goodhamgupta

# Script to convert yolo annotations to voc format

# Sample format
# <annotation>
#     <folder>_image_fashion</folder>
#     <filename>brooke-cagle-39574.jpg</filename>
#     <size>
#         <width>1200</width>
#         <height>800</height>
#         <depth>3</depth>

trandaison

Note: This is the guide for v 2.x.

For the v3, please follow this url: https://blog.csdn.net/sam_shan/article/details/80585240 Thanks @liy-cn for contributing.

StarUML

Download: StarUML.io

Crack

Source: jorgeancal

flyyufelix

ResNet-101 in Keras

This is an Keras implementation of ResNet-101 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

angrycoffeemonster

I use the first


—– BEGIN LICENSE —–
Michael Barnes
Single User License
EA7E-821385
8A353C41 872A0D5C DF9B2950 AFF6F667
C458EA6D 8EA3C286 98D1D650 131A97AB
AA919AEC EF20E143 B361B1E7 4C8B7F04

baraldilorenzo

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

koulmomo

[
	// Move out of common paired characters () and [] with `Tab`
	{
		"keys": ["tab"],
		"command": "move",
		"args": {"by": "characters", "forward": true},
		"context": [
			// Check if next char matches (followed by anything)
			{ "key": "following_text", "operator": "regex_match", "operand": "(:?`|\\)|\\]|\\}).*", "match_all": true },
			// ...and that there is a paid character before it on the same