subproduct of my tesis project Implementation of algorithms for the restoration of retinal images

RRtoolbox___init__.py

__author__ = 'Davtoh'
__all__ = ['lib','RRtools']

RRtoolbox__concepts.txt

memoization, caching, persistence
serializing and de-serializing a Python object structure
https://docs.python.org/2/glossary.html
https://docs.python.org/2/library/persistence.html

RRtoolbox__dependencies.txt

# three party
dill
cv2
numpy
matplotlib

# owned
chache
asift

RRtoolbox__developer_notes.txt

*Threat http://stackoverflow.com/questions/1865727/how-to-design-an-application-in-a-modular-way

Try to keep things loosely coupled, and use interfaces liberally to help.

I'd start the design with the Separation of Concerns. The major architectural layers are:

Problem Domain (aka. Engine, Back-end): the domain classes, which do all the actual work, have domain knowledge implement domain behaviour
Persistence: storage management for domain classes, database/filesystem layer
User Interface: the GUI, which talks to the domain classes
System Interfaces: talking to other systems, eg. networking, web services
The domain classes do the work, but don't know about the UI. The persistence layer knows about the domain classes, enough to save/load as required. The system interface layer abstracts away external systems, which lets you plug a simulator in behind while testing. The UI should ideally use MVC, for maximum flexibility.

Without putting too fine a point on it, one would not ordinarily look to Drupal as an exemplar of good architectural design. It has grown rather organically, and there have been many upheavals of the design, as evidenced by the regular plugin breakage upon system upgrades.

I would also echo what MicSim said, regarding carefully designing the plugin interface and writing multiple different plugins to exercise it. This is the only way to really flesh out the issues of how the app and plugins interact.

*http://docs.python-guide.org/en/latest/writing/structure/

*http://stackoverflow.com/questions/1707709/list-all-the-modules-that-are-part-of-a-python-package

RRtoolbox__pending_list.txt

# general purpose
root (in development)

# modules
asift (in development)
session (finished)

# packaging modules
core (in development)

# interpreter, commands
shell (in development)

# user interface
interface (pending)

RRtoolbox_ConfigFile.pkl

€}q(U_CONFIGFILEq
cdirectory
directory
q}q(UispathqˆUreprq]q(}q(UnoteqU
don't change!q	hˆh]q
U1C:\Users\Davtoh\Dropbox\PYTHON\projects\RRtoolboxqauUConfigFile.pklqeu…q
�qhbU
_init_toolqh}q(hU2contents of __init__.py file in TOOLPATH directoryqh‰h]q(U3
__author__ = 'Davtoh'
import sys
sys.path.append('q}q(hˆh]qUC:\Users\Davtoh\Desktop\RRtoolsqauU')qeUfilenameqU__init__.pyqu…q�qhbUTOOLPATHqhh…q�qhbUMAINPATHqhh…q �q!hbUTEMPPATHq"h}q#(hˆh]q$(hUtempq%eu…q&�q'h#bUTESTPATHq(h}q)(hˆh]q*U-C:\Users\Davtoh\Dropbox\PYTHON\projects\tesisq+au…q,�q-h)bULIBRARYPATHq.h}q/(hˆh]q0(hUlibq1eu…q2�q3h/bu.

RRtoolbox_core.py

__author__ = 'Davtoh'

import time

from RRtoolbox.lib.root import Logger,memoize,temp_created,temp_cleaned,temp_cleaners
from RRtoolbox.lib.config import getTools,ConfigFile

pkl_path = __file__.split(".")[0]+".pkl"

mylogger = Logger()
mylogger.throwAtError = False
@mylogger.tracer
def f(a, b=1, *pos, **named):
   a = b
   return a

mylogger.report()
import inspect,types

def tools(instance,modules):
    for key in modules.keys():
        moduleTool = getattr(modules[key],"tool","tool")
        classmethods = dict(inspect.getmembers(moduleTool, predicate=inspect.ismethod))
        if "__init__" in classmethods.keys(): del classmethods["__init__"]
        for method in classmethods:
            fn = types.MethodType(classmethods[method], instance, instance.__class__) # convert to bound method
            setattr(instance, fn.func_name, fn) # set fn method with name fn.func_name in instance

def tools2(instance,modules):
    for key in modules.keys():
        instance.__dict__[key] = getattr(modules[key],"tool","tool")

class rrbox(object):
    def __init__(self,*args):
        #configuration object
        self.tools = getTools(ConfigFile()['TOOLPATH'])
        tools2(self,self.tools)
    @memoize
    def asift(self):
        pass

if __name__ == '__main__':
    a = rrbox()
    f(1, 2, 3)
    f(a=2, x=4)
    mylogger.report()
    print "tools:",a.tools.keys()
    print dir(a.tools['descriptor'])
    print getattr(a.tools['descriptor'],"tool","tool")
    #memoize = a.tools['descriptor'].root.memoize
    #MEMORY = a.tools['descriptor'].root.MEMORY
    #a.tools['descriptor'].multipleASIFT.flush()

    @memoize(filename=pkl_path)
    def memtest(x):
        k=1
        time.sleep(10)
        for i in xrange(x):
            k+=123
        return k

    def test(x):
        print "processing...."
        return memtest(x)

    #print test(123)
    a.tools['descriptor'].asif_demo()
    #mm = a.tools['descriptor'].multipleASIFT
    #help(mm)
    #help(mm.flush)
    memtest.flush()
    print temp_created
    print temp_cleaned
    print temp_cleaners

RRtoolbox_lib___init__.py

__author__ = 'Davtoh'
__all__ = ['cache','overlay','root','session']

RRtoolbox_lib_cache.py

__author__ = 'Davtoh'
## READ: https://wiki.python.org/moin/PythonDecoratorLibrary

class cache(object):
    """
    Descriptor (non-data) for building an attribute on-demand on first use.
    @cache decorator is used for methods without inputs, ex:

    class x(object):
        @cache
        method_x(self):
            return self.data

    Cached data can be deleted in the decorated object to recalculate its value
    """
    def __init__(self, func):
        """
        Initialize cache with a property function
        """
        self.func = func # function handle
        #self.cache = {}
    # if method simulating getattr
    def __get__(self, instance, owner):  # if trying to get attribute
        # Build the attribute.
        cached = self.func(instance) #evaluate function over instance
        # Cache the value;
        # Creates variable (name) of value (cached) in (instance).
        # instance.name = cached
        setattr(instance, self.func.__name__, cached)
        return cached
    # if function
    def __call__(self, *args, **kwargs):
        argnames = self.func.func_code.co_varnames[:self.func.func_code.co_argcount] # variable names
        defaults = self.func.func_defaults or tuple() # get default variables else empty tuple
        argdefs = zip(argnames[-len(defaults):], defaults) # default arguments
        inputsdict = dict(argdefs + zip(argnames,args) + kwargs.items()) # get inputs,do not change order
        inputs = tuple(inputsdict.items()) # convert to tuple to be hashable
        if not inputs in self.__dict__:
            self.__dict__[inputs] = self.func(**inputsdict)
        return self.__dict__[inputs]

RRtoolbox_lib_config.py

__author__ = 'Davtoh'

import directory as dr
import session as sn
import pkgutil

# ----------------------------GLOBAL VARIABLES---------------------------- #
# PATHS
MAINPATH = dr.directory(dr.correctPath(-1,__file__),note= "don't change!")
TOOLPATH = dr.directory("C:\Users\Davtoh\Desktop\RRtools") # dr.directory("RRtools")-MAINPATH #
LIBRARYPATH = dr.directory("lib")-MAINPATH
TEMPPATH = dr.directory("temp")-MAINPATH
TESTPATH = dr.directory(r"C:\Users\Davtoh\Dropbox\PYTHON\projects\tesis")# dr.directory("tests")-MAINPATH #
# FILES
_CONFIGFILE = dr.directory('ConfigFile.pkl')-MAINPATH

# CONETENTS
_init_tool = dr.directory(["""
__author__ = 'Davtoh'
import sys
sys.path.append('""",TOOLPATH,"')"]
,ispath=False
,note="contents of __init__.py file in TOOLPATH directory"
,filename = "__init__.py")

# ----------------------------ConfigTool FUNCTIONS---------------------------- #

def makeToolDir(path = TOOLPATH,init = _init_tool):
    path = dr.mkPath(path)
    initfile = dr.joinPath(path,"__init__.py")
    with open(initfile, 'wb') as logger:
        logger.write(init)
    return True

def getPackagePath(package):
    """
    get the path of a package object
    :param package: package object or path
    :return: path to the package
    """
    if isinstance(package,str): # if path
        return package
    else: # if imported package
        return package.__path__[0]

def findModules(package,
    exclude = None,
    StrFound = "Found submodule {0} (is a package: {1})",
    StrNoFound = "No modules have been found"):
    """
    find modules from a package
    :param package: imported packaged or path (str)
    :param StrFound: message for found module
    :param StrNoFound: message where no module is found
    :return: dictionary containing importer,ispkg
    """
    path = getPackagePath(package)
    modules = {}
    for importer, modname, ispkg in pkgutil.walk_packages([path]):
        if exclude and modname in exclude:
            continue
        modules[modname] = importer,ispkg
        print(StrFound.format(modname, ispkg))
    if modules == {}: print(StrNoFound)
    return modules

def getModules(package,
    exclude = None,
    StrImported = "Imported submodule {0}..."):
    """
    import modules from a package
    :param package: imported packaged or path (str)
    :param StrImported: message for imported module
    :return: dictionary containing imported modules
    """
    path = getPackagePath(package)
    modules = {}
    for importer, modname, ispkg in pkgutil.walk_packages([path]):
        if exclude and modname in exclude:
            continue
        modules[modname] = importer.find_module(modname).load_module(modname)
        print(StrImported.format(modname, ispkg))
    return modules

def getTools(package):
    """
    obtain the tools of a directory for the RRtoolbox.
    The RRtools directory has to contain a the ConfigTool.py file.
    :param package: path to the directory or package object
    :return: a dictionary of imported modules
    """
    path = getPackagePath(package)
    modname = "__init__"
    try:
        pkgutil.get_importer(path).find_module(modname).load_module(modname)
    except AttributeError:
        print("No "+modname+" file found at "+path)
        raise
    except:
        print(modname+" could not be loaded from "+path)
        raise
    return getModules(path,exclude=[modname])

# ----------------------------ConfigFile FUNCTIONS---------------------------- #

def resetConfigFile(path = _CONFIGFILE):
    print "Creating default ConfigFile.pkl file..."
    #sn.saveSession(str(path),serializer(sn.getEnviromentSession(globals())))
    sn.saveSession(str(path),sn.getEnviromentSession(globals()))
    print "ConfigFile.pkl has been reseted successfully..."
    return 1

def loadConfigFile(path=_CONFIGFILE):
    try:
        print "Loading ConfigFile.pkl..."
        #return deserializer(sn.readSession(str(path)))
        return sn.readSession(str(path))
    except IOError:
        print "ConfigFile.pkl no found..."
        resetConfigFile()
        #archive = deserializer(sn.readSession(str(path)))
        archive = sn.readSession(str(path))
        print "Default ConfigFile.pkl read successfully..."
        return archive

def saveConfigFile(vardic, path=_CONFIGFILE, mode = False):
    """
    :param vardic: dictionary containg variables
    :param path: path to the configFile
    :param mode: 0- delete and save, 1- update without replace, 2- update replacing variables
    :return:
    """
    vardic = sn.getEnviromentSession(vardic)
    if mode:
        try:
            sn.updateSession(str(path),vardic, replace= mode - 1)
            return 1
        except IOError:
            sn.saveSession(str(path),vardic)
            return 2
    else: # to delete and replace
        sn.saveSession(str(path),vardic)
        return 1

# ----------------------------CLASSES---------------------------- #

class ConfigFile:
    def __init__(self, path=_CONFIGFILE):
        self.__path = str(path)
        self.loadConfigFile()
    def resetConfigFile(self):
        try:
            return resetConfigFile(self.__path)
        except IOError:
            return False
    def loadConfigFile(self):
        try:
            vars = loadConfigFile(self.__path)
            self.__dict__.update(vars)
            return vars
        except IOError:
            return None
    def saveConfigFile(self,mode=False):
        try:
            return saveConfigFile(self.__dict__,self.__path, mode)
        except IOError:
            return False
    def __getitem__(self, item):
        return self.__dict__[item]

class ConfigTool:
    def __init__(self, path=_CONFIGFILE):
        self.__path = str(path)
        self.loadConfigFile()
    def resetConfigFile(self):
        try:
            return resetConfigFile(self.__path)
        except IOError:
            return False
    def loadConfigFile(self):
        try:
            vars = loadConfigFile(self.__path)
            self.__dict__.update(vars)
            return vars
        except IOError:
            return None
    def saveConfigFile(self,mode=False):
        try:
            return saveConfigFile(self.__dict__,self.__path, mode)
        except IOError:
            return False
    def __getitem__(self, item):
        return self.__dict__[item]

if __name__ == '__main__':
    resetConfigFile()
    a = ConfigFile()
    makeToolDir()

RRtoolbox_lib_directory.py

__author__ = 'Davtoh'

import os,inspect,functools
import shutil

def getPath(filename=__file__):
    """get standard path from filename"""
    body,base = os.path.splitext(filename)
    if base != "":
        body = os.path.dirname(body)
    return os.path.abspath(body)

def mkPath(filepath):
    """make path for filename"""
    path = getPath(filepath)
    if not os.path.exists(path): os.makedirs(path)
    return path

def rmPath(filepath):
    """remove path from filename"""
    path = getPath(filepath)
    shutil.rmtree(path)
    return True

def getPathIndicator(path,pattern='/\\'):
    """
    obtain path indicator
    :param path: relative or absolute path (str)
    :param pattern: guess characters to compare path (str)
    :return: indicator (str)
    """
    i = len(path)
    while i and path[i-1] not in pattern: i -= 1
    head, tail = path[:i], path[i:]  # now tail has no slashes
    # remove trailing slashes from head, unless it's all slashes
    head2 = head
    count = 0
    while head2 and head2[-1] in pattern:
        head2 = head2[:-1]
        count += 1
    character = head[len(head)-count:len(head)] # get the slash character
    return character

def getShortenedPath(path,comp):
    """
    path is controlled to give absolute path from relative path or integer
    :param path: absolute path (str)
    :param comp: pattern or relative path (str) or integer representing level of folder
                determined by the separator Ex. C://level 1//level 2//...//level N or -1
    :return: path before matched comp  Ex: C://level 1//"comp" --> C://level 1
    """
    if type(comp) is str:
        if os.path.isabs(comp):
            comp = os.path.relpath(path,comp)
        return path.split(comp)[0]
    else:
        indicator = getPathIndicator(path)
        return indicator.join(path.split(indicator)[:comp])

def decoratePath(relative,indicator=os.path.sep):
    """
    decorated path is controlled to give absolute path from relative path
    :param relative: int or path
    :param indicator:
    :return:
    """
    def decorator(f):
        @functools.wraps(f)
        def wrapper(*args,**kwargs):
            path = f(*args,**kwargs)
            return indicator.join(getShortenedPath(path,relative).split(getPathIndicator(path)))
        return wrapper
    return decorator

def correctPath(relative,filename=__file__):
    """
    get path corrected from its relative path or level index
    :param relative: pattern or level in directory
    :param filename: path or file name
    :return: corrected path
    """
    return decoratePath(relative)(getPath)(filename)

def joinPath(absolute,relative):
    """
    joins an absolute path to a relative path => str
    """
    return os.path.join(str(absolute), str(relative)) # ensures updated version is processed

def repr2list(data,level=0):
    """
    converts the representation of a directory.repr to pickleable
    :param data: directory.repr of the form ["string",directory,...,directory.repr]
    :return: pickeable list
    """
    if isinstance(data,list): # list defines levels of directories
        if level == 0: # [level 0, ..., [level 1, [...[level N]...]], level 0]
            for i,value in enumerate(data): # process several objects in the list
                data[i] = repr2list(value,level+1)
            return data
        else: # convert anything to directory if not in level 0
            return directory(data)
    elif isinstance(data,str): # if string or directory
        return data
    else: # try to convert to directory
        return directory(data)

def repr2str(data, ispath = True):
    """
    converts the representation of a directory.repr to string
    :param data: directory.repr of the form ["string",directory,...,directory.repr]
    :return: converted string
    """
    if isinstance(data,list):
        if len(data)>1:
            string = str(repr2str(data[0]))
            for i in data[1:]:
                if ispath:
                    string = joinPath(string,repr2str(i)) # join paths
                else:
                    string += repr2str(i, ispath)
            return string
        else:
            return str(data[0]) # get single path
    elif isinstance(data, directory):
        return repr2str(data.repr, data.ispath)
    else:
        return str(data) # object must be string

def correctSTRBuiltin(self):
    """
    decorate all the built-in functions of class directory
    :return: built-in decorated function
    """
    def decorator(f):
        @functools.wraps(f)
        def wrapper(*args,**kwargs):
            return getattr(str(self),f.__name__,f.__name__)(*args,**kwargs)
        return wrapper
    return decorator

class directory(str):
    #repr = [""]
    def __new__(cls, data, ispath = None, copy = False, **kwargs):
        # data can be list, str, directory or dictionary
        data = directory.filterdata(data,ispath,kwargs)
        self = str.__new__(cls, repr2str(data["repr"],data["ispath"]))
        if copy:
            self.__dict__.update(data)
        else:
            self.__dict__ = data
        return self
    @staticmethod
    def filterdata(data, ispath = None, kwargs=None):
        if isinstance(data,directory):
            data = data.__dict__
        elif not isinstance(data,dict):
            if isinstance(data,list):
                data = {"repr":data}
            else:
                data = {"repr":[data]}
        if ispath: data["ispath"]= ispath
        if not data.has_key("ispath"): data["ispath"] = True # repr default
        if not data.has_key("repr"):
            data["repr"] = [""] # repr default
        else:
            data["repr"] = repr2list(data["repr"]) # ensure repr is maintained
        if kwargs: data.update(kwargs) # update data with kwargs
        return data
    def __add__(self, other):
        if type(other)==str: # it's exactly str an not directory
            return joinPath(self,other)
        return self.update_right(other)
    def __sub__(self, other):
        if type(other)==str: # it's exactly str an not directory
            return joinPath(other,self)
        return self.update_left(other)
    def update_right(self, other):
        self.repr.append(other) # it will be parsed at directory creation
        return directory(self) # string is immutable and must be renewed
    def update_left(self, other):
        self.repr.insert(0,other) # it will be parsed at directory creation
        return directory(self) # string is immutable and must be renewed
    def update(self, data = None):
        if isinstance(data,list): # if list
            if len(data)>len(self.repr):
                for i in xrange(len(self.repr)):
                    self.repr[i] = data[i]
                for j in xrange(i+1,len(data)):
                    self.repr.append(data[j])
            else:
                for i in xrange(len(data)):
                    self.repr[i] = data[i]
                del self.repr[i+1:]
            return directory(self) # string is immutable and must be renewed
        elif isinstance(data,dict): # if dictionary
            self.__dict__.update(data)
            return directory(self)
        elif data: # if not list or dict
            return self.update([data])
        else: # if None return updated version
            return directory(self)
    def __str__(self):
        return repr2str(self.repr, self.ispath)
    def __repr__(self):
        return str(self.repr)
    # TODO: implement 2 versions: one with directory-like functionality and other basic for str support
    """
    ### MAGIC FUNCTIONS
    def __nonzero__(self):
        return self == self.update()
    def __getitem__(self, item):
        return self.repr[item]
    def __len__(self):
        return len(self.repr)"""

if __name__=="__main__":
    import session as sn
    import dill
    ## TESTS
    a = directory("string1",sapo = "mamo")
    b = a.update(["string2",["string4","string 5"]])
    result = bool(a) # False
    result = bool(b) # True
    c = directory(["string3"])-a
    sn.saveSession("test.pkl",{"d",a})
    c = sn.readSession("test.pkl")
    print type(a)==directory
    print type(a) is directory
    print a is directory
    print a == directory
    print "with str"
    print type(a)==str
    print type(a) is str
    print a is str
    print a == str
    print isinstance(a,str)
    print type(a)
    print os.path.splitext(os.path.basename(__file__)) ### look here ###

RRtoolbox_lib_overlay.py

__author__ = 'Davtoh'
# shape = (height,width,chanel)=(y,x,c)
import numpy as np
import cv2

def axesintercept(coorSM,maxS,maxM):
    """
    intercept static axis (S) and mobile axis (M) with a coordinate connecting
    both axes from minS to minM.
                    S1                     S2
                  S0 |<---------------------|-----------> maxS
    coorSM <- - - - -|                      |
                    M1                     M2
        M0 <---------|--------------------->| maxM

    :param coorSM: coordinate of vector from S=0 to M=0
    :param maxS: value representing end of estatic axis
    :param maxM: value representing end of mobile axis
    :return: S1,S2,M1,M2
    """
    if coorSM<0: # left of the static axis
        S1 = 0
        S2 = np.min((np.max((0,maxM+coorSM)), maxS))
        M1 = np.min((maxM,-coorSM))
        M2 = np.min((maxM,S2-coorSM))
    else: # right of the static axis
        S1 = np.min((coorSM,maxS))
        S2 = np.min((maxS,coorSM+maxM))
        M1 = 0
        M2 = np.min((maxS-S1,maxM))
    return S1,S2,M1,M2

def matrixintercept(x,y,staticm,*mobilem):
    """
    intercepts planes x and y of a static matrix (staticm) with N mobile matrices (mobilem)
    translated from the origin to x,y coordinates
    :param x: x coordinate
    :param y: y coordinate
    :param staticm: static matrix
    :param mobilem: mobile matrices
    :return: ROI of intercepted matrices [staticm,*mobilem]
    """
    foreshape = np.min([i.shape[0:2] for i in mobilem],axis=0)
    BminY,BmaxY,FminY,FmaxY = axesintercept(y,staticm.shape[0],foreshape[0])
    BminX,BmaxX,FminX,FmaxX = axesintercept(x,staticm.shape[1],foreshape[1])
    ROIs = [staticm[BminY:BmaxY,BminX:BmaxX]]
    mobilem = [i[FminY:FmaxY,FminX:FmaxX] for i in mobilem]
    ROIs.extend(mobilem)
    return ROIs

def centerSM(coorSM,maxS,maxM):
    """
    center vector coorSM in both S and M axes
    :param coorSM: coordinate of vector from S to M centers
    :param maxS: value representing end of estatic axis
    :param maxM: value representing end of mobile axis
    :return: SM centered coordinate
    """
    return int((maxS)/2.0+coorSM-(maxM)/2.0)

def invertSM(coorSM,maxS,maxM):
    """
    invert S and M axes
    :param coorSM: coordinate of vector for SM inverted axes
    :param maxS: value representing end of estatic axis
    :param maxM: value representing end of mobile axis
    :return: SM coordinate on inverted SM axes
    """
    return int(maxS+coorSM-maxM)

def quartileM(coorX,coorY,maxX,maxY,cuartil=0):
    if cuartil==0:
        return coorX,coorY
    elif cuartil==4:
        coorX = coorX+maxX/2
        coorY = coorY+maxY/2
    elif cuartil==3:
        coorX = coorX-maxX/2
        coorY = coorY+maxY/2
    elif cuartil==2:
        coorX = coorX-maxX/2
        coorY = coorY-maxY/2
    elif cuartil==1:
        coorX = coorX+maxX/2
        coorY = coorY-maxY/2

    return coorX,coorY

def angleXY(coorX,coorY,angle):
    magnitude = np.sqrt(coorX*coorY)
    coorX = int(magnitude*np.cos(angle))
    coorY = int(-magnitude*np.sin(angle)) # y axis is downward
    return coorX,coorY

def invertM(coorSM,maxM):
    """
    invert M axis
    :param coorSM: coordinate of vector for M inverted axes
    :param maxS: value representing end of estatic axis
    :param maxM: value representing end of mobile axis
    :return: SM coordinate on S axis and inverted M axis
    """
    return int(coorSM-maxM)

def centerS(coor,maxS):
    """
    center vector coor in S axis
    :param coor: coordinate of vector from S center to M=0
    :param maxS: value representing end of estatic axis
    :return: S centered coordinate
    """
    return int(maxS/2.0+coor)

def centerM(coor,maxM):
    """
    center vector coor in M axis
    :param coor: coordinate of vector from S=0 to M center
    :param maxM: value representing end of mobile axis
    :return: M centered coordinate
    """
    return int(coor-maxM/2.0)

def convertXY(x,y,backshape,foreshape,flag=0,quartile=0,angle=None):
    """
    Convert absolute XY 0,0 coordinates to new system WZ
    :param x:
    :param y:
    :param backshape:
    :param foreshape:
    :param flag: flag for position (default=0)
            flag==0 : foreground to left up
            flag==1 : foreground to left down
            flag==2 : foreground to right up
            flag==3 : foreground to right down
            flag==4 : foreground at center of background
            flag==5 : XY 0,0 is at center of background
            flag==6 : XY 0,0 is at center of foreground
            flag==7 : XY 0,0 is at right down of foreground
    :param quartile: place Mobile image at quartile 1,2,3,4.
            if left quartile=0 image won't be moved.
    :param angle: angle in radians (defalut=None). if None it does not apply
    :return: W,Z
    """
    if flag==0: # left up
        pass
    elif flag==1:
        # vector coor to the end of both axes # left down
        y = invertSM(y,backshape[0],foreshape[0])
    elif flag==2:
        # vector coor to the end of both axes # right up
        x = invertSM(x,backshape[1],foreshape[1])
    elif flag==3:
        # vector coor to the end of both axes # right down
        x = invertSM(x,backshape[1],foreshape[1])
        y = invertSM(y,backshape[0],foreshape[0])
    elif flag==4:
        # vector coor centered in both axes
        x = centerSM(x,backshape[1],foreshape[1])
        y = centerSM(y,backshape[0],foreshape[0])
    elif flag==5:
        # vector coor centered in static axis
        x = centerS(x,backshape[1])
        y = centerS(y,backshape[0])
    elif flag==6:
        # vector coor centered in mobile axis
        x = centerM(x,foreshape[1])
        y = centerM(y,foreshape[0])
    elif flag==7:
        # vector coor to the S axis and inverted M axis
        x = invertM(x,foreshape[1])
        y = invertM(y,foreshape[0])

    x,y=quartileM(x,y,foreshape[1],foreshape[0],quartile)
    if angle is not None:
        x,y=angleXY(x,y,angle)

    return x,y

def fore2back(back,fore):
    """
    convert foreground to background
    :param back: background image
    :param fore: foreground image
    :return: reshaped bgr
    """
    temp = back.shape
    temp2 = fore.shape
    if len(temp) == 2:  # GRAY, YUV_I420, YUV_IYUV or YUV_YV12
        if len(temp2) == 3 and temp2[2] == 2:  # BGR555 or BGR565
            fore = cv2.cvtColor(fore, cv2.COLOR_BGR5552GRAY)
        elif len(temp2) == 3 and temp2[2] == 3:  # BGR or RGB
            fore = cv2.cvtColor(fore, cv2.COLOR_BGR2GRAY)
        elif len(temp2) == 3 and temp2[2] == 4:  # BGRA or RGBA
            fore = cv2.cvtColor(fore, cv2.COLOR_BGRA2GRAY)
    elif len(temp) == 3 and temp[2] == 2:  # BGR555 or BGR565
        if len(temp2) == 2:  # GRAY, YUV_I420, YUV_IYUV or YUV_YV12
            fore = cv2.cvtColor(fore, cv2.COLOR_GRAY2BGR555)
        elif len(temp2) == 3 and temp2[2] == 3:  # BGR or RGB
            fore = cv2.cvtColor(fore, cv2.COLOR_BGR2BGR555)
        elif len(temp2) == 3 and temp2[2] == 4:  # BGRA or RGBA
            fore = cv2.cvtColor(fore, cv2.COLOR_BGRA2BGR555)
    elif len(temp) == 3 and temp[2] == 3:  # BGR or RGB
        if len(temp2) == 2:  # GRAY, YUV_I420, YUV_IYUV or YUV_YV12
            fore = cv2.cvtColor(fore, cv2.COLOR_GRAY2BGR)
        elif len(temp2) == 3 and temp2[2] == 2:  # BGR555 or BGR565
            fore = cv2.cvtColor(fore, cv2.COLOR_BGR5552BGR)
        elif len(temp2) == 3 and temp2[2] == 4:  # BGRA or RGBA
            fore = cv2.cvtColor(fore, cv2.COLOR_BGRA2BGR)
    elif len(temp) == 3 and temp[2] == 4:  # BGRA or RGBA
        if len(temp2) == 2:  # GRAY, YUV_I420, YUV_IYUV or YUV_YV12
            fore = cv2.cvtColor(fore, cv2.COLOR_GRAY2BGRA)
        elif len(temp2) == 3 and temp2[2] == 2:  # BGR555 or BGR565
            fore = cv2.cvtColor(fore, cv2.COLOR_BGR5552BGRA)
        elif len(temp2) == 3 and temp2[2] == 3:  # BGR or RGB
            fore = cv2.cvtColor(fore, cv2.COLOR_BGR2BGRA)
    return fore

def gettransparency(matrix):
    """
    convert foreground to background
    :param back: background image
    :param bgr: foreground image
    :return: reshaped bgr
    """
    try:
        temp = matrix.shape
        if len(temp) == 3 and temp[2] == 4:  # BGRA or RGBA
            trans = matrix[:,:,3]
        else:
            trans = np.ones(temp[0:2],dtype=np.uint8)
            #trans = 1
    except:
        trans = 1
    return trans

def overlaypng(back,fore,alfa=None,alfainverted=False,under=False,flag=0):
    if alfa is None:
        alfa = gettransparency(fore)
    if np.max(alfa)>1:
        alfa = alfa/255.0

    def png(back,fore,dst):
        for chanel in xrange(3):
            dst[:,:,chanel] = fore[:,:,chanel]*(alfa) + back[:,:,chanel]*(1-alfa) #(2) without correction
        temp = dst.shape
        if not under and len(temp) == 3 and temp[2]>3:
            if flag==0: dst[:,:,3] = fore[:,:,3] + back[:,:,3]*(1-alfa) # normally replace inverted transparency of alfa in back (N); (2) superpose alfa in back (V)
            elif flag==1: dst[:,:,3] = fore[:,:,3]*(alfa) + back[:,:,3]*(1-alfa) # bloat and replace inverted transparency of alfa in back; (2) superpose bgr in back (V)
            elif flag==2: dst[:,:,3] = back[:,:,3]*(1-alfa) # superpose inverted transparent of alfa in back; (2) superpose inverted transparent COLOR of alfa in back
            elif flag==3: dst[:,:,3] = fore[:,:,3]*(1-alfa) # superpose inverted transparent of alfa in back; (2) superpose inverted transparent COLOR of alfa in back
            elif flag==4: dst[:,:,3] = back[:,:,3]*(alfa) # superpose transparent of alfa in back; (2) superpose transparent COLOR of alfa in back
            elif flag==5: dst[:,:,3] = fore[:,:,3]*(alfa) # superpose transparent of alfa in back; (2) superpose transparent COLOR of alfa in back
            #if under: (1) do nothing; (2) superpose bgr in visible parts of back
    if alfainverted:
        png(fore,back,back)
    else:
        png(back,fore,back)
    return back

def overlay(back,fore,alfa=None,alfainverted=False,under=False,flag=0):
    if alfa is None:
        alfa = gettransparency(fore)
    if np.max(alfa)>1:
        alfa = alfa/255.0
    # addWeighted operation
    temp = back.shape
    temp2 = fore.shape
    if len(temp) == 2:  # 1 channel
        fore = fore2back(back,fore)
        if alfainverted:
            back[:,:] = fore*(1-alfa) + back*(alfa)
        else:
            back[:,:] = fore*(alfa) + back*(1-alfa)
    elif len(temp) == 3 and temp[2]>=3 and len(temp2) == 3 and temp2[2] > 3: # 4 channels
        overlaypng(back,fore,alfa,alfainverted,under,flag)
    elif len(temp) == 3: # more than one channel but 4
        fore = fore2back(back,fore)
        if alfainverted:
            for chanel in xrange(temp[2]):
                back[:,:,chanel] = fore[:,:,chanel]*(1-alfa) + back[:,:,chanel]*(alfa)
        else:
            for chanel in xrange(temp[2]):
                back[:,:,chanel] = fore[:,:,chanel]*(alfa) + back[:,:,chanel]*(1-alfa)
    return back

def overlay2(back,fore):
    """
    Overlay foreground to x,y coordinates in background image
    :param back: background image (numpy array dim 3)
    :param fore: foreground image (numpy array dim 4). the fourth
    dimension is used for transparency
    :return: back (with overlay)

    #Example:
    import cv2
    import numpy as np
    import time
    a= time.time()
    back = cv2.imread("t1.jpg")
    temp = back.shape
    bgr = np.zeros((temp[0],temp[1],4), np.uint8)
    points = [(86, 162), (1219, 1112), (2219, 2112), (1277,3000),(86, 162)]
    col_in = (0, 0, 0,255)
    thickness = 10
    for i in range(len(points)-1):
        pt1 = (points[i][0], points[i][1])
        pt2 = (points[i+1][0], points[i+1][1])
        cv2.line(bgr, pt1, pt2, col_in, thickness)

    overlay(back,bgr)

    win = "overlay"
    cv2.namedWindow(win,cv2.WINDOW_NORMAL)
    cv2.imshow(win, back)
    print time.time()-a
    cv2.waitKey()
    cv2.destroyAllWindows()
    """
    # addWeighted operation
    data = fore[:,:,3]/255.0
    for chanel in (0,1,2):
        back[:,:,chanel] = fore[:,:,chanel]*data + back[:,:,chanel]*(1-data)
    return back

def overlayXY(x,y,back,fore,alfa=None,alfainverted=False,under=False,flag=0):
    """
    Overlay foreground image to x,y coordinates in background image.
    This function support images of different sizes with formats: BGR background
    and BGRA foreground of Opencv or numpy images
    :param x: x position in background
    :param y: y position in background
    :param back: background image (numpy array dim 3)
    :param fore: foreground image (numpy array dim 4). the fourth
    dimension is used for transparency
    :return: back (with overlay)

    #Example:
    import cv2
    back = cv2.imread("t1.jpg")
    bgr = cv2.imread("mustache.png",-1)
    x,y=convertXY(0,0,back.shape,bgr.shape,flag=1)
    overlayXY(x,y,back,bgr)
    win = "overlay"
    cv2.namedWindow(win,cv2.WINDOW_NORMAL)
    cv2.imshow(win, back)
    cv2.waitKey()
    cv2.destroyAllWindows()
    """
    if alfa is None:
        overlay(*matrixintercept(x,y,back,fore),alfainverted=alfainverted,under=under,flag=flag)
    else:
        overlay(*matrixintercept(x,y,back,fore,alfa),alfainverted=alfainverted,under=under,flag=flag)
    return back

RRtoolbox_lib_root.py

# system
from __future__ import print_function
import sys
import traceback
import functools
import time
import inspect
import tempfile
import types

import numpy as np
import matplotlib.animation as animation
import matplotlib.pyplot as plt
import cv2
import joblib
import directory as dr
import session as sn

#import os
from RRtoolbox.lib.config import ConfigFile

# ----------------------------GLOBAL VARIABLES---------------------------- #
__author__ = 'Davtoh'
Config = ConfigFile()
temp_created = {} # FOR DEBUGGING
temp_cleaned = {} # FOR DEBUGGING
temp_cleaners = {} # FOR CLEANING UP (flag,handle) # flag = True is safe to remove, flag = False is unsafe to remove

# ----------------------------BASIC FUNCTIONS---------------------------- #

def decorateInstanceMethods(self,decorator,excludeMth=("__init__"),includeMth=None):
    """
    decorate methods in an instance. It should be used in the __init__ method of a class.
    :param self: class instance.
    :param decorator: decorator function to apply to self.
    :param excludeMth: list of methods to exclude.
    :param includeMth: list of methods to include if not in exclude.
    if excludeMth is None then decorateInstanceMethods checks for includeMth list.
    if includeMth and excludeMth is None then all methods of self are decorated.
    :return:
    """
    classmethods = dict(inspect.getmembers(self, predicate=inspect.ismethod))
    #if "__init__" in classmethods.keys(): del classmethods["__init__"] # init method should not be decorated
    for key in classmethods:
        if excludeMth and key in excludeMth:
            continue
        if includeMth is None or key in includeMth:
            setattr(self, key, decorator(classmethods[key]))
    return self


# ----------------------------DECORATORS---------------------------- #

def addto(instance,funcname=None):
    def decorator(fn):
        fn = types.MethodType(fn, instance, instance.__class__) # convert to bound method
        if funcname:
            setattr(instance, funcname, fn)
        else:
            setattr(instance, fn.func_name, fn) # set fn method with name fn.func_name in instance
        return fn
    return decorator

def makememory(path, mmap_mode=None, compress=False, verbose=0):
    DUMPFILE = tempfile.mkdtemp(dir=path)
    temp_created[DUMPFILE] = "makememory" # report which function created the temp file
    MEMORY = joblib.Memory(DUMPFILE, mmap_mode, compress, verbose)
    return MEMORY

def memoize(memory=Config.TEMPPATH,filename=None):
    """
    decorated functions are faster by trading memory for time
    only hashable type values can be memoized
    :param memory: joblib.Memory or Path
    :param filename: path to save persistence between sessions
    :return:
    """
    def decorator(fn):

        if isinstance(memory,str): # try to get memory from cached file
            try:
                tmp = sn.readSession(filename)
                DUMPFILE = tmp[fn.func_name]
                if dr.getPath(DUMPFILE).startswith(dr.getPath(memory)):
                    cached_memory = joblib.Memory(dr.correctPath(-1,DUMPFILE), verbose=0)
                else:
                    cached_memory = makememory(memory)
                memoizedfn = cached_memory.cache(fn)
            except IOError: # cached dir does not exists
                new_memory = makememory(memory)
                memoizedfn = new_memory.cache(fn)
        else: # use provided memory
            memoizedfn = memory.cache(fn)

        DUMPFILE = dr.correctPath(-1,memoizedfn.cachedir)
        temp_created[DUMPFILE] = fn.func_name # report which function created the temp file

        def flush():
            try:
                dr.rmPath(DUMPFILE) # replaces memoizedfn.clear(True)
                temp_cleaned[DUMPFILE] = fn.func_name
                print(fn.func_name + " from "+DUMPFILE+" has been flushed...")
                del temp_cleaners[DUMPFILE]
            except:
                print(fn.func_name + " at "+DUMPFILE+" could NOT been flushed..." )

        if filename:
            @functools.wraps(fn)
            def wrapper(*args,**kwargs):
                try: # if possible get updated version of memoized function while running
                    tmp = sn.readSession(filename)
                    dummy = memoizedfn
                    dummy.cachedir = tmp[fn.func_name]
                    print(filename + " read for memoized session...")
                except IOError: # the file does not exists
                    dummy = memoizedfn
                    print(filename + " could NOT be read for memoized session...")
                except KeyError: # the file could exists without data
                    dummy = memoizedfn
                result = dummy(*args,**kwargs) # get result
                try: # update version of memoized function
                    sn.updateSession(filename,{fn.func_name:dummy.cachedir})
                except IOError: # else create new file
                    sn.saveSession(filename,{fn.func_name:dummy.cachedir})
                return result

            flush.__doc__ = "flush "+fn.func_name+" from "+filename+" session file"
            wrapper.flush = flush
            temp_cleaners[DUMPFILE] = (False,flush) # safe to remove
            return wrapper

        @functools.wraps(fn)
        def wrapper(*args,**kwargs):
            return memoizedfn(*args,**kwargs)
        wrapper.flush = flush
        temp_cleaners[DUMPFILE] = (True,flush) # unsafe to remove
        return wrapper
    return decorator


def tracer(instance, broadcast = True, report = True):
    def decorator(func):
        argnames = func.func_code.co_varnames[:func.func_code.co_argcount]
        fname = func.func_name
        @functools.wraps(func)
        def wrapper(*args,**kwargs):
            instance.func = func
            instance.stack = inspect.stack() # traceback.extract_stack()
            instance.funcname = fname
            instance.inputs = inspect.getcallargs(func,*args,**kwargs)
            instance.trace = inspect.trace()
            timeit = time.time()
            instance.time = time.localtime(timeit)
            e = None
            try:
                result = func(*args,**kwargs)
                if broadcast: instance.broadcast()
            except:
                result = None
                e = sys.exc_info()
            instance.exectime = time.time()-timeit
            instance.outputs = result
            instance.error = e
            if report: instance.report()
            instance.throwError()
            instance.renew()
            return result
        return wrapper
    return decorator

# ----------------------------CLASS OBJECTS---------------------------- #

class Logger(object):
    func = None
    funcname = ""
    inputs = {}
    outputs = ()
    stack = []
    trace = []
    error = None
    throwAtError = True
    time = 0
    exectime = 0
    eventHandle = None
    file = sys.stdout
    msg_report = "\nName: {self.funcname}\n" \
           "Type: {self.Type_}\n" \
           "Time of execution: {self.Time_}\n" \
           "Execution time: {self.exectime} secs\n" \
           "Inputs: {self.inputs}\n" \
           "Outputs: {self.outputs}\n"
    msg_no_executed = "No instance {self.funcname} has been exeuted"
    msg_executed = "{self.funcname} has been executed..."
    def __init__(self, **kwargs):
        """
        holds important information of an instanced object and
        can be used with @trace decorator for traceback purposes.
        :param func: object reference.
        :param funcname: object name.
        :param inputs: inputs pass to the object.
        :param outputs: outputs given by the object execution.
        :param time: initial time of execution.
        :param exectime: time of execution in seconds.
        :param writer: writer function where messages are passed.
        :param eventHandle: event function where object is passed when Logger.broadcast() is called.
        :param msg_report: message format to use in reports.
        :param msg_no_executed: massage format to pass to writer when object
            has not been executed and Logger.report() is called.
        :param msg_executed: massage format to use when object is executed and Logger.broadcast() is called.
        """
        #self.writer = writer
        self.__dict__.update(kwargs)
    def broadcast(self):
        """
        pass a notification message on object execution to the writer
        """
        self.writer(self.broadcast,self.msg_executed.format(self=self))
        if self.eventHandle: self.eventHandle(self)
    def report(self):
        """
        pass a report of the last executed object to the writer
        """
        if self.func is not None:
            self.writer(self.report,self.msg_report.format(self=self))
        else:
            self.writer(self.report,self.msg_no_executed.format(self=self))
    def throwError(self):
        if self.error:
            self.writer(self.throwError,self.error)
    def writer(self,method,*arg):
        FILE = self.file
        HEADER = (method.im_self,method.im_func,self.func)
        if method.im_func.__name__=="throwError":
            exc_type, exc_value, exc_traceback = arg[0]
            if self.throwAtError:
                raise
            else:
                print(HEADER,">>> ", file=FILE)
                traceback.print_exception(exc_type, exc_value, exc_traceback, file=FILE)
        else:
            print(HEADER,">>> ",*arg, file=FILE)
    @property
    def tracer(self):
        return tracer(self)
    @property
    def Type_(self):
        """
        returns type name (str)
        """
        return type(self.func).__name__
    @property
    def Time_(self):
        """
        returns formated time (str)
        """
        return time.asctime(self.time)
    def renew(self):
        """
        renew Instance
        """
        self.func = None
        self.funcname = ""
        self.inputs = {}
        self.outputs = ()
        self.stack = []
        self.trace = []
        self.error = None
        self.time = 0
        self.exectime = 0

# ----------------------------DECORATED FUNCTIONS---------------------------- #


# ----------------------------SPECIALISED FUNCTIONS---------------------------- #

def smooth(x,window_len=11,window='hanning'):
    """smooth the data using a window with requested size.

    This method is based on the convolution of a scaled window with the signal.
    The signal is prepared by introducing reflected copies of the signal
    (with the window size) in both ends so that transient parts are minimized
    in the begining and end part of the output signal.

    input:
        x: the input signal
        window_len: the dimension of the smoothing window; should be an odd integer
        window: the type of window from 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'
            flat window will produce a moving average smoothing.

    output:
        the smoothed signal

    example:

    t=linspace(-2,2,0.1)
    x=sin(t)+randn(len(t))*0.1
    y=smooth(x)

    see also:

    numpy.hanning, numpy.hamming, numpy.bartlett, numpy.blackman, numpy.convolve
    scipy.signal.lfilter

    TODO: the window parameter could be the window itself if an array instead of a string
    NOTE: length(output) != length(input), to correct this: return y[(window_len/2-1):-(window_len/2)] instead of just y.
    """

    if x.ndim != 1:
        raise ValueError, "smooth only accepts 1 dimension arrays."

    if x.size < window_len:
        raise ValueError, "Input vector needs to be bigger than window size."

    if window_len<3:
        return x

    if not window in ['flat', 'hanning', 'hamming', 'bartlett', 'blackman']:
        raise ValueError, "Window is on of 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'"

    s=np.r_[x[window_len-1:0:-1],x,x[-1:-window_len:-1]]

    if window == 'flat': #moving average
        w=np.ones(window_len,'d')
    else:
        w=eval('numpy.'+window+'(window_len)')

    y=np.convolve(w/w.sum(),s,mode='valid')
    return y

def normsigmoid(x,alfa,beta):
    """
    apply normalized sigmoid filter
    :param x: data to apply filter
    :param alfa: if alfa > 0: pass high filter, if alfa < 0: pass low filter, alfa must be != 0
    :param beta: shift from origin
    :return: filtered values normalized to range [-1 if x<0, 1 if x>=0]
    """
    return 1/(np.exp((beta-x)/alfa)+1)

def filter(alfa,beta1,beta2=None):
    """
    make filter
    :param alfa: steepness of filter
    :param beta1: first shift from origin
    :param beta2: second shift from origin
    alfa must be != 0
    if beta2 = None:
        if alfa > 0: high-pass filter, if alfa < 0: low-pass filter
    else:
        if beta2 > beta1:
            if alfa > 0: band-pass filter, if alfa < 0: band-stop filter
        else:
            if alfa > 0: inverted-band-pass filter, if alfa < 0: inverted-band-stop filter
    :return: filter funtion with intup levels
    # Example
    alfa,beta1,beta2 = 10,20,100
    myfilter = filter(alfa,beta1,beta2)
    print myfilter,type(myfilter)
    print myfilter.alfa,myfilter.beta1,myfilter.beta2
    """
    #http://en.wikipedia.org/wiki/Filter_%28signal_processing%29
    def bandstop(levels):
        return normsigmoid(levels,alfa,beta1)-normsigmoid(levels,alfa,beta2)+1.0
    def bandpass(levels):
        return normsigmoid(levels,alfa,beta1)-normsigmoid(levels,alfa,beta2)
    def invertedbandstop(levels):
        return normsigmoid(levels,alfa,beta2)-normsigmoid(levels,alfa,beta1)-1.0
    def invertedbandpass(levels):
        return normsigmoid(levels,alfa,beta2)-normsigmoid(levels,alfa,beta1)
    def lowpass(levels):
        return normsigmoid(levels,alfa,beta1)
    def highpass(levels):
        return normsigmoid(levels,alfa,beta1)
    if beta2 is None:
        if alfa < 0: # low pass
            func = lowpass
        else: # high pass
            func = highpass
    else:
        if beta2>beta1:
            if alfa < 0: # band stop
                func = bandstop
            else: # band pass
                func = bandpass
        else: # inverted
            temp = beta1
            beta1 = beta2
            beta2 = temp
            if alfa < 0: # inverted band stop
                func = invertedbandstop
            else: # inverted band pass
                func = invertedbandpass
    func.func_dict = {"alfa":alfa,"beta1":beta1,"beta2":beta2}
    return func

def sigmoid(x,alfa,beta,max=255,min=0):
    """
    apply sigmoid filter
    :param x: data to apply filter
    :param alfa: if alfa > 0: pass high filter, if alfa < 0: pass low filter, alfa must be != 0
    :param beta: shift from origin
    :param max: maximum output value
    :param min: minimum output value
    :return: filtered values ranging as [min,max]
    based from http://www.itk.org/Doxygen/html/classitk_1_1SigmoidImageFilter.html
    """
    if min: return (max-min)*normsigmoid(x,alfa,beta)+min
    else: return max*normsigmoid(x,alfa,beta)  # speeds up operation

def animateSimoid(alfas,betas,x=None,interval=1000,show=True,frames=None):
    """
    Show sigmoid filter or animation of it if alfas or betas are iterable
    :param alfas: array of alfa values or alfa value
    :param betas: array of beta values or beta value
    :param x: array of values or matrix to filter
    :param interval: time in millisecond of each update
    :return: None
    #example1:
    alfas = 10
    betas = np.linspace(0,256,256)
    simulateSimoid(alfas,betas)
    #example2:
    import cv2
    grayim = cv2.imread("asift2fore.png",0).astype("float")
    ani = simulateSimoid(125,np.linspace(0, 10, 13),grayim,100,show=False)
    ani.save('sigmoid.gif', fps=1)
    """
    if x is None:
        x = np.linspace(0, 255, 256)
    else:
        x = np.array(x,dtype=np.float)
    alfas = np.array(alfas,dtype=np.float)
    betas = np.array(betas,dtype=np.float)
    fig, ax = plt.subplots()
    # correct arrays
    if not len(alfas.shape): alfas = np.array((alfas,),dtype=np.float)
    if not len(betas.shape): betas = np.array((betas,),dtype=np.float)
    alfas[alfas==0]=0.01 # replacing 0 for aproximation
    if len(x.shape) == 1:  # if x is array
        ax_minx,ax_maxx = np.min(x),np.max(x) # control x axis
        ax_miny,ax_maxy = -1.5,1.5 # control y axis
        ax.hold(False) # plot replaces previous plots
        title = 'Sigmoid Filter: x = ['+str(ax_minx)+'-'+str(ax_maxx)+']'
        def updatefig(*args):
            args[1][0] = (args[1][0]+1)%len(alfas) # increase alfas index
            if args[1][0] ==0: # increase beta index
                args[1][1] = (args[1][1]+1)%len(betas)
            ax.plot(x, normsigmoid(x,alfas[args[1][0]],betas[args[1][1]]))
            ax.axis([ax_minx, ax_maxx, ax_miny, ax_maxy]) # set axis dimensions
            ax.set_title(title)
            ax.text(0, -1, ' alfa='+str(alfas[args[1][0]])+', beta='+str(betas[args[1][1]])) # set text
            return ax,
    else:  # if x is matrix array
        im = plt.imshow(normsigmoid(x,alfas[0],betas[0]), cmap=plt.get_cmap('jet'))
        title = 'Sigmoid Filter: x = '+str(x.shape)
        title_obj = plt.title(title) # plt.getp(title_obj)
        plt.colorbar()
        def updatefig(*args):
            args[1][0] = (args[1][0]+1)%len(alfas) # increase alfas index
            if args[1][0] ==0: # increase beta index
                args[1][1] = (args[1][1]+1)%len(betas)
            plt.setp(title_obj,text = title+', alfa='+str(alfas[args[1][0]])+', beta='+str(betas[args[1][1]])) # set title
            im.set_array(normsigmoid(x,alfas[args[1][0]],betas[args[1][1]]))
            plt.draw() # update plt title after image is shown
            return im,

    ab= np.array([-2,0])
    if frames is None:
        frames = len(alfas)*len(betas)
    ani = animation.FuncAnimation(fig, updatefig, frames, interval=interval, blit=True,fargs=[ab])
    if show: plt.show()
    return ani

def histogramGraph(img,show=True,size=None, hold=True):
    if not hold: plt.figure()
    sz = img.shape
    if len(sz)==2:
        histr = cv2.calcHist([img],[0],None,[256],[0,256])
        plt.plot(histr,color = "k")
        plt.xlim([0,256])
    else:
        color = ('b','g','r')
        for i,col in enumerate(color):
            histr = cv2.calcHist([img],[i],None,[256],[0,256])
            plt.plot(histr,color = col)
            plt.xlim([0,256])
    fig = plt.gcf()
    if size is not None: fig.set_size_inches(*size)
    if show: plt.show()
    return fig

def histogram(img):
    sz = img.shape
    if len(sz)==2:
        histr = [cv2.calcHist([img],[0],None,[256],[0,256])]
    else:
        histr = []
        for i in xrange(sz[2]):
            histr.append(cv2.calcHist([img],[i],None,[256],[0,256]))
    return histr

def hist_cdf(img,window_len=0,window='hanning'):
    hist,bins = np.histogram(img.flatten(),256,[0,256])
    if window_len: hist = smooth(hist,window_len,window) # if window_len=0 => no filter
    cdf = hist.cumsum()
    cdf_normalized = cdf*float(hist.max())/cdf.max()
    return hist,cdf_normalized.astype("int")

def mathgraph(y,colors= None, linedic={'ls':'-'},win=None,title=None,show=True,plt=plt):
    #http://matplotlib.org/users/pyplot_tutorial.html
    tp = type(y)
    if tp is not list and tp is not tuple: y = [y]
    if win is not None: plt.figure(win)
    if title is not None: plt.title(title)
    for i,axisy in enumerate(y):
        if colors is None:
            line = plt.plot(axisy)
        else:
            line = plt.plot(axisy,colors[i])
        plt.setp(line,**linedic)

    #plt.xlim([0,256])
    #fig = plt.gcf()
    if show: plt.show()
    return plt

def normalize(data):
    """normalize data to 1"""
    return data/np.max(data)

def normalize2(data):
    """normalize data to [-1,1]"""
    return data/np.max([np.max(data),-1.0*np.min(data)])

def spoint2opointfunc(scaled_shape,original_shape):
    """
    return function with parameters to change scaled point to original point
    :param scaled_shape:
    :param original_shape: shape of
    :return:
    # Example:
    forefunc = scaled2realfunc(imgf.shape,bgr.shape)
    backfunc = scaled2realfunc(imgb.shape,back.shape)
    p1fore = np.array([forefunc(i) for i in p1])
    p2back = np.array([backfunc(i) for i in p2])
    """
    rH = float(original_shape[0])
    rW = float(original_shape[1])
    sH = float(scaled_shape[0])
    sW = float(scaled_shape[1])
    op = np.array([rW/sW,rH/sH],dtype=np.float32)
    def scaled2original(p):
        #rx = sx*rW/sW
        #ry = sy*rH/sH
        return p*op
    return scaled2original

def sh2oh(sH,osrc_sh,sscr_sh,odst_sh,sdst_sh):
    """
    convert scaled transformation matrix (sH) to original (oH)
    :param sH: scaled transformation matrix
    :param osrc_sh: original source's shape
    :param sscr_sh: scaled source's shape
    :param odst_sh: original destine's shape
    :param sdst_sh: scaled destine's shape
    :return:
    """
    oH = sH.copy()
    #height, Width
    Hos,Wos = float(osrc_sh[0]),float(osrc_sh[1]) # original source
    Hss,Wss = float(sscr_sh[0]),float(sscr_sh[1]) # scaled source
    Hod,Wod = float(odst_sh[0]),float(odst_sh[1]) # original destine
    Hsd,Wsd = float(sdst_sh[0]),float(sdst_sh[1]) # scaled destine
    oH[:,0] = oH[:,0]*Wss/Wos # first row
    oH[:,1] = oH[:,1]*Hss/Hos # second row
    oH[0] = oH[0]*Wod/Wsd # first column
    oH[1] = oH[1]*Hod/Hsd # second column
    return oH

def brightness(img):
    return cv2.cvtColor(img,cv2.COLOR_BGR2HSV)[:,:,2]

def findminima(hist,thresh=None,side = None):
    mn = (np.diff(np.sign(np.diff(hist))) > 0).nonzero()[0] + 1 # local min
    if thresh is None: return mn
    if side == "left":
        if thresh> mn[0]:
            mn = mn[mn<=thresh]
        else:
            return mn[0]
    if side == "right":
        if thresh < mn[-1]:
            mn = mn[mn>=thresh]
        else:
            return mn[-1]
    distances = np.sqrt((mn-thresh)**2)
    idx = np.where(np.min(distances)==distances)[0]  # get index
    return mn[idx][0]

def getthresh(gray):
    hist,cdf = hist_cdf(gray,11)
    th1 = 130 #np.min(np.where(cdf.max()*0.2<=cdf))
    th2 = np.max(np.where(hist.max()==hist))
    th3 = np.min(np.where(np.mean(cdf)<=cdf))
    th4=findminima(hist,np.mean([th1,th2,th3]))
    return th4

def threshold(src, thresh, maxval, type):
    kz = np.mean(src.shape)/50
    kernel = np.ones((kz,kz),np.uint8)
    retval,th = cv2.threshold(src, thresh, maxval, type)
    th = cv2.morphologyEx(th, cv2.MORPH_OPEN, kernel)
    return th

def pad(gray,pad_val,pad_width=1):
    gray[0:pad_width,:] = pad_val
    gray[:,0:pad_width] = pad_val
    gray[-1:-1-pad_width:-1,:] = pad_val
    gray[:,-1:-1-pad_width:-1] = pad_val
    return gray

def retinalmask(gray,invert = False):
    thresh = getthresh(gray) # obtain optimus threshold
    rough_mask=threshold(gray,thresh,1,0)
    contours,hierarchy = cv2.findContours(rough_mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    index,maxarea = 0,0
    for i in xrange(len(contours)):
        area = cv2.contourArea(contours[i])
        if area>maxarea: index,maxarea = i,area
    cnt = contours[index]
    ellipse = cv2.fitEllipse(cnt)
    if invert:
        mask = np.ones(gray.shape,dtype=np.uint8)
        cv2.ellipse(mask,ellipse,0,-1)
    else:
        mask = np.zeros(gray.shape,dtype=np.uint8)
        cv2.ellipse(mask,ellipse,1,-1)
    return mask

def simulateLens(img, scaled_shape = (300,300), parameters = (10,30,None)):
    sz = img.shape[0:2] # get original image size
    scalepoints = spoint2opointfunc(scaled_shape,sz) # make rescaling function: scaled point -to- original point function
    scaled_img = cv2.resize(img,scaled_shape) # resize to scaled image
    fore2 = scaled_img.copy()

    if parameters is not None:
        myfilter = filter(*parameters) # alfa,beta1,beta2
        fore2=myfilter(fore2.astype("float"))*255#*fore.astype("float")
        fore2 = fore2.astype("uint8")

    P = brightness(fore2) # get scaled image brightness
    thresh,sure_bg = cv2.threshold(P,0,1,cv2.THRESH_BINARY+cv2.THRESH_OTSU) # obtain over threshold
    thresh,sure_fg = cv2.threshold(P,thresh+10,1,cv2.THRESH_BINARY)

    markers = np.ones_like(sure_fg).astype("int32") # make background markers
    markers[sure_bg==1]=0 # mark unknown markers
    markers[sure_fg==1]=2 # mark sure object markers

    cv2.watershed(scaled_img,markers) # get watershed on markers

    thresh,lastthresh = cv2.threshold(markers.astype("uint8"),1,1,cv2.THRESH_BINARY) # get binary image of contour
    # find biggest area and contour
    contours,hierarchy = cv2.findContours(lastthresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    index = 0
    maxarea = 0
    for i in xrange(len(contours)):
        area = cv2.contourArea(contours[i])
        if area>maxarea:
            index = i
            maxarea = area
    cnt = contours[index]
    cnt2 = np.int32(scalepoints(cnt)) # rescale contour to original image contour
    ellipse = cv2.fitEllipse(cnt2) # get ellipse for original image to simulate lens
    mask = np.ones(sz,dtype=np.uint8) # create mask
    cv2.ellipse(mask,ellipse,0,-1) # project lens over mask
    # simulate lens
    img[mask>0]=0 # use mask to project black color over original image
    return img,mask

def getalfa(foregray,backgray,window):
    backmask = normalize(normsigmoid(backgray,10,180)+normsigmoid(backgray,3.14,192)+normsigmoid(backgray,-3.14,45))
    foremask = normalize(normsigmoid(foregray,-1,242)*normsigmoid(foregray,3.14,50))
    foremask = normalize(foremask * backmask)
    foremask[foremask>0.9] = 2.0
    ksize = (21,21)
    foremask = normalize(cv2.blur(foremask,ksize))
    foremask *= normalize(window)
    return foremask

def imEqualization(img):
    # get hist and cdf from img
    hist,bins = np.histogram(img.flatten(),256,[0,256])
    cdf = hist.cumsum()
    # get equalized img in img2
    cdf_m = np.ma.masked_equal(cdf,0) # masking to leave out 0
    cdf_m = (cdf_m - cdf_m.min())*255/(cdf_m.max()-cdf_m.min()) # applying equalization
    cdf = np.ma.filled(cdf_m,0).astype('uint8')
    return cdf[img], cdf

RRtoolbox_lib_session.py

"""
    session module made by Davtoh and powered by dill

dill license:

This software is part of the open-source mystic project at the California
Institute of Technology, and is available subject to the conditions and
terms laid out below. By downloading and using this software you are
agreeing to the following conditions.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met::

    - Redistribution of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.

    - Redistribution in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentations and/or other materials provided with the distribution.

    - Neither the name of the California Institute of Technology nor
      the names of its contributors may be used to endorse or promote
      products derived from this software without specific prior written
      permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Copyright (c) 2015 California Institute of Technology. All rights reserved.

"""

__author__ = 'Davtoh'

import dill  # dill must be >= 0.2.4 download: https://pypi.python.org/pypi/dill#downloads
# see print dill.license() https://github.com/uqfoundation
#import jsonpickle # http://jsonpickle.github.io/
import types
__excludeType = [types.FunctionType,types.ModuleType,types.NoneType,types.ClassType,types.TypeType]
__excludeVar = []
__excludePattern = ['__']
#dill.detect.trace(True)

def getEnviromentSession(
        enviroment = globals()
    ):
    """
    gets the filtered session from the global variables
    :return: dictionary containing filtered session
    """
    #globals(), dir(), [type(enviroment[keys]) for keys in enviroment]
    session = {}
    for keys in enviroment.keys():
        if __excludePattern != [] and keys.startswith(*__excludePattern):
            continue
        if not (type(enviroment[keys]) in __excludeType or keys in __excludeVar):
            session[keys] = enviroment[keys]
    return session

def saveSession(filepath, dicvar, helper = None):
    """

    :param filepath:
    :param dicvar:
    :return:
    """
    # safely save session file
    with open(filepath, 'wb') as logger:
        if helper:
            return dill.dump(helper(dicvar), logger, dill.HIGHEST_PROTOCOL) # save dictionary
        else:
            return dill.dump(dicvar, logger, dill.HIGHEST_PROTOCOL) # save dictionary

def readSession(filepath, helper=None):
    """

    :param filepath:
    :return:
    """
    # safely read session file
    with open(filepath, 'rb') as logger:
        dicvar = dill.load(logger) # get session
    if helper:
        return helper(dicvar)
    else:
        return dicvar

def updateSession(filepath, dicvar, replace=True, rdhelper=None, svhelper=None):
    """

    :param filepath:
    :param dicvar:
    :param replace:
    :return:
    """
    current = readSession(filepath,rdhelper)
    if replace: # update by replacing existing values
        current.update(dicvar)
    else: # update without replacing existing values
        for key in dicvar:
            if not current.has_key(key):
                current[key] = dicvar[key]
    saveSession(filepath, current, svhelper) # save updated session

def flushSession(filepath):
    """

    :param filepath:
    :return:
    """
    readSession(filepath)
    saveSession(filepath, {}) # save updated session

def checkFromSession(filepath, varlist):
    """

    :param filepath:
    :param varlist:
    :return:
    """
    current = readSession(filepath)
    cmplist = varlist[:]
    for i,var in enumerate(varlist): # checking variables
        cmplist[i] = current.has_key(var)
    return cmplist

def deleteFromSession(filepath, varlist):
    """

    :param filepath:
    :param varlist:
    :return:
    """
    current = readSession(filepath)
    for var in varlist: # deleting variables
        del(current[var])
    saveSession(filepath, current) # save updated session

RRtoolbox_lib_test.pkl

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    ## THIS __doc__ IS OUTDATED
    dynamic paths and manipulation as a string. By Davtoh

    Because examples are better than explanations!!

    ##Ex 1:
    directory(["C:\dir1","\"]) #=> "C:"
    directory(["C:\dir1\"]) #=> "C:\dir1\"
    directory(["C:\dir1","\","dir2"]) #=> "C:dir2"

    ##Ex 2:

    MAINPATH = directory("C:\main1")  #=> (Creates a directory object and assign to local namespace variable MAINPATH)
    SECOND = directory("dir1")-MAINPATH  #=> "C:\main1\dir1" (Creates, operates and assigns object to SECOND.
                                         #                  NOTE: MAINPATH is bound to the object in variable SECOND)
    MAINPATH.update("C:\main2") #=> (MAINPATH has been updated but not assigned to its namespace value)
    print SECOND #=> "C:\main2\dir1" (prints real value but namespace variable SECOND is not updated)
    "" + SECOND #=> "C:\main1\dir1" (returns a str object containing the old value of SECOND)
    SECOND + "" #=> "C:\main2\dir1\" (returns a str object containing the updated value of SECOND + '\')
    "" + str(SECOND) #=> "C:\main2\dir1" (using the buil-in str function ensures that the variable gets the last update)
    SECOND.startswith("C:\main2\dir1") #=> True (call to buil-in methods uses updated string)
    SECOND = SECOND.update() #=> "C:\main2\dir1" (variable SECOND has been assigned to the to the updated directory object)
    "" + SECOND #=> "C:\main2\dir1" (now that SECOND has been reassigned to the updated version its real value is evident)
    THIRD = SECOND + "dir2" #=> "C:\main2\dir1\dir2" (returns a str object NOT associated with directory class)
    FOURTH = SECOND + directory("dir2") #=> "C:\main2\dir1\dir2" (operations between directories updates the first operand)
    print SECOND #=> "C:\main2\dir1\dir2" (then, str(FOURTH) == str(SECOND) is True, FOURTH == SECOND is False
                 #                       FOURTH == SECOND.update() is True too!)
    SECOND == SECOND.update() #=> False (this way, the user can know if the variable is up to date)

    FIFTH = directory([SECOND,directory("dir3")]) #=> "C:\main2\dir1\dir2\dir3" (jet, another directory object)
    SECOND.update(MAINPATH)
    print FIFTH #=> "C:\main2\dir3" (of course, FIFTH variable must be updated)
    MAINPATH.update("C:\main3")
    print FIFTH #=> "C:\main3\dir3" (of course, if MAINPATH is updated then SECOND is updated too, and so on updating FIFTH)

    SECOND.startswith(MAINPATH) #=> False
    MAINPATH = MAINPATH.update() #=> (of course, MAINPATH must be reassigned to maintain namespace variable updated)
    SECOND.startswith(MAINPATH) #=> True

    type(SECOND) #=> <class '__main__.directory'>
    type(THIRD) #=> <type 'str'>
    type(FOURTH) #=> <class '__main__.directory'>
    type(FIFTH) #=> <class '__main__.directory'>

    ##Ex 3:

    M1 = directory("C:\main")
    M2 = directory("dir2")-M1
    M3 = directory("dir3")
    M5 = directory([M2,M3])
    M2 = M2+directory("dir2_2")
    M3 = M3+directory("dir3_3")
    print M5

    ##Ex 4:

    M1 = directory("C:\main")
    M2 = directory("dir2")-M1
    M3 = directory("dir3")-M2
    M2 = M2+M3 # DEATH, obviously

    qdU__getinitargs__qeh(hU¶c


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RRtoolbox_read me.txt

RRToolbox (Retinal Restauration Toolbox)

RRtoolbox_run.py

__author__ = 'Davtoh'
# This script has been made to test and run the core.py and shell.py modules.

from pycallgraph import PyCallGraph
from pycallgraph.output import GraphvizOutput

from core import rrbox
graphviz = GraphvizOutput()
graphviz.output_file = 'run.png'

with PyCallGraph(output=graphviz):
    a = rrbox()
    a.modules['descriptor'].asif_demo()

RRtoolbox_shell.py

__author__ = 'Davtoh'

import getopt
import sys

flags = ''
longopts = ('feature=','xxx=')

def shell_parser(syslist,flags=flags,longopts=longopts):
    opts, args = getopt.getopt(syslist, flags, longopts)  # convert command
    opts = dict(opts)
    return opts, args

def shell_processor(commands):
    parsed_commands = []
    for command in commands:
        parsed_commands.append(shell_parser(command)) # opts, args

class shell:
    pass

if __name__ == '__main__':
    #getting commands from command pront
    opts, args = shell_parser(sys.argv[1:])
    print opts,args
    #detector, matcher = init_feature(feature_name)

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_metadata.json

{"duration": 17.66700005531311, "input_args": {"imgs": "[array([[23, 26, 27, ..., 13, 11, 11],\n       [24, 21, 22, ..., 14, 15, 16],\n       [27, 27, 24, ..., 15, 15, 13],\n       ..., \n       [17, 18, 23, ..., 45, 46, 43],\n       [19, 20, 22, ..., 50, 50, 49],\n       [24, 23, 24, ..., 48, 56, 57]], dtype=uint8), array([[18, 19, 16, ..., 14, 14, 15],\n       [20, 19, 17, ..., 16, 16, 17],\n       [23, 19, 18, ..., 19, 17, 16],\n       ..., \n       [28, 31, 38, ..., 13, 13, 11],\n       [28, 29, 35, ..., 12, 12, 11],\n       [37, 32, 34, ..., 10, 10, 10]], dtype=uint8)]"}}

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_output.pkl

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RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_output.pkl_02.npy

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RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleASIFT-alias_func_code.py

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_4fa2fa552c5a79f45832e2dd66725cf3_metadata.json

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_4fa2fa552c5a79f45832e2dd66725cf3_output.pkl

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_4fa2fa552c5a79f45832e2dd66725cf3_output.pkl_01.npy

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_4fa2fa552c5a79f45832e2dd66725cf3_output.pkl_02.npy

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_552cd56f36c444e968878ea037b04f21_metadata.json

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_552cd56f36c444e968878ea037b04f21_output.pkl

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_552cd56f36c444e968878ea037b04f21_output.pkl_01.npy

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_552cd56f36c444e968878ea037b04f21_output.pkl_02.npy

RRtoolbox_temp_tmphaissi_joblib___main__-C%3A-Users-Davtoh-Dropbox-PYTHON-projects-RRtoolbox-RRtools-descriptor_multipleMATCH-alias_func_code.py

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_metadata.json

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_output.pkl

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_output.pkl_01.npy

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleASIFT-alias_537fc135fc03ef7f5fa0a9b7a2f6b960_output.pkl_02.npy

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleASIFT-alias_func_code.py

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleMATCH-alias_ad45a477940de0be324f3bdb9761161c_metadata.json

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleMATCH-alias_ad45a477940de0be324f3bdb9761161c_output.pkl

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleMATCH-alias_ad45a477940de0be324f3bdb9761161c_output.pkl_01.npy

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleMATCH-alias_ad45a477940de0be324f3bdb9761161c_output.pkl_02.npy

RRtoolbox_temp_tmphaissi_joblib_descriptor_multipleMATCH-alias_func_code.py