Tutorial: PyQt4 UI Development for Maya

Oct 122012

PyQt4 UI Development for Maya

Just released my 3rd python-based online training video through cmiVFX.com

Introduction

This tutorial is about learning PyQt4 python bindings for the Qt Framework, and how to introduce new UI elements to Maya as a platform.

We discuss what comprises a “Framework” and a “GUI Framework”, and how Qt and PyQt4 work together.

Getting Started With PyQt4

There are multiple ways of getting a working installation of PyQt4, both for the general system and for Maya. We look into these approaches to get your system up and running to begin working with PyQt4!

We also talk about what is included, such as command line tools and applications, tips on how to test and learn the code, and how to structure a project.

PyQt4 Fundamentals

Lets get crackin’ and learn the basics!

• What is a QObject? What is a QWidget? Common PyQt4 classes are explained in detail

• Working with the Qt Designer application, to build a UI visually

• Layouts: Making widgets resize elegantly and stay organized in your design

• Coordinate space: How do widgets transform in your 2D screen space?

• QApplication and the Qt Event Loop: The engine that runs your UI

• Events, Signals, and Slots: How components communicate changes and how the application can respond to changes to make it dynamic

General Examples

With an understanding of the framework components, we can begin working with fully functional stand-alone examples.

• Common PyQt4 app template

• Subclassing Widgets: Creating custom functionality to the existing classes provided by PyQt4

• Dialogs: Raising dialog windows above existing windows, Modal vs Non-modal, and creating forms. We look at different ways to validate the data provided by the user, to these dialog forms.

PyQt4 And Maya Introduction

Finally, some Maya action! Maya has a slightly different approach to using PyQt4…

• How does the QApplication and event loop work?

• Common Maya PyQt4 app template

• Looking at the Maya API’s MQtUtil class

• The sip module: Helping us translate between Maya’s Qt and our own PyQt4 code

Replicating Maya’s UI Components

What better way to see examples of creating UI for Maya than to replicate some existing functionality? This gives us the opportunity expand with custom functionality

In this chapter we will take two different UI components in Maya, and do a basic custom version of our own, and show to how link them up to Maya’s own callbacks.

Some Features Of This Chapter Include

• The QTableWidget

• Model / View separation with QTreeView

• Docking windows into the Maya interface

• Mixing together PyQt4, the Maya API, Maya commands, and callbacks

• Sorting model data

Customizations

A button can be a button, and a slider might look alright in its stock form, but sometimes we want to customize the look of our widgets. This chapter introduces multiple ways of achieving custom looks to our components

• Stylin’ Stylesheets: Use CSS-like syntax for applying style sheets to widgets

• Painting By … Paint events: For even more control, we can tell a widget exactly how to draw itself on the screen. We will look at two different examples of how to use custom painting.

Previous cmiVFX tutorials:

Python 2.7.3 serializer speed comparisons

Code 1 Response »

Jul 252012

In a recent python project where I was sending multiple messages per second of data over a basic socket, I had initially just grabbed the cPickle module to get the prototype proof-of-concept functioning properly. cPickle is awesome for easily serializing more complex python objects like custom classes, even though in my case I am only sending basic types.

My messages were dicts with some nested dicts, lists, floats, and string values. Roughly 500-1000 bytes. cPickle was doing just fine, but there came a point where I wanted to investigate the areas that could be tightened up. The first thing I realized was that I had forgotten to encode cPickle in the binary format (the default is ascii). That saved me quite a bit of time. But then I casually searched online to see if any json options might be better since my data is pretty primitive anyways.

I found UltraJSON, which is a pure C json parsing library for python, and ran some tests. There are benchmarks on the project page for ujson, as well as other articles on the internet, but I just wanted to post up my own results using a mixed type data container. ujson came out extremely fast (faster than cPickle in binary)

This test included the following:

Here is my IPython test script using timeit for each encode and decode step. I’m using IPython 0.13 with python 2.7.3.

import pickle import cPickle import json import simplejson import cjson import ujson import yajl d = { 'words': """ Lorem ipsum dolor sit amet, consectetur adipiscing elit. Mauris adipiscing adipiscing placerat. Vestibulum augue augue, pellentesque quis sollicitudin id, adipiscing. """, 'list': range(50), 'dict': dict((str(i),'a') for i in xrange(50)), 'int': 100, 'float': 100.123456 } print "*Encoding*" print "pickle.dumps" %timeit _ = pickle.dumps(d) print "pickle.dumps (binary)" %timeit _ = pickle.dumps(d, 2) print "cPickle.dumps" %timeit _ = cPickle.dumps(d) print "cPickle.dumps (binary)" %timeit _ = cPickle.dumps(d, 2) print "json.dumps" %timeit _ = json.dumps(d) print "simplejson.dumps" %timeit _ = simplejson.dumps(d) print "cjson.encode" %timeit _ = cjson.encode(d) print "ujson.dumps" %timeit _ = ujson.dumps(d) print "yajl.dumps" %timeit _ = yajl.dumps(d) pickle_src = cPickle.dumps(d) pickle_src2 = cPickle.dumps(d, 2) json_src = json.dumps(d) print "*Decoding*" print "pickle.loads" %timeit _ = pickle.loads(pickle_src) print "pickle.loads (binary)" %timeit _ = pickle.loads(pickle_src2) print "cPickle.loads" %timeit _ = cPickle.loads(pickle_src) print "cPickle.loads (binary)" %timeit _ = cPickle.loads(pickle_src2) print "json.loads" %timeit _ = json.loads(json_src) print "simplejson.loads" %timeit _ = simplejson.loads(json_src) print "cjson.decode" %timeit _ = cjson.decode(json_src) print "ujson.loads" %timeit _ = ujson.loads(json_src) print "yajl.loads" %timeit _ = yajl.loads(json_src) """ *RESULTS* Python 2.73 IPython 0.13 *Encoding* pickle.dumps 1000 loops, best of 3: 527 us per loop pickle.dumps (binary) 1000 loops, best of 3: 576 us per loop cPickle.dumps 10000 loops, best of 3: 56.8 us per loop cPickle.dumps (binary) 100000 loops, best of 3: 11.3 us per loop json.dumps 10000 loops, best of 3: 30.9 us per loop simplejson.dumps 10000 loops, best of 3: 36.2 us per loop cjson.encode 10000 loops, best of 3: 22.9 us per loop ujson.dumps 100000 loops, best of 3: 7.03 us per loop <== FASTEST yajl.dumps 10000 loops, best of 3: 23.2 us per loop *Decoding* pickle.loads 1000 loops, best of 3: 652 us per loop pickle.loads (binary) 1000 loops, best of 3: 234 us per loop cPickle.loads 10000 loops, best of 3: 43.9 us per loop cPickle.loads (binary) 100000 loops, best of 3: 13.7 us per loop json.loads 10000 loops, best of 3: 63.2 us per loop simplejson.loads 10000 loops, best of 3: 33.8 us per loop cjson.decode 10000 loops, best of 3: 36 us per loop ujson.loads 100000 loops, best of 3: 12.8 us per loop <== FASTEST yajl.loads 10000 loops, best of 3: 27.4 us per loop """

Getting started with XBOX 360 Kinect on OSX – opensource+python

Code, FX No Responses »

Jun 212012

A recent project of mine involves research and development with an XBOX 360 Kinect Sensor. Being a python guy, I started searching for python bindings to some OSX-supported framework. When you just get started looking into this area it can be a little confusing. There are a number of layers to the software stack to enable one to accomplish anything meaningful. This is just a short and general blog post outlining the basics of what I have discovered thus far, to help anyone else that might also be getting started.

At the lowest level, you need a driver. Something that can talk to the USB device that is the Kinect sensor. When you purchase the XBOX Kinect for Windows version of the sensor, and you are going to be developing on windows, much of this whole stack is provided to you by way of the Kinect SDK. But for the open source folks with the standard XBOX 360 sensor, you need to piece together your own solution.

Two drivers that I have discovered thus far:

I had started OpenKinect (libfreenect) because it comes with a python wrapper included. There were a few dependencies (I will talk about specific build steps in just a moment), but once I got this installed I was able to fire up the included glview app and see both depth and rgb data streaming in from my sensor. The role of these drivers is to provide simply the basic streams. That is, the depth, rgb, audio, and a few other sensor data streams. If your goal is to start tracking players, seeing skeletons, and registering gestures, the drivers are not enough. You would be required to make your own solution from this raw data at this phase in the game.

You would now want to look into middleware that can take the raw data and provide to you an API with higher level information. This would include finding users in the scene for you, tracking their body features, and giving you various events to watch for as the data streams.

Being that my goal was to have python bindings, I found my options to be much more limited than if I were going to be developing in C++. Wrappers have to exist for the framework you want. This is where my research really started ramping up. I spent a few days dealing wtih compiling issues, as well as having an actual bad power adapter that had to be exchanged. But all said and done, here is what I have settled on thus far…

Driver: PrimeSense Sensor
OpenNI Framework
NITE middleware for OpenNI
PyOpenNI python bindings

Install Details

Install homebrew (package manager)

http://mxcl.github.com/homebrew/

Install build tools


brew install cmake
brew install boost

brew install cmake

brew install boost

Install python2.7


brew install python --framework

brew install python --framework

Suggestion: virtualenv Environment

This is not a requirement. But I recommend using virtualenv to set up an environment that specifically uses python2.7 so that you don’t have to fight with mixed dependencies and versions.

Create a virtualenv called “kinect”


pip install virtualenv
virtualenv --no-site-packages -p python2.7 kinect
cd kinect
source bin/activate

pip install virtualenv

virtualenv --no-site-packages -p python2.7 kinect

cd kinect

source bin/activate

Install libusb (patched version)

There is a special patched version of the libusb library, in the form of a homebrew formula.


git clone https://github.com/OpenKinect/libfreenect.git

git clone https://github.com/OpenKinect/libfreenect.git

Now copy platform/osx/homebrew/libusb-freenect.rb -> /usr/local/Library/Formula/


brew install libusb-freenect

brew install libusb-freenect

Install SensorKinect drivers


git clone https://github.com/avin2/SensorKinect.git

git clone https://github.com/avin2/SensorKinect.git

Then uncompress Bin/SensorKinect093-Bin-MacOSX-v*tar.bz2


sudo ./install.sh

sudo ./install.sh

Install OpenNI framework

Go here: http://www.openni.org/Downloads/OpenNIModules.aspx
Download Unstable Binary for MacOSX
sudo ./install.sh

Install NITE middleware (for OpenNI)

Go here: http://www.openni.org/Downloads/OpenNIModules.aspx
Download Unstable MIDDLEWARE of NITE for OSX
sudo ./install.sh

Install PyOpenNI

Be aware that on OSX, PyOpenNI requires a framework build of python 2.7+ and that you must build it for x86_64 specifically. Also, I was having major problems with cmake properly finding the python includes location. I had to suggest a fix, so please see here for the necessary corrections. I have referenced a patched fork of the repository below.


export CPPFLAGS="-arch x86_64"
git clone git://github.com/justinfx/PyOpenNI.git
mkdir PyOpenNI-build
cd PyOpenNI-build
cmake -D PYTHON_INCLUDE_DIR=/usr/local/Cellar/python/2.7.3/Frameworks/Python.framework/Headers ../PyOpenNI
make

export CPPFLAGS="-arch x86_64"

git clone git://github.com/justinfx/PyOpenNI.git

mkdir PyOpenNI-build

cd PyOpenNI-build

cmake -D PYTHON_INCLUDE_DIR=/usr/local/Cellar/python/2.7.3/Frameworks/Python.framework/Headers ../PyOpenNI

make

copy the lib/openni.so module to the python2.7 site-packages

Examples

Once you have everything installed, you can try out the examples that are included both in the NITE source location that you downloaded and also in the PyOpenNI source location:

NITE/Samples
PyOpenNI/examples

I also tried out ofxKinect (github.com/ofTheo/ofxKinect) on the side, which is an addon for OpenFrameworks. This is kind of a separate path than the OpenNI stack. I would say its more like an advanced offering of libfreenect. Using the included example, I recorded a 3D point cloud that is built on the fly from the RGB and depth data:

Mixing PyQt4 widgets and Maya UI objects

Code, FX 9 Responses »

Nov 202011

A question came up in the Maya-Python mailing list that I thought was a really good topic, and should be reposted.

Someone asked how you can create maya UI objects and embed them within your main PyQt application. Specifically he wanted to create a modelPanel and embed it so that he would have a camera view within his own PyQt window.

Here is my example of how to achieve this…

from PyQt4 import QtCore, QtGui import maya.cmds as cmds import maya.OpenMayaUI as mui import sip global app class MyDialog(QtGui.QDialog): def __init__(self, parent, **kwargs): super(MyDialog, self).__init__(parent, **kwargs) self.setObjectName("MyWindow") self.resize(800, 600) self.setWindowTitle("PyQt ModelPanel Test") self.verticalLayout = QtGui.QVBoxLayout(self) # need to set a name so it can be referenced by maya node path self.verticalLayout.setObjectName("mainLayout") # First use SIP to unwrap the layout into a pointer # Then get the full path to the UI in maya as a string layout = mui.MQtUtil.fullName(long(sip.unwrapinstance(self.verticalLayout))) cmds.setParent(layout) self._cameraName = cmds.camera()[0] nodeName = cmds.modelPanel(cam=self._cameraName) # Find a pointer to the modelPanel that we just created ptr = mui.MQtUtil.findControl(nodeName) # Wrap the pointer into a python QObject self.modelPanel = sip.wrapinstance(long(ptr), QtCore.QObject) # add our QObject reference to the modelPanel to our layout self.verticalLayout.addWidget(self.modelPanel) def show(self): super(MyDialog, self).show() # maya can lag in how it repaints UI. Force it to repaint # when we show the window. self.modelPanel.repaint() def show(): global app # use a shared instance of QApplication app = QtGui.QApplication.instance() # get a pointer to the maya main window ptr = mui.MQtUtil.mainWindow() # use sip to wrap the pointer into a QObject win = sip.wrapinstance(long(ptr), QtCore.QObject) d = MyDialog(win) d.show() return d

You need sip and the MQtUtil functions to convert between maya node paths and python Qbjects. Its the same idea as having to use those functions to get a reference to the maya MainWindow, in order to parent your dialog.

Python for Maya Artists – Volume 2

Code, FX 2 Responses »

Nov 152011

Second video in the python for maya series, just released through cmiVFX!

Python For Maya – Volume 2

If you watched the first video, you now have a good grasp on Python. Sweet. Let’s plow through some more involved concepts like python juggernauts!

With a working knowledge of the python scripting language, and the Maya Python commands API, we can continue to learn new ways to solve more challenging problems, create complete scripts, and build user interfaces around our tools. We also introduce the Maya Python API; a lower-level interface into Maya.

This video focuses more on breaking down full scripts, as opposed to typing out syntax. Its jam packaged with information and moves fast to deliver you as much brain food as possible. The first segment of the video transitions from beginning to intermediate level, with the majority of the video being intermediate, and finishing out by touching on advanced concepts. The included project files are abundant, complete, and full of helpful documentation so that you can take your time and learn about each piece of the tools.

If you check it out, leave me feedback!
http://cmivfx.com/tutorials/view/328/Python+For+Maya+Vol+02

First video can be found here

Installing PyQt4 for Maya 2012+ (osx)

Code, FX 22 Responses »

Nov 092011

This is a follow up post to my previous one on Installing PyQt4 for Maya 2011

Recently while putting together my next video tutorial for Python for Maya, I came to a section where I wanted to demo PyQt4 in Maya2012. But I was concerned that viewers would have to go through the complicated steps of building PyQt4. I noticed that other people have made available precompiled PyQt installers for windows (here) but I could not find any for OSX or linux. So I decided to put together a build.

I created a new project on github called MyQt4
https://github.com/justinfx/MyQt4

Its a Makefile for completely downloading and building PyQt4 for maya, and generating a .pkg installer. Hopefully someone can contribute improvements since I dont have a ton of experience writing makefiles, and also that someone might create a linux version.

Here is a link to the latest pkg build:

Snow Leopard:

Maya2011: MyQt4.7.4-maya2011-x64-osx-10.6.pkg
Maya2012: MyQt4.9.4-maya2012-x64-osx-10.6.pkg
Maya2013: MyQt4.9.4-maya2013-x64-osx-10.6.pkg

Lion:

Maya2012: MyQt4.8.6-maya2012-x64-osx-10.7.pkg (Thanks Chris!)
Maya2013: MyQt4.8.6-maya2013-x64-osx-10.7.pkg

Mountain Lion:

Maya2011: MyQt4.7.4-maya2011-x64-osx-20130114.pkg

Here are builds other people have made:

Win 32bit: http://blarg.robertkist.com/?p=51
Win 64bit: http://nathanhorne.com/?p=322
Win 7 64bit Maya 2013: https://www.box.com/s/1db3b0c903059ac89fc4
Linux: http://www.kurianos.com/wordpress/?p=551

Intro to Python for Maya Artists – Tutorial

Code, FX 1 Response »

Oct 082011

Just released my first online video tutorial, through cmiVFX

Python Introduction Vol 01 – Maya

Amazing at Animation? Master of Modeling? Conquistador of Character Rigging?

But how is your Python?

This course brings the talented artist into the fold of the technical-side of Maya. Learn the basics of Python, and its place in your 3D workflow, with visual examples and real world problems. Get a kick-start on adding some automation into your life, and solving common problems in a fraction of the time. By the end of this video, you should have a deeper understanding of one of the languages Maya speaks under the hood, and how to start viewing your scenes in terms of glorious Python code!

Check it out: http://cmivfx.com/tutorials/view/320/Python+Introduction+Vol+01+-+Maya

If you check out this course, please leave me some feedback! I would love to hear your thoughts.
Stay tuned for more installments to come!

AtomSplitter v1.6 update

FX No Responses »

Aug 312010

AtomSplitter has been updated to v1.6, available through cmivfx.com

AtomSplitter 1.6 – cmiVFX.com

Updates:

Exports Terragen .tgd scene file format

See the original post.


COMMAND LINE HELP

OSX:
AtomSplitter.app/Contents/MacOS/AtomSplitter &lt;chan file&gt; [out file]

Linux:
AtomSplitter &lt;chan file&gt; [out file]

Windows:
AtomSplitter.exe &lt;chan file&gt; [out file]

=========================================

HELP:
&gt;&gt;&gt; AtomSplitter -h

Usage: AtomSplitter &lt;chan file&gt; [out file]

Options:
-h, --help
        show this help message and exit
-o OBJ, --obj=OBJ
        Optional nuke-exported pointCloud .obj file
-f FPS, --fps=FPS
        Set FPS rate (default 24)
-x WIDTH, --width=WIDTH
        Set frame width (default 2048)
-y HEIGHT, --height=HEIGHT
        Set frame height (default 1556)
--filmwidth=FILMWIDTH
        Set film aperature width in mm (default 24.576)
--filmheight=FILMHEIGHT
        Set film aperature height in mm (default 18.672)
-s SCALE, --scale=SCALE
        Scale the translation values by this amount
-F FORMAT, --format=FORMAT
        Output format (fbx, action, terragen)

COMMAND LINE HELP

OSX:

AtomSplitter.app/Contents/MacOS/AtomSplitter <chan file> [out file]

Linux:

AtomSplitter <chan file> [out file]

Windows:

AtomSplitter.exe <chan file> [out file]

=========================================

HELP:

>>> AtomSplitter -h

Usage: AtomSplitter <chan file> [out file]

Options:

-h, --help

show this help message and exit

-o OBJ, --obj=OBJ

Optional nuke-exported pointCloud .obj file

-f FPS, --fps=FPS

Set FPS rate (default 24)

-x WIDTH, --width=WIDTH

Set frame width (default 2048)

-y HEIGHT, --height=HEIGHT

Set frame height (default 1556)

--filmwidth=FILMWIDTH

Set film aperature width in mm (default 24.576)

--filmheight=FILMHEIGHT

Set film aperature height in mm (default 18.672)

-s SCALE, --scale=SCALE

Scale the translation values by this amount

-F FORMAT, --format=FORMAT

Output format (fbx, action, terragen)

AtomSplitter v1.5 update

FX No Responses »

May 262010

AtomSplitter has been updated to v1.5, available through cmivfx.com

AtomSplitter 1.5 – cmiVFX.com

Updates:

Added the ability to convert point cloud data, exported from Nuke as a .obj, to be included in the fbx/action export.

See the original post.

AtomSplitter v1.2 update

FX No Responses »

May 112010

AtomSplitter (chanToFbx) has been updated to v1.2, available through cmivfx.com

AtomSplitter 1.2 – cmiVFX.com

Updates:

Camera rotation order set to ZXY, which is the Nuke camera default
Fixed a bug where the FocalLength value was not being keyframed properly
Added a scene scale field, for adjusting the translation values globally.

If you haven’t visited cmiVFX.com before, PLEASE check them out. Chris Maynard does an amazing job rounding up top talent in the industry to create these outstanding visual fx tutorials. The information is always cutting edge.

See the original post.

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