PyMT/Movid @THSP


THSP is a Festival in Toulouse, with lot of events and hackers, from the 28 to the 30 May.

Saturday, i’ll do a talk/introduction about PyMT and Movid. Jimi is doing a workshop during the whole event, to build another Wall, and some other Multitouch Table. It will be a nice playground for both software! Thanks to Marc Bruyere and Jimi Hertz for giving me the possibility to talk here 🙂

Read more about the event with the THSP Program May 2010.


Multitouch Linux Support for PyMT


Since the last week, i’ve done some jobs about supporting nativly multitouch screens in PyMT. Linux was missing in the native support, next to Windows and MacOSX, already available.

2 supports have been realized : HID Input Support, and MPX/XI2 Support.

1. Kernel Part

HID Input is the Input part of Linux Kernel. Since 2.6.34, lot of multitouch screens got their drivers integrated in the source code. Most of the drivers have been done by the Stephane Chatty from the ENAC Laboratory, inside the ShareIT project.

HID Input is reading the Event generated by the kernel, using /dev/input/eventX.

The Event are documented in the input.h. New event type have been added for Multitouch support: all the ABS_MT_. As today, we support :

  • ABS_MT_POSITION_X : X position
  • ABS_MT_POSITION_Y: Y position
  • ABS_MT_PRESSURE : pressure
  • ABS_MT_TOUCH_MAJOR : width of the object
  • ABS_MT_TOUCH_MINOR : height of the object

Other event are ignored, but would be interested to add the support, like ABS_MT_ORIENTATION. But right now, no device support them.

This work is available on the latest version of PyMT. Check our PyMT github repository. If you want to known how to use it, you can read the mail sent to the pymt-dev mailing list.

The result of my work : PyMT + HIDInput support on Linux

2. Xorg

Since Xorg 7.5, MPX is available. MPX is the support of Multi Pointer inside X. Benjamin (from the Enac too), have provided a modified evdev module for Xorg, to read Multitouch Event from kernel, and pass them to Xorg.
This work require a running daemon, actually called multitouchd (on the same page as evdev). The daemon detect all the devices with Multitouch support, and create by default 5 fake mouse device, attached to the main multitouch device. With this way, each touch control one fake mouse device.

Unfortunaly, this is not stable, and with a stantum screen, once i get more that 4 or 5 touch, Xorg crash.

Anyway, i’ve start the support in the PyMT branch input-xi2. This rely on python-xlib, but this library required some change to make our work run.
Since it’s really more complicated than HID Input, i’ll not explain all the work right now. Maybe in another blog post.

3. So, which screen i could buy to play with ?

That’s pretty simple. ENAC (again) maintain a full list of multitouch screen working on linux, and the status of the support in linux kernel.
For my part, i’m playing with an Acer T230H. A little bit bugged, and support only 2 points. But enough to play and debug with right now.

That’s all for the moment, enjoy !


Movid, a Modular Open Vision Interaction Daemon


Hi everyone,

We are glad to announce the birth of the Movid project: http://movid.org/

Movid is an acronym; it stands for ‘Modular Open Vision Interaction Daemon’. It’s a cross-platform and Open Source vision tracker, designed to be as modular as possible. Although the project is pretty young, it already features more than 20 modules, including blob and fiducial trackers as well as TUIO output. Movid is coded in C++, and use WOscLIB, cJSON, libevent, libfidtrack, jpeg-8 and XgetOpt.

(more…)


Python: is X is better than Y ? Round 3, pure python VS cython


Round 3: pure python drawing VS cython

Benchmark code :

s = time.time()
for x in xrange(10000):
   drawRectangle(0, 0, 50, 50)
print 'result=', time.time() - s

Let’s take the Python version of simplified drawRectangle():

def drawRectangle(x, y, w, h):
   glBegin(GL_QUADS)
   glVertex2f(x, y)
   glVertex2f(x + w, y)
   glVertex2f(x + w, y + h)
   glVertex2f(x, y + h)
   glEnd()

I got the result on poor graphics card: average ~1.1268s

Let’s rewrite in Cython:

cdef extern from "GL/gl.h":
   ctypedef float         GLfloat
   ctypedef unsigned int  GLenum
   int GL_QUADS
   cdef void glBegin(GLenum mode)
   cdef void glEnd()
   cdef void glVertex2f(GLfloat x, GLfloat y)
def drawRectangle(float x, float y, float w, float h):
   glBegin(GL_QUADS)
   glVertex2f(x, y)
   glVertex2f(x + w, y)
   glVertex2f(x + w, y + h)
   glVertex2f(x, y + h)
   glEnd()

And the result : average ~0.0325s

PyMT Impact: rewriting graphx package 🙂

EDIT:
On a NVIDIA 9800 GT: with 1000000 (instead of 10000):

  • Python: 16.1
  • Python -O: 17.2
  • Python -OO: 16.9
  • Cython: 0.29

Very weird about -O / -OO…


Python: is X is better than Y ? Round 2, remove exception VS test in + remove


Round 2: catching remove exception VS test in + remove

Benchmark code :

from time import time

# exceptions vs list in
def bench_in_remove(count):
    for x in xrange(count):
        q = []
        for z in xrange(1000):
            q.append(z)
        for z in xrange(0, 500):
            if z in q:
                q.remove(z)
        
def bench_exception(count):
    for x in xrange(count):
        q = []
        for z in xrange(1000):
            q.append(z)
        for z in xrange(0, 500):
            try:
                q.remove(z)
            except ValueError:
                continue

def bench_remove(count):
    for x in xrange(count):
        q = []
        for z in xrange(1000):
            q.append(z)
        for z in xrange(0, 500):
            q.remove(z)

def run(f, c=10000):
    t = time()
    f(c)
    print '%-15s time=%.8f count=%d' % (f.func_name, time() - t, c)

run(bench_remove)
run(bench_in_remove)
run(bench_exception)

And the result :

bench_remove    time=4.20256305 count=10000
bench_in_remove time=4.49746203 count=10000
bench_exception time=4.33078504 count=10000

We can see a little improvement with testing exception instead of testing in.
We can also see the overhead due to the test before removing in list.

I’ve also tested with xrange(-500, 500) instead of (0, 500), to trigger invalid removal. Here is the result :

bench_in_remove time=12.42448401 count=1000
bench_exception time=14.26106405 count=1000

Triggering an exception cost much time than testing if value is in a list…

PyMT Impact: must check.


Python: is X is better than Y ? Round 1, deque vs list.


This week-end, i’ve spend some time about searching how to optimize PyMT code. And done some interesting benchmark. Next days, i’ll post some of them, in order to remember which is the better solution.

For the first round: let’s test Deque from collections package VS Python List !

Code:

from time import time

# collections VS list
def bench_deque(count):
    from collections import deque
    q = deque()
    for x in xrange(count):
        for z in xrange(1000):
            q.append(z)
        while True:
            try:
                q.pop()
            except:
                break

def bench_list(count):
    q = []
    for x in xrange(count):
        for z in xrange(1000):
            q.append(z)
        for y in xrange(len(q)):
            q.pop(0)

def run(f, c=100000):
    t = time()
    f(c)
    print '%-15s time=%.8f count=%d' % (f.func_name, time() - t, c)

run(bench_deque)
run(bench_list)

And the result :

bench_deque     time=35.61677003 count=100000
bench_list      time=78.20481586 count=100000

Impact for PyMT: wm_pen, wm_touch.


Python and HTTP Pipelining


Attention, this method is NOT pipelining as described in comments, and even might break if the http connection is too fast with httplib.ResponseNotReady. I’ll update this post when i’ll found a real and simple way to achieve pipelining, because one possible way to do it with httplib is really ugly

I wanted to do HTTP Pipelining using urllib2. But, first of all, what is pipelining ?
HTTP pipelining is a technique in which multiple HTTP requests are written out to a single socket without waiting for the corresponding responses.

What is the benefit of pipelining ? Less network load, speedup processing !
I was searching a way to do it with urllib2… But solution are complicated, and not fit well to my needs.
But way, why stay on urllib2 ? Use httplib !

Reusing the connection :

First, reusing the same connection

import httplib
server = httplib.HTTPConnection('yourserver.com')
server.request('GET', '/index.html')
print 'RESPONSE1:', server.getresponse().read()

server.request('GET', '/index2.html')
print 'RESPONSE2:', server.getresponse().read()

server.request('GET', '/index3.html')
print 'RESPONSE3:', server.getresponse().read()

Second, try pipelining !

import httplib
server = httplib.HTTPConnection('yourserver.com')
server.request('GET', '/index.html')
res1 = server.getresponse()
server.request('GET', '/index2.html')
res2 = server.getresponse()
server.request('GET', '/index3.html')
res3 = server.getresponse()

print 'RESPONSE1:', res1.read()
print 'RESPONSE2:', res2.read()
print 'RESPONSE3:', res3.read()