sunshinejnjn

Not just an Universal MediaCreationTool wrapper script with ingenious support for business editions,

A powerful yet simple windows 10 / 11 deployment automation tool as well!

configure via set vars, commandline parameters or rename script like iso 21H2 Pro MediaCreationTool.bat
recommended windows setup options with the least amount of issues on upgrades already set
awesome keyboard focus dialogs to pick windows version and enhanced preset action

Auto Setup for upgrading directly with the auto-detected Edition, Language, Architecture *
- can troubleshoot auto setup failing by adding no_update to script name

sunshinejnjn

from keras import backend as K
from keras import activations, initializations, regularizers, constraints
from keras.engine import Layer, InputSpec
from keras.utils.np_utils import conv_output_length
from keras.layers import Convolution1D, Convolution2D
import tensorflow as tf

class Convolution1D_tied(Layer):
    '''Convolution operator for filtering neighborhoods of one-dimensional inputs.
    When using this layer as the first layer in a model,

sunshinejnjn

# -*- coding: utf-8 -*-

import cv2
import numpy as np
import copy

from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Flatten, Activation, add
from keras.optimizers import SGD
from keras.layers.normalization import BatchNormalization
from keras.models import Model

sunshinejnjn

ResNet-152 in Keras

This is an Keras implementation of ResNet-152 with ImageNet pre-trained weights. I converted the weights from Caffe provided by the authors of the paper. The implementation supports both Theano and TensorFlow backends. Just in case you are curious about how the conversion is done, you can visit my blog post for more details.

ResNet Paper:

Deep Residual Learning for Image Recognition.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
arXiv:1512.03385