Functions — github.com/SakhriHoussem/Image-Classification

hub / github.com/SakhriHoussem/Image-Classification / functions

Functions44 in github.com/SakhriHoussem/Image-Classification

⨍ Functions 44 ◇ Types & classes 4

↓ 16 callersMethodconv_layer

(self, bottom, in_channels, out_channels, name)

vgg19/vgg19_trainable.py:108

↓ 16 callersMethodconv_layer

(self, bottom, name)

vgg19/vgg19.py:94

↓ 13 callersMethodconv_layer

(self, bottom, in_channels, out_channels, name)

vgg16/vgg16_trainable.py:104

↓ 13 callersMethodconv_layer

(self, bottom, name)

vgg16/vgg16.py:90

↓ 6 callersMethodbuild

load variable from npy to build the VGG :param rgb: rgb image [batch, height, width, 3] values scaled [0, 1]

vgg16/vgg16.py:22

↓ 5 callersMethodfc_layer

(self, bottom, in_size, out_size, name)

vgg16/vgg16_trainable.py:114

↓ 5 callersMethodfc_layer

(self, bottom, in_size, out_size, name)

vgg19/vgg19_trainable.py:118

↓ 5 callersMethodmax_pool

(self, bottom, name)

vgg16/vgg16_trainable.py:101

↓ 5 callersMethodmax_pool

(self, bottom, name)

vgg16/vgg16.py:87

↓ 5 callersMethodmax_pool

(self, bottom, name)

vgg19/vgg19_trainable.py:105

↓ 5 callersMethodmax_pool

(self, bottom, name)

vgg19/vgg19.py:91

↓ 5 callersMethodsave_npy

(self, sess, npy_path="./vgg16-save.npy")

vgg16/vgg16_trainable.py:161

↓ 4 callersMethodget_var

(self, initial_value, name, idx, var_name)

vgg16/vgg16_trainable.py:141

↓ 4 callersMethodget_var

(self, initial_value, name, idx, var_name)

vgg19/vgg19_trainable.py:145

↓ 3 callersMethodfc_layer

(self, bottom, name)

vgg16/vgg16.py:102

↓ 3 callersMethodfc_layer

(self, bottom, name)

vgg19/vgg19.py:106

↓ 2 callersFunctionClusterGen

function to generate list of IP addresses for workers and parameters servers from Devices name :param list[str] workers: list of workers De

Networking.py:16

↓ 2 callersMethodget_bias

(self, name)

vgg16/vgg16.py:122

↓ 2 callersMethodget_bias

(self, name)

vgg19/vgg19.py:126

↓ 1 callersFunctiondraw_table

:param data: :param classes: :param save_as: :param save_to: :return:

dataSetGenerator.py:1

↓ 1 callersMethodget_conv_filter

(self, name)

vgg16/vgg16.py:119

↓ 1 callersMethodget_conv_filter

(self, name)

vgg19/vgg19.py:123

↓ 1 callersMethodget_conv_var

(self, filter_size, in_channels, out_channels, name)

vgg16/vgg16_trainable.py:123

↓ 1 callersMethodget_conv_var

(self, filter_size, in_channels, out_channels, name)

vgg19/vgg19_trainable.py:127

↓ 1 callersMethodget_fc_var

(self, in_size, out_size, name)

vgg16/vgg16_trainable.py:132

↓ 1 callersMethodget_fc_var

(self, in_size, out_size, name)

vgg19/vgg19_trainable.py:136

↓ 1 callersMethodget_fc_weight

(self, name)

vgg16/vgg16.py:125

↓ 1 callersMethodget_fc_weight

(self, name)

vgg19/vgg19.py:129

↓ 1 callersMethodget_var_count

(self)

vgg16/vgg16_trainable.py:176

↓ 1 callersFunctioninMyNetwork

generate list of devices and there IP addresses who connected with you in the same Network :param str() hosts: string for hosts as nmap use

Networking.py:4

Method__init__

(self, vgg16_npy_path=None,output = 1000, trainable=True, dropout=0.5)

vgg16/vgg16_trainable.py:13

Method__init__

(self, vgg16_npy_path=None)

vgg16/vgg16.py:11

Method__init__

(self, vgg19_npy_path=None,output = 1000, trainable=True, dropout=0.5)

vgg19/vgg19_trainable.py:13

Method__init__

(self, vgg19_npy_path=None)

vgg19/vgg19.py:11

Methodavg_pool

(self, bottom, name)

vgg16/vgg16_trainable.py:98

vgg19/vgg19_trainable.py:102

load variable from npy to build the VGG :param rgb: rgb image [batch, height, width, 3] values scaled [0, 1] :param train_mo

vgg16/vgg16_trainable.py:23

Methodbuild

load variable from npy to build the VGG :param rgb: rgb image [batch, height, width, 3] values scaled [0, 1] :param train_mo

vgg19/vgg19_trainable.py:24

Methodbuild

load variable from npy to build the VGG :param rgb: rgb image [batch, height, width, 3] values scaled [0, 1]

vgg19/vgg19.py:22

FunctiondataSetGenerator

Generate a image dataSet from a picture dataSets the picture dataSets must be in the same structure to generate also labels example of

dataSetGenerator.py:1

Methodget_var_count

(self)

vgg19/vgg19_trainable.py:177

Methodsave_npy

(self, sess, npy_path="./vgg19-save.npy")

vgg19/vgg19_trainable.py:162