I am currently watching a video from 27C3 and I would like to filter the applause, as it is very loud. Is this possible? I have heard something like this was made for Vuvuzelas.
I use Ubuntu. If this filter would work via ffmpeg this would be great. If it is written in Python it would also be ok.
Here is an example: http://www.youtube.com/watch?v=TIViQuCX7XM#t=5m4s
No, this isn't possible. The sound of applause covers a very wide band. Filtering vuvuzelas was somewhat possible because they were all close to the same pitch. Applause is all over.
If you want to experiment, pull up this video and play with your EQ in VLC. Even with the wide bands of a 7-band EQ, you'll be dropping quite a few to cut the audience, thus leaving you with nothing.
As Brad said, this is not possible with a static frequency filter, however, if you have some knowledge in signal theory, and a fair lot of free time, you could write an active noise control system. See google scholar for some examples of such a filter (like this one).
You could use a dynamic range compressor, this will not filter out the applause, but at least it will smooth out the loudness. You can give it a threshold so that it doesn't affect sound below that threshold.
Related
I'm interested in using python to make diagrams representing the size of values based on the size of squares (and optionally their colour). Basically I'm looking for a way to make overviews of a bunch of values like the good old program windirstat does with hard-drive usage (it basically makes a big square representing your harddrive and then smaller squares making up the area inside of it representing different programs, the bigger the square the larger the file, colour indicates the type of file). I'm fairly familiar with matplotlib, and I don't think it's possible to do something like this with it. Is there any other python package that would help? Any suggestions for something more low level if it's not? I guess I could do it manually if I could find a way to draw the boxes programatically (I don't really care about the format, but the option to export SVG as well as PNG would be nice).
Ultimately, it would be nice to have it be interactive like windirstat is, where if you were to hover over a particular square you get more information on it, and if you clicked on it maybe you'd go in and see the makeup of that particular square. I'm only familiar with wxpython for GUI stuff, not sure if it could be used for something like this. For now I'd be happy with just outputting them though.
Thanks a lot!
Alex
Edit:
Thanks guys, both your answers helped a lot.
You're looking for Treemapping algorithms. Once implemented, you can transform the output (which should be rectangles) into plotting commands to anything that can draw layered rectangles.
Edit:
More links and information:
If you don't mind reading papers, the browser-based d3 library provides for 'squarified' treemaps (js implementation). They reference this paper by Bruls, Huizing, and van Wijk. (This is also citation 3 on the wikipedia article)
I'd search on the algorithms listed on the linked Wikipedia article. For instance, they also link to this article, which describes an algorithm for "mixed treemaps". The paper also includes some interesting portions at the end describing transformations into other-than-rectangular shapes.
Squarified certainly appears to be the most common variety around. The above links should give you enough to work towards a solution or, even, directly port the d3 implementation. However, the cost of grokking d3's model (which is something like a declarative form of jQuery) may be somewhat high. At first glance, though, the implementation appears relatively straightforward.
Squaremap does this. I haven't used it (I only know it from RunSnakeRun) and its documentation is severely lacking, but it seems to work.
I'm using Python 2.7, PyGTK 2.24, and PyGST (Gstreamer).
To ensure smooth playback from one clip to another (without a blink), I combined all the clips I needed into one larger video. This lets me seek to the exact place I need in code. One of the clips is like a "fill-in", which should loop whenever one of the other clips is not playing.
However, to make my code easier and more streamlined, I want to use segments to define the various clips within the larger video. Then, at the end of each segment (I know there is a segment end event), I seek to the fill-in clip. When I need another clip, I just seek to that segment.
My question is, how exactly do I create these segments? I'm guessing that would be the event_new_new_segment(), but I am not sure. Can I create multiple clips to seek with using this function? Is there another I should use. Are there any gotchas to this method of seeking in my video that I should be aware of?
Second, how do I seek to that segement?
Thank you!
Looks like only GstElement's can generate NEWSEGMENT events, you can't simply attach it to an existing element. The closest thing you could do if not using Python, would be creating a single shot or periodic GstClockID or and use gst_clock_id_wait_async until the clock time hit. But the problem is, GstClockID is not wrapped in PyGst.
I think I'm actually working on some similar problem. Some kind of solution I'm using now, is gluing video streams in real time with gnonlin. The good side: seems to work, didn't have time to thoroughly test it yet. Bad side: poorly documented and buggy. These sources from the flumotion project (and the comments inside!) were very, very helpful to me for understanding how to make the whole thing work.
I want to develop a tool that does the following things.
take in a live voice recording
produce a real time spectrogram
show the time-domain signal
output few values extracted from the spectral analysis
All of these have to be kept updated in a window as the voice is recorded.
I have worked with numpy. But I'm completely new to Qt and other GUI builder tools. What's the best way to proceed given this situation? My peers recommended Qt after I explained them the task. If someone knew of a better tool to be used with python for this task, please let me know. Also, please help me with technical details as to how to capture the live stream and process it in python which is to be shown in a GUI window. One link that gave me some hope is http://www.swharden.com/blog/2010-03-05-realtime-fft-graph-of-audio-wav-file-or-microphone-input-with-python-scipy-and-wckgraph/ . But it is a bit difficult to comprehend it. May be a less intensive solution will help me in getting started.
In Qt 4.6, the QAudioInput API was added. This provides a cross-platform abstraction for getting an audio input signal, and therefore would be of use in achieving point (1).
As for (2) and (3), the Spectrum Analyzer demo which ships with Qt may be of interest.
Screenshot of Spectrum Analyzer demo running on Symbian http://labs.trolltech.com/blogs/wp-content/uploads/2010/05/spectrum.png
The implementation is in C++ rather than in Python, but it may be of use as a reference. Basically what you need for (2) is to calculate the Fast Fourier Transform of the input signal. You'll probably want to use a library which provides an FFT implementation rather than writing your own - that's the approach I took when writing the demo :)
As for (3), this is conceptually pretty simple, but requires a bit of thought in order to get a smoothly scrolling waveform. Take a look at the tiling approach used in the Waveform class in the demo for some tips.
I think by (4) you mean: reduce the large number of points in the FFT output to a small number of values. This is what the demo does in order to plot a bar chart for the spectrum. Again, refer to the demo code to see how the binning of frequency amplitudes is implemented.
Another example of a real-time audio spectrum analyzer using PyAudio, scipy, Chaco in one script can be found in the list of examples for Chaco. (Worked out-of-the-box on my Precise).
On Linux, this is definitely feasible. Other platforms too, but I can really only answer for Linux. Python isn't necessarily your sharpest tool for real-time DSP, but on a suitably modern machine and suitably modest goals you will be fine.
First, you need an interface to the Linux audio drivers. ALSA is pretty universal. There are several different Python wrappers for the ALSA libraries, see Python In Music for a list of libs and applications using them.
Then you do your spectral analysis. SciPy and NumPy have all that.
Then you draw into your Qt window. My expertise is in GTK but you probably want to create a QtCanvas (tutorial), which is an object-oriented drawing area that's designed for this kind of use.
Or you could just use SciPy, which can probably be convinced to do all of this! AudioLab in particular looks like it might be a big help.
I have a camera that will be stationary, pointed at an indoors area. People will walk past the camera, within about 5 meters of it. Using OpenCV, I want to detect individuals walking past - my ideal return is an array of detected individuals, with bounding rectangles.
I've looked at several of the built-in samples:
None of the Python samples really apply
The C blob tracking sample looks promising, but doesn't accept live video, which makes testing difficult. It's also the most complicated of the samples, making extracting the relevant knowledge and converting it to the Python API problematic.
The C 'motempl' sample also looks promising, in that it calculates a silhouette from subsequent video frames. Presumably I could then use that to find strongly connected components and extract individual blobs and their bounding boxes - but I'm still left trying to figure out a way to identify blobs found in subsequent frames as the same blob.
Is anyone able to provide guidance or samples for doing this - preferably in Python?
The latest SVN version of OpenCV contains an (undocumented) implementation of HOG-based pedestrian detection. It even comes with a pre-trained detector and a python wrapper. The basic usage is as follows:
from cv import *
storage = CreateMemStorage(0)
img = LoadImage(file) # or read from camera
found = list(HOGDetectMultiScale(img, storage, win_stride=(8,8),
padding=(32,32), scale=1.05, group_threshold=2))
So instead of tracking, you might just run the detector in each frame and use its output directly.
See src/cvaux/cvhog.cpp for the implementation and samples/python/peopledetect.py for a more complete python example (both in the OpenCV sources).
Nick,
What you are looking for is not people detection, but motion detection. If you tell us a lot more about what you are trying to solve/do, we can answer better.
Anyway, there are many ways to do motion detection depending on what you are going to do with the results. Simplest one would be differencing followed by thresholding while a complex one could be proper background modeling -> foreground subtraction -> morphological ops -> connected component analysis, followed by blob analysis if required. Download the opencv code and look in samples directory. You might see what you are looking for. Also, there is an Oreilly book on OCV.
Hope this helps,
Nand
This is clearly a non-trivial task. You'll have to look into scientific publications for inspiration (Google Scholar is your friend here). Here's a paper about human detection and tracking: Human tracking by fast mean shift mode seeking
This is similar to a project we did as part of a Computer Vision course, and I can tell you right now that it is a hard problem to get right.
You could use foreground/background segmentation, find all blobs and then decide that they are a person. The problem is that it will not work very well since people tend to go together, go past each other and so on, so a blob might very well consist of two persons and then you will see that blob splitting and merging as they walk along.
You will need some method of discriminating between multiple persons in one blob. This is not a problem I expect anyone being able to answer in a single SO-post.
My advice is to dive into the available research and see if you can find anything there. The problem is not unsolvavble considering that there exists products which do this: Autoliv has a product to detect pedestrians using an IR-camera on a car, and I have seen other products which deal with counting customers entering and exiting stores.
Background
I have been asked by a client to create a picture of the world which has animated arrows/rays that come from one part of the world to another.
The rays will be randomized, will represent a transaction, will fade out after they happen and will increase in frequency as time goes on. The rays will start in one country's boundary and end in another's. As each animated transaction happens a continuously updating sum of the amounts of all the transactions will be shown at the bottom of the image. The amounts of the individual transactions will be randomized. There will also be a year showing on the image that will increment every n seconds.
The randomization, summation and incrementing are not a problem for me, but I am at a loss as to how to approach the animation of the arrows/rays.
My question is what is the best way to do this? What frameworks/libraries are best suited for this job?
I am most fluent in python so python suggestions are most easy for me, but I am open to any elegant way to do this.
The client will present this as a slide in a presentation in a windows machine.
The client will present this as a slide in a presentation in a windows machine
I think this is the key to your answer. Before going to a 3d implementation and writing all the code in the world to create this feature, you need to look at the presentation software. Chances are, your options will boil down to two things:
Animated Gif
Custom Presentation Scripts
Obviously, an animated gif is not ideal due to the fact that it repeats when it is done rendering, and to make it last a long time would make a large gif.
Custom Presentation Scripts would probably be the other way to allow him to bring it up in a presentation without running any side-programs, or doing anything strange. I'm not sure which presentation application is the target, but this could be valuable information.
He sounds like he's more non-technical and requesting something he doesn't realize will be difficult. I think you should come up with some options, explain the difficulty in implementing them, and suggest another solution that falls into the 'bang for your buck' range.
If you are adventurous use OpenGL :)
You can draw bezier curves in 3d space on top of a textured plane (earth map), you can specify a thickness for them and you can draw a point (small cone) at the end. It's easy and it looks nice, problem is learning the basics of OpenGL if you haven't used it before but that would be fun and probably useful if your in to programing graphics.
You can use OpenGL from python either with pyopengl or pyglet.
If you make the animation this way you can capture it to an avi file (using camtasia or something similar) that can be put onto a presentation slide.
It depends largely on the effort you want to expend on this, but the basic outline of an easy way. Would be to load an image of an arrow, and use a drawing library to color and rotate it in the direction you want to point(or draw it using shapes/curves).
Finally to actually animate it interpolate between the coordinates based on time.
If its just for a presentation though, I would use Macromedia Flash, or a similar animation program.(would do the same as above but you don't need to program anything)