##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
| cmake_minimum_required( VERSION 3.0 ) | |
| project( so-opencv-calibration ) | |
| find_package( OpenCV 3.0.0 EXACT REQUIRED ) | |
| set( INPUT_FILENAME "${CMAKE_CURRENT_LIST_DIR}/input_00.png" ) # Input file, e.g. http://i.stack.imgur.com/WjER0.png | |
| add_executable( mwe mwe.cpp ) | |
| target_compile_definitions( mwe PRIVATE -DINPUT_FILENAME="${INPUT_FILENAME}" ) | |
| target_include_directories( mwe PRIVATE ${OpenCV_INCLUDE_DIRS} ) | |
| target_link_libraries( mwe ${OpenCV_LIBS} ) |
| using UnityEngine; | |
| using System.Collections; | |
| using Holoville.HOTween; | |
| namespace FS.Handlers | |
| { | |
| public class FSScrollController : MonoBehaviour { | |
| public float contentOverflowY = 0f; | |
| public float contentHeight = 0f; |
Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.
$ python -m SimpleHTTPServer 8000| # source : http://code.google.com/p/natvpn/source/browse/trunk/stun_server_list | |
| # A list of available STUN server. | |
| stun.l.google.com:19302 | |
| stun1.l.google.com:19302 | |
| stun2.l.google.com:19302 | |
| stun3.l.google.com:19302 | |
| stun4.l.google.com:19302 | |
| stun01.sipphone.com | |
| stun.ekiga.net |
