_dataset_parser_arguments, get_metainfo
... | 7,626 | 32.897778 | 111 | py |
imgclsmob | imgclsmob-master/other/eval_pt_cifar-.py | import argparse
import time
import logging
from common.logger_utils import initialize_logging
from pytorch.model_stats import measure_model
from pytorch.cifar1 import add_dataset_parser_arguments, get_val_data_loader
from pytorch.utils import prepare_pt_context, prepare_model, calc_net_weight_count, validate1, Average... | 5,894 | 30.524064 | 107 | py |
imgclsmob | imgclsmob-master/other/eval_pt_mch.py | """
Script for evaluating trained image matching model on PyTorch (under development).
"""
import os
import time
import logging
import argparse
import numpy as np
import torch
from common.logger_utils import initialize_logging
from pytorch.utils import prepare_pt_context, prepare_model
from pytorch.dataset_utils i... | 19,664 | 35.620112 | 98 | py |
imgclsmob | imgclsmob-master/other/eval_pt_cub-.py | import argparse
import time
import logging
from common.logger_utils import initialize_logging
from pytorch.model_stats import measure_model
from pytorch.cub200_2011_utils1 import add_dataset_parser_arguments, get_val_data_loader
from pytorch.utils import prepare_pt_context, prepare_model, calc_net_weight_count, Averag... | 7,660 | 32.748899 | 103 | py |
imgclsmob | imgclsmob-master/other/chainer_/train_ch_in1k.py | import argparse
import numpy as np
import chainer
from chainer import cuda
from chainer import training
from chainer.training import extensions
from chainer.serializers import save_npz
from common.logger_utils import initialize_logging
from chainer_.utils import prepare_model
from chainer_.imagenet1k1 import add_data... | 9,308 | 29.224026 | 115 | py |
imgclsmob | imgclsmob-master/other/chainer_/train_ch_cifar.py | import argparse
import numpy as np
import chainer
from chainer import cuda
from chainer import training
from chainer.training import extensions
from chainer.serializers import save_npz
from common.logger_utils import initialize_logging
from chainer_.utils import prepare_model
from chainer_.cifar1 import add_dataset_p... | 9,190 | 28.744337 | 115 | py |
imgclsmob | imgclsmob-master/other/gluon/seg_utils1.py | """
Segmentation datasets (VOC2012/ADE20K/Cityscapes/COCO) routines.
"""
__all__ = ['add_dataset_parser_arguments', 'batch_fn', 'get_test_data_source', 'get_num_training_samples', 'validate1',
'get_metainfo']
from tqdm import tqdm
from mxnet import gluon
from mxnet.gluon.data.vision import transforms
f... | 5,809 | 31.640449 | 119 | py |
imgclsmob | imgclsmob-master/other/gluon/khpa/khpa_utils.py | """
KHPA dataset routines.
"""
__all__ = ['add_dataset_parser_arguments', 'get_batch_fn', 'get_train_data_source', 'get_val_data_source', 'validate']
import math
from mxnet import gluon
from gluon.weighted_random_sampler import WeightedRandomSampler
from other.gluon.khpa.khpa_cls_dataset import KHPA
def add_dat... | 6,499 | 33.210526 | 118 | py |
imgclsmob | imgclsmob-master/other/gluon/khpa/khpa_cls_dataset.py | """
KHPA classification dataset.
"""
import os
import json
import logging
import numpy as np
import pandas as pd
import mxnet as mx
from mxnet.gluon.data import Dataset
from imgaug import augmenters as iaa
from imgaug import parameters as iap
class KHPA(Dataset):
"""
Load the KHPA classification dataset.... | 20,192 | 41.511579 | 104 | py |
imgclsmob | imgclsmob-master/other/gluon/khpa/eval_gl_khpa.py | import argparse
import time
import logging
import mxnet as mx
from common.logger_utils import initialize_logging
from gluon.utils import prepare_mx_context, prepare_model, calc_net_weight_count
from other.gluon.khpa.khpa_utils import add_dataset_parser_arguments
from other.gluon.khpa.khpa_utils import get_batch_fn
fr... | 4,686 | 27.23494 | 101 | py |
imgclsmob | imgclsmob-master/other/gluon/khpa/train_gl_khpa.py | import argparse
import time
import logging
import os
import numpy as np
import random
import mxnet as mx
from mxnet import gluon
from mxnet import autograd as ag
from common.logger_utils import initialize_logging
from common.train_log_param_saver import TrainLogParamSaver
from gluon.lr_scheduler import LRScheduler
fr... | 19,879 | 31.012882 | 105 | py |
imgclsmob | imgclsmob-master/other/pytorch/imagenet1k1.py | import math
import os
import cv2
import numpy as np
from PIL import Image
import torch.utils.data
import torchvision.transforms as transforms
import torchvision.datasets as datasets
__all__ = ['add_dataset_parser_arguments', 'get_train_data_loader', 'get_val_data_loader']
def add_dataset_parser_arguments(parser):
... | 5,152 | 27.469613 | 90 | py |
imgclsmob | imgclsmob-master/other/pytorch/cub200_2011_utils1.py | """
CUB-200-2011 fine-grained classification dataset routines.
"""
__all__ = ['add_dataset_parser_arguments', 'get_train_data_loader', 'get_val_data_loader']
import math
import torch.utils.data
import torchvision.transforms as transforms
from pytorch.datasets.cub200_2011_cls_dataset import CUB200_2011
def add_d... | 3,014 | 26.409091 | 90 | py |
imgclsmob | imgclsmob-master/other/pytorch/cifar1.py | """
CIFAR/SVHN dataset routines.
"""
import torch.utils.data
import torchvision.transforms as transforms
import torchvision.datasets as datasets
__all__ = ['add_dataset_parser_arguments', 'get_train_data_loader', 'get_val_data_loader']
def add_dataset_parser_arguments(parser,
da... | 4,409 | 28.205298 | 90 | py |
imgclsmob | imgclsmob-master/other/pytorch/seg_utils.py | """
Segmentation datasets (VOC2012/ADE20K/Cityscapes/COCO) routines.
"""
__all__ = ['add_dataset_parser_arguments', 'get_test_data_loader', 'validate1', 'get_metainfo']
from tqdm import tqdm
import torch.utils.data
import torchvision.transforms as transforms
from pytorch.datasets.voc_seg_dataset import VOCSegData... | 5,401 | 31.347305 | 95 | py |
imgclsmob | imgclsmob-master/tensorflow_/utils_tp.py | import math
import logging
import os
import multiprocessing
import numpy as np
import cv2
import tensorflow as tf
from tensorpack.models import regularize_cost
from tensorpack.tfutils.summary import add_moving_summary
# from tensorpack.tfutils.summary import add_tensor_summary
from tensorpack import ModelDesc, get_cur... | 12,668 | 36.482249 | 108 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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 ... | 14,880 | 29.745868 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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
from .c... | 12,086 | 30.313472 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/preresnet.py | """
PreResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
"""
__all__ = ['PreResNet', 'preresnet10', 'preresnet12', 'preresnet14', 'preresnetbc14b', 'preresnet16', 'preresnet18_wd4',
'preresnet18_wd2', '... | 31,739 | 30.645065 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/shufflenetv2b.py | """
ShuffleNet V2 for ImageNet-1K, implemented in TensorFlow. The alternative variant.
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'... | 15,582 | 29.980119 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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... | 19,323 | 29.86901 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/channelnet.py | """
ChannelNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions,'
https://arxiv.org/abs/1809.01330.
"""
__all__ = ['ChannelNet', 'channelnet']
import os
import tensorflow as tf
from .common import co... | 24,927 | 30.16 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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... | 15,382 | 29.704591 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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'... | 29,772 | 29.85285 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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']
import os
import tensorflow as tf
fr... | 12,232 | 30.939948 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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']
... | 14,788 | 29.810417 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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... | 15,566 | 30.576065 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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
from .common import is_channels_fi... | 17,642 | 32.478178 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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'... | 21,991 | 30.194326 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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']
import os
import tensorflow as tf
from .common import pre_conv1x1_block,... | 13,065 | 29.816038 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/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
from .common import conv1x1_block, se_b... | 10,990 | 30.048023 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/mobilenetv3.py | """
MobileNetV3 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
"""
__all__ = ['MobileNetV3', 'mobilenetv3_small_w7d20', 'mobilenetv3_small_wd2', 'mobilenetv3_small_w3d4',
'mobilenetv3_small_w1', 'mobilenetv3_small_w5d4', 'mo... | 22,437 | 33.048558 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/sepreresnet.py | """
SE-PreResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEPreResNet', 'sepreresnet10', 'sepreresnet12', 'sepreresnet14', 'sepreresnet16', 'sepreresnet18',
'sepreresnet26', 'sepreresnetbc26b', 's... | 22,299 | 30.766382 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/resnext.py | """
ResNeXt for ImageNet-1K, implemented in TensorFlow.
Original papers: 'Aggregated Residual Transformations for Deep Neural Networks,' http://arxiv.org/abs/1611.05431.
"""
__all__ = ['ResNeXt', 'resnext14_16x4d', 'resnext14_32x2d', 'resnext14_32x4d', 'resnext26_16x4d', 'resnext26_32x2d',
'resnext2... | 18,384 | 30.320273 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/senet.py | """
SENet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SENet', 'senet16', 'senet28', 'senet40', 'senet52', 'senet103', 'senet154']
import os
import math
import tensorflow as tf
from .common import conv1x1_block... | 16,887 | 28.16753 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/shufflenet.py | """
ShuffleNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices,'
https://arxiv.org/abs/1707.01083.
"""
__all__ = ['ShuffleNet', 'shufflenet_g1_w1', 'shufflenet_g2_w1', 'shufflenet_g3_w1', 'shufflenet_g4_w1',
... | 19,344 | 30.151369 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/common.py | """
Common routines for models in TensorFlow.
"""
__all__ = ['round_channels', 'hswish', 'is_channels_first', 'get_channel_axis', 'flatten', 'batchnorm', 'maxpool2d',
'avgpool2d', 'conv2d', 'conv1x1', 'conv3x3', 'depthwise_conv3x3', 'conv_block', 'conv1x1_block',
'conv3x3_block', 'conv7x7_blo... | 39,625 | 28.265879 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/darknet53.py | """
DarkNet-53 for ImageNet-1K, implemented in TensorFlow.
Original source: 'YOLOv3: An Incremental Improvement,' https://arxiv.org/abs/1804.02767.
"""
__all__ = ['DarkNet53', 'darknet53']
import os
import tensorflow as tf
from .common import conv1x1_block, conv3x3_block, is_channels_first, flatten
def dark... | 8,796 | 31.223443 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/mobilenet.py | """
MobileNet & FD-MobileNet for ImageNet-1K, implemented in TensorFlow.
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... | 14,167 | 31.645161 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/darknet.py | """
DarkNet for ImageNet-1K, implemented in TensorFlow.
Original source: 'Darknet: Open source neural networks in c,' https://github.com/pjreddie/darknet.
"""
__all__ = ['DarkNet', 'darknet_ref', 'darknet_tiny', 'darknet19']
import os
import tensorflow as tf
from .common import conv2d, maxpool2d, conv1x1_bloc... | 10,892 | 31.038235 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow_/tensorflowcv/models/alexnet.py | """
AlexNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'One weird trick for parallelizing convolutional neural networks,'
https://arxiv.org/abs/1404.5997.
"""
__all__ = ['AlexNet', 'alexnet', 'alexnetb']
import os
import tensorflow as tf
from .common import maxpool2d, conv_block, is_chann... | 11,485 | 28.603093 | 116 | py |
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