Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
|import matplotlib.pyplot as plt|
|def draw_neural_net(ax, left, right, bottom, top, layer_sizes):|
|Draw a neural network cartoon using matplotilb.|
|>>> fig = plt.figure(figsize=(12, 12))|
|>>> draw_neural_net(fig.gca(), .1, .9, .1, .9, [4, 7, 2])|
|using namespace std;|
|using namespace cv;|
|#define MIN_Y 90|
|#define MAX_Y 180|
|#define MIN_X 0|
|#define MAX_X 180|
You have played MapRoulette. You have seen some of the fun challenges. If you are reading this, you are probably thinking: 'I have a great idea for the next MapRoulette challenge!'
Great! That is exactly what I am here to explain step by step. So let's get started!
|This is how to track a white ball example using SimpleCV|
|The parameters may need to be adjusted to match the RGB color|
|of your object.|
|The demo video can be found at:|
This list of resources is all about acquring and processing aerial imagery. It's generally broken up in three ways: how to go about this in Photoshop/GIMP, using command-line tools, or in GIS software, depending what's most comfortable to you. Often these tools can be used in conjunction with each other.
|# "Colorizing B/W Movies with Neural Nets",|
|# Network/Code Created by Ryan Dahl, hacked by samim.io to work with movies|
|# BACKGROUND: http://tinyclouds.org/colorize/|
|# DEMO: https://www.youtube.com/watch?v=_MJU8VK2PI4|
|# 1. Download TensorFlow model from: http://tinyclouds.org/colorize/|
|# 2. Use FFMPEG or such to extract frames from video.|
|# 3. Make sure your images are 224x224 pixels dimension. You can use imagemagicks "mogrify", here some useful commands:|
|# mogrify -resize 224x224 *.jpg|
|# mogrify -gravity center -background black -extent 224x224 *.jpg|