Metadata-Version: 1.1
Name: cerebrum
Version: 0.1.21
Summary: A library for Crossmodal Supervised Learning Algorithm with Time Series Memory Recording & Long Short-Term Memory Networks
Home-page: https://github.com/mertyildiran/Cerebrum
Author: Mehmet Mert Yildiran
Author-email: mert.yildiran@bil.omu.edu.tr
License: MIT
Description: Cerebrum
        ========
        
        An implementation of "Crossmodal Supervised Learning Algorithm with Time
        Series Memory Recording & Long Short-Term Memory Networks"
        
        Parts of The Cerebrum:
        
        ::
        
        		- Vision
        				- Amodal Perception
        				- Color Perception
        				- Depth Perception (in Future) (needs Stereoscopic Vision)
        				- Form Perception (in Future) (needs Stereoscopic Vision)
        				- Relative Velocity Perception (in Future) (needs Stereoscopic Vision)
        		- Hearing
        				- Speech Perception
        				- Rhythmic Perception
        				- Harmonic Perception (in Future) (WARNING: High Complexity)
        				- Acceleration Perception (in Future) (needs 2 units of Triple Axis Accelerometer)
        		- Language
        				- Speech Analysis
        				- Speech Synthesis
        		- Multisensorial (Not Yet Available)
        				- Touching (Not Yet Available)
        						- Mechanic Perception (in Future) (needs lots of Pressure Sensors)
        						- Heat & Cooling Perception (in Future) (needs lots of Temperature Sensors)
        				- Tasting (Not Yet Available)
        						- Solid/Fluid State Chemical Perception (in Future) (WARNING: Sensor Technology Not Available)
        				- Smelling (Not Yet Available)
        						- Gas State Chemical Perception (in Future) (WARNING: Sensor Technology Not Available)
        
        *Multisensorial Part (Touching, Tasting and Smelling) is not yet
        available. Because of their absence there should be a False Reward &
        Punishment Mechanism for Reinforcement Learning*
        
        		Cerebrum's purpose is getting continuous data inputs from different
        		types of sensors as events, depending on the predefined threshold
        		values and creating a complex time based relations between those
        		events in memory by Long Short-Term Memory Networks. Lastly creating
        		outputs triggered by stimuli, using already trained Artificial
        		Neural Networks.
        
        Version
        ~~~~~~~
        
        0.1.21
        
        Dependencies
        ~~~~~~~~~~~~
        
        Cerebrum uses a number of open source libraries to do the job:
        
        -  `Python 2.7 <https://www.python.org/download/releases/2.7/>`__ -
        	 a widely used general-purpose, high-level programming language.
        -  `PyAudio <https://people.csail.mit.edu/hubert/pyaudio/r>`__ -
        	 provides Python bindings for PortAudio, the cross platform audio API.
        -  `OpenCV <http://opencv.org/r>`__ - (Open Source Computer Vision)
        	 is a library of programming functions mainly aimed at real-time
        	 computer vision.
        -  `wave Module <https://docs.python.org/2/library/wave.html>`__ -
        	 provides a convenient interface to the WAV sound format.
        -  `datetime Module <https://docs.python.org/2/library/datetime.html>`__
        	 supplies classes for manipulating dates and times in both simple
        	 and complex ways.
        -  `os.path Module <https://docs.python.org/2/library/os.path.html>`__ -
        	 the path module suitable for the operating system Python is running
        	 on, and therefore usable for local paths.
        -  `sys Module <https://docs.python.org/2/library/sys.html>`__ -
        	 provides access to some variables used or maintained by the
        	 interpreter and to functions that interact strongly with the
        	 interpreter. It is always available.
        -  `audioop Module <https://docs.python.org/2/library/audioop.html>`__ -
        	 operates on sound fragments consisting of signed integer samples 8,
        	 16 or 32 bits wide, stored in Python strings.
        -  `NumPy <http://www.numpy.org/>`__ -
        	 the fundamental package for scientific computing with Python.
        -  `multiprocessing Module <https://docs.python.org/2/library/multiprocessing.html>`__ -
        	 a package that supports spawning processes using an API similar to
        	 the threading module.
        -  `imutils Module <https://pypi.python.org/pypi/imutils/0.2>`__ -
        	 a series of convenience functions to make basic image processing
        	 functions such as translation, rotation, resizing, skeletonization
        	 etc.
        -  `PyQtGraph <http://www.pyqtgraph.org/>`__ -
        	 a pure-python graphics and GUI library built on PyQt4 / PySide and numpy
        -  `PyQt4 <https://pypi.python.org/pypi/PyQt4>`__ -
        	 a comprehensive set of Python bindings for Digia's Qt cross platform GUI toolkit.
        -  `time Module <https://docs.python.org/2/library/time.html>`__ -
        	 provides various time-related functions.
        -  `argparse Module <https://docs.python.org/2.7/library/argparse.html>`__ -
        	 makes it easy to write user-friendly command-line interfaces.
        -  `os Module <https://docs.python.org/2/library/os.html>`__ -
        	 provides a portable way of using operating system dependent functionality.
        -  `subprocess Module <https://docs.python.org/2/library/subprocess.html>`__ -
        	 allows you to spawn new processes, connect to their
        	 input/output/error pipes, and obtain their return codes.
        -  `random Module <https://docs.python.org/2/library/random.html>`__ -
        	 pseudo-random number generators for various distributions.
        -  `pysrt Module <https://pypi.python.org/pypi/pysrt>`__ -
        	 SubRip (.srt) subtitle parser and writer
        -  `itertools Module <https://docs.python.org/2/library/itertools.html>`__ -
        	 implements a number of iterator building blocks inspired by
        	 constructs from APL, Haskell, and SML. Each has been recast in a form
        	 suitable for Python
        
Keywords: machine learining neural networks artifical intelligence long shor term memory audio video text captions real time
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
