After a long hiatus I'm back with an update. Recently I've been upgrading the Structure-from-Motion Toy Library (https://github.com/royshil/SfM-Toy-Library/) to OpenCV 3.x from OpenCV 2.4.x.
Continue reading "Structure-from-Motion Toy Lib Upgrades to OpenCV 3"
WTH OpenGL 4? Rendering elements arrays with VAOs and VBOs in a QGLWidget
I spent an entire day getting OpenGL 4 to display data from a VAO with VBOs so I thought I'd share the results with you guys, save you some pain.
I'm using the excellent GL wrappers from Qt, and in particular QGLShaderProgram.
This is pretty straightforward, but the thing to remember is that OpenGL is looking for the vertices/other elements (color? tex coords?) to come from some bound GL buffer or from the host. So if your app is not working and nothing appears on screen, just make sure GL has a bound buffer and the shader locations match up and consistent (see the
const int I have on the class here).
[Python] OpenCV capturing from a v4l2 device
OpenCV Python YAML persistance
I wasn't able to find online a complete example on how to persist OpenCV matrices in Python (so really NumPy arrays) to YAML like what cv::FileStorage will give you.
So here's a short snippet:
import numpy as np import yaml # A yaml constructor is for loading from a yaml node. # This is taken from: http://stackoverflow.com/a/15942429 def opencv_matrix_constructor(loader, node): mapping = loader.construct_mapping(node, deep=True) mat = np.array(mapping["data"]) mat.resize(mapping["rows"], mapping["cols"]) return mat yaml.add_constructor(u"tag:yaml.org,2002:opencv-matrix", opencv_matrix_constructor) # A yaml representer is for dumping structs into a yaml node. # So for an opencv_matrix type (to be compatible with c++'s FileStorage) we save the rows, cols, type and flattened-data def opencv_matrix_representer(dumper, mat): mapping = {'rows': mat.shape[0], 'cols': mat.shape[1], 'dt': 'd', 'data': mat.reshape(-1).tolist()} return dumper.represent_mapping(u"tag:yaml.org,2002:opencv-matrix", mapping) yaml.add_representer(np.ndarray, opencv_matrix_representer) #example with open('output.yaml', 'w') as f: f.write("%YAML:1.0") yaml.dump({"a matrix": np.zeros((10,10)), "another_one": np.zeros((2,4))}, f) # a matrix: !!opencv-matrix # cols: 10 # data: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, # 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, # 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, # 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, # 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, # 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, # 0.0, 0.0, 0.0, 0.0, 0.0] # dt: d # rows: 10 # another_one: !!opencv-matrix # cols: 4 # data: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # dt: d # rows: 2 with open('output.yaml', 'r') as f: print yaml.load(f) # {'a matrix': array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], # [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]]), 'another_one': array([[ 0., 0., 0., 0.], # [ 0., 0., 0., 0.]])}
There you go
Simple Loading Spinner Tapestry 5 Mixin w/ spin.js
Sharing a small snippet on creating a loading spinner in a Tapestry 5.3+ Mixin, using spin.js.
It creates a convenient way to add spinners to your long-loading-times ajax zone updates, with all the code hidden away from the template .tml and page class object.
Sorry I can't show a working example, that would entail running a Tapestry application server.
But it's very straightforward, just grab the spin.min.js and the rest falls into place (it also depends on jQuery).
Adding radial labels to Dimple.JS pie chart
Bootstrap3 fluid container with custom width sidebar
I was looking for a way to get a fluid container live side-by-side with a custom width sidebar.
A custom width sidebar can't be achieved with a Bootstrap column, and is a total mess to get right with floats if you then need a fluid container to get a grid system for the main section.
So, here's one solution:
JSFiddle: https://jsfiddle.net/6sfog80k/
YUYV to JPEG conversion with libjpeg
Sharing a small libjpeg snippet.
Some SO questions about it have only partial snippets:
- http://stackoverflow.com/questions/16390783/how-to-save-yuyv-raw-data-to-jpeg-using-libjpeg
- http://stackoverflow.com/questions/17029136/weird-image-while-trying-to-compress-yuv-image-to-jpeg-using-libjpeg
- http://stackoverflow.com/questions/19282402/how-to-compress-a-yuyv-image-into-a-jpeg
Enjoy!
Roy
Quickly: How to render a PDF to an image in C++?
Using Poppler, of course!
Poppler is a very useful tool for handling PDF, so I've discovered lately. Having tried both muPDF and ImageMagick's Magick++ and failed, Poppler stepped up to the challenge and paid off.
So here's a small example of how work the API (with OpenCV, naturally):
#include <iostream> #include <fstream> #include <sstream> #include <opencv2/opencv.hpp> #include <poppler-document.h> #include <poppler-page.h> #include <poppler-page-renderer.h> #include <poppler-image.h> using namespace cv; using namespace std; using namespace poppler; Mat readPDFtoCV(const string& filename,int DPI) { document* mypdf = document::load_from_file(filename); if(mypdf == NULL) { cerr << "couldn't read pdf\n"; return Mat(); } cout << "pdf has " << mypdf->pages() << " pages\n"; page* mypage = mypdf->create_page(0); page_renderer renderer; renderer.set_render_hint(page_renderer::text_antialiasing); image myimage = renderer.render_page(mypage,DPI,DPI); cout << "created image of " << myimage.width() << "x"<< myimage.height() << "\n"; Mat cvimg; if(myimage.format() == image::format_rgb24) { Mat(myimage.height(),myimage.width(),CV_8UC3,myimage.data()).copyTo(cvimg); } else if(myimage.format() == image::format_argb32) { Mat(myimage.height(),myimage.width(),CV_8UC4,myimage.data()).copyTo(cvimg); } else { cerr << "PDF format no good\n"; return Mat(); } return cvimg; }
All you have to do is give it the DPI (say you want to render in 100 DPI) and a filename.
Keep in mind it only renders the first page, but getting the other pages is just as easy.
That's it, enjoy!
Roy.
Bootstrapping planar AR and tracking without markers [w/code]
Years ago I wanted to implement PTAM. I was young and naïve 🙂
Well I got a few moments to spare on a recent sleepless night, and I set out to implement the basic bootstrapping step of initializing a map with a planar object - no known markers needed, and then tracking it for augmented reality purposes.
Continue reading "Bootstrapping planar AR and tracking without markers [w/code]"