Difference between revisions of "Projects:Sketchy recognition"
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==== Sketches ==== | ==== Sketches ==== | ||
| − | [[File:Splitscreen05.png|800px | + | [[File:Splitscreen05.png|frameless|none|800px]] |
| + | <small>Early sketch</small> | ||
| − | + | [[File:Contours.png|frameless|none|800px]] | |
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| − | + | <small>[http://vandal.ist/diversions2019/mim/contours.html Contours of the Musical Instruments database]</small> | |
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| − | + | [[File:2052.png|frameless|none|500px]] | |
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| − | + | <small>[http://vandal.ist/diversions2019/mim/sketchrecog.html Sketch recognition outcomes]</small> | |
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==== (Re)sources ==== | ==== (Re)sources ==== | ||
Revision as of 06:26, 10 September 2019
Nicolas Malevé, Michael Murtaugh
Sketchy recognition
Bread, Nose, Kangaroo or Teddy Bear?
A photograph from the collection of the Museum of Musical Instrument is processed by a contour detector algorithm. The algorithm draws the lines it found on the image sequentially. While it is tracing the contours, another algorithm, a sketch detector, tries to guess what is being drawn. Is it bread? A kangaroo? It is a teddy bear.
Sketchy Recognition (working title) is an attempt to provoke a dialogue with, and between, algorithms, visitors and museum collections.
Cast:
- Musical instruments: MIM collection, Brussels.
- Line detector: The Hough algorithm in the OpenCV toolbox, originally developed to analyse bubble chamber photographs.
- Sketch recognizer: an algorithm based on the research of Mathias Eitz, James Hays and Marc Alexa (2012), and the code and models by Jean-Baptiste Alayrac.
- Data: from the hands of the many volunteers who contributed to Google's Quick, Draw! Dataset.
- Special sauce, bugs and fixes: Michael and Nicolas
Sketches
Early sketch
Contours of the Musical Instruments database
(Re)sources
- Code for this project
- You were asked to draw an angel, Working notes from the Scandinavian Institute for Computational Vandalism (April 2017)
- Assisted drawing, Working notes from the Scandinavian Institute for Computational Vandalism (January 2016) + Assisted drawing: Exploring Augmented Creativity, original blogpost by Samim (December 2015)
- How Do Humans Sketch Objects? and C/C++ implementation, Mathias Eitz, James Hays and Marc Alexa (2012)
- Python/Jupyter https://github.com/ajwadjaved/Sketch-Recognizer
- sketch-recognizer, Jean-Baptist Alayrac's working Python code that we ended up using
Collection: Musical Instruments Museum (MIM)
Reconnaissance esquissé
[translation FR]
Schetsmatige herkenning
[translation NL]
Working sketches + notes (not in publication v1)
