cd ..
cd # back to home dir
cd ~/p2 # ~ means home dir as well
ls # dir
# install vim: sudo is to notify running as administrater,
# apt-get install to install package,
# vim is a common editor (extension of vi)
sudo apt-get install vim
sudo apt-cache search vim # search packages relating to vi
gedit tmp.py # open to edit a file
ctrl-z # break the current job
bg # send job to background
fg # send job back to foreground
ctrl-c # kill foreground job
ps aux | grep gedit # list all jobs and then search for "gedit" jobs
kill -9 12345 # kill job with job number 12345
# extract the audio channel of dummy.mp4
# audio format suppose to be aac though
# change extension (.ac3/.flac) accordingly
ffmpeg -i dummy.mp4 -acodec copy -vn audio.aac
ls -1 \*.mp4|sed 's/\(.*\)\.mp4/ffmpeg -i "&" -acodec copy -vn "\1.aac"/'|sh
sudo apt-get install python-virtualenv
virtualenv ~/p2 # create a virtualenv with python2
virtualenv --python=/usr/bin/python3 ~/p3 # create a virtualenv with python3
source ~/p2/bin/activate
For windows
conda create -n p36 python=3.6 # dlib seems to be faster than in 3.77
conda activate p36
help('if')
The "if" statement ****************** The "if" statement is used for conditional execution: if_stmt ::= "if" assignment_expression ":" suite ("elif" assignment_expression ":" suite)* ["else" ":" suite] It selects exactly one of the suites by evaluating the expressions one by one until one is found to be true (see section Boolean operations for the definition of true and false); then that suite is executed (and no other part of the "if" statement is executed or evaluated). If all expressions are false, the suite of the "else" clause, if present, is executed. Related help topics: TRUTHVALUE
import numpy
# help(numpy)
# help(numpy.sort)
numpy.sort?
dir(numpy)
['ALLOW_THREADS', 'AxisError', 'BUFSIZE', 'Bytes0', 'CLIP', 'ComplexWarning', 'DataSource', 'Datetime64', 'ERR_CALL', 'ERR_DEFAULT', 'ERR_IGNORE', 'ERR_LOG', 'ERR_PRINT', 'ERR_RAISE', 'ERR_WARN', 'FLOATING_POINT_SUPPORT', 'FPE_DIVIDEBYZERO', 'FPE_INVALID', 'FPE_OVERFLOW', 'FPE_UNDERFLOW', 'False_', 'Inf', 'Infinity', 'MAXDIMS', 'MAY_SHARE_BOUNDS', 'MAY_SHARE_EXACT', 'MachAr', 'ModuleDeprecationWarning', 'NAN', 'NINF', 'NZERO', 'NaN', 'PINF', 'PZERO', 'RAISE', 'RankWarning', 'SHIFT_DIVIDEBYZERO', 'SHIFT_INVALID', 'SHIFT_OVERFLOW', 'SHIFT_UNDERFLOW', 'ScalarType', 'Str0', 'Tester', 'TooHardError', 'True_', 'UFUNC_BUFSIZE_DEFAULT', 'UFUNC_PYVALS_NAME', 'Uint64', 'VisibleDeprecationWarning', 'WRAP', '_NoValue', '_UFUNC_API', '__NUMPY_SETUP__', '__all__', '__builtins__', '__cached__', '__config__', '__deprecated_attrs__', '__dir__', '__doc__', '__expired_functions__', '__file__', '__getattr__', '__git_version__', '__loader__', '__name__', '__package__', '__path__', '__spec__', '__version__', '_add_newdoc_ufunc', '_distributor_init', '_financial_names', '_globals', '_mat', '_pytesttester', '_version', 'abs', 'absolute', 'add', 'add_docstring', 'add_newdoc', 'add_newdoc_ufunc', 'alen', 'all', 'allclose', 'alltrue', 'amax', 'amin', 'angle', 'any', 'append', 'apply_along_axis', 'apply_over_axes', 'arange', 'arccos', 'arccosh', 'arcsin', 'arcsinh', 'arctan', 'arctan2', 'arctanh', 'argmax', 'argmin', 'argpartition', 'argsort', 'argwhere', 'around', 'array', 'array2string', 'array_equal', 'array_equiv', 'array_repr', 'array_split', 'array_str', 'asanyarray', 'asarray', 'asarray_chkfinite', 'ascontiguousarray', 'asfarray', 'asfortranarray', 'asmatrix', 'asscalar', 'atleast_1d', 'atleast_2d', 'atleast_3d', 'average', 'bartlett', 'base_repr', 'binary_repr', 'bincount', 'bitwise_and', 'bitwise_not', 'bitwise_or', 'bitwise_xor', 'blackman', 'block', 'bmat', 'bool8', 'bool_', 'broadcast', 'broadcast_arrays', 'broadcast_shapes', 'broadcast_to', 'busday_count', 'busday_offset', 'busdaycalendar', 'byte', 'byte_bounds', 'bytes0', 'bytes_', 'c_', 'can_cast', 'cast', 'cbrt', 'cdouble', 'ceil', 'cfloat', 'char', 'character', 'chararray', 'choose', 'clip', 'clongdouble', 'clongfloat', 'column_stack', 'common_type', 'compare_chararrays', 'compat', 'complex128', 'complex256', 'complex64', 'complex_', 'complexfloating', 'compress', 'concatenate', 'conj', 'conjugate', 'convolve', 'copy', 'copysign', 'copyto', 'core', 'corrcoef', 'correlate', 'cos', 'cosh', 'count_nonzero', 'cov', 'cross', 'csingle', 'ctypeslib', 'cumprod', 'cumproduct', 'cumsum', 'datetime64', 'datetime_as_string', 'datetime_data', 'deg2rad', 'degrees', 'delete', 'deprecate', 'deprecate_with_doc', 'diag', 'diag_indices', 'diag_indices_from', 'diagflat', 'diagonal', 'diff', 'digitize', 'disp', 'divide', 'divmod', 'dot', 'double', 'dsplit', 'dstack', 'dtype', 'e', 'ediff1d', 'einsum', 'einsum_path', 'emath', 'empty', 'empty_like', 'equal', 'errstate', 'euler_gamma', 'exp', 'exp2', 'expand_dims', 'expm1', 'extract', 'eye', 'fabs', 'fastCopyAndTranspose', 'fft', 'fill_diagonal', 'find_common_type', 'finfo', 'fix', 'flatiter', 'flatnonzero', 'flexible', 'flip', 'fliplr', 'flipud', 'float128', 'float16', 'float32', 'float64', 'float_', 'float_power', 'floating', 'floor', 'floor_divide', 'fmax', 'fmin', 'fmod', 'format_float_positional', 'format_float_scientific', 'format_parser', 'frexp', 'frombuffer', 'fromfile', 'fromfunction', 'fromiter', 'frompyfunc', 'fromregex', 'fromstring', 'full', 'full_like', 'gcd', 'generic', 'genfromtxt', 'geomspace', 'get_array_wrap', 'get_include', 'get_printoptions', 'getbufsize', 'geterr', 'geterrcall', 'geterrobj', 'gradient', 'greater', 'greater_equal', 'half', 'hamming', 'hanning', 'heaviside', 'histogram', 'histogram2d', 'histogram_bin_edges', 'histogramdd', 'hsplit', 'hstack', 'hypot', 'i0', 'identity', 'iinfo', 'imag', 'in1d', 'index_exp', 'indices', 'inexact', 'inf', 'info', 'infty', 'inner', 'insert', 'int0', 'int16', 'int32', 'int64', 'int8', 'int_', 'intc', 'integer', 'interp', 'intersect1d', 'intp', 'invert', 'is_busday', 'isclose', 'iscomplex', 'iscomplexobj', 'isfinite', 'isfortran', 'isin', 'isinf', 'isnan', 'isnat', 'isneginf', 'isposinf', 'isreal', 'isrealobj', 'isscalar', 'issctype', 'issubclass_', 'issubdtype', 'issubsctype', 'iterable', 'ix_', 'kaiser', 'kernel_version', 'kron', 'lcm', 'ldexp', 'left_shift', 'less', 'less_equal', 'lexsort', 'lib', 'linalg', 'linspace', 'little_endian', 'load', 'loads', 'loadtxt', 'log', 'log10', 'log1p', 'log2', 'logaddexp', 'logaddexp2', 'logical_and', 'logical_not', 'logical_or', 'logical_xor', 'logspace', 'longcomplex', 'longdouble', 'longfloat', 'longlong', 'lookfor', 'ma', 'mafromtxt', 'mask_indices', 'mat', 'math', 'matmul', 'matrix', 'matrixlib', 'max', 'maximum', 'maximum_sctype', 'may_share_memory', 'mean', 'median', 'memmap', 'meshgrid', 'mgrid', 'min', 'min_scalar_type', 'minimum', 'mintypecode', 'mod', 'modf', 'moveaxis', 'msort', 'multiply', 'nan', 'nan_to_num', 'nanargmax', 'nanargmin', 'nancumprod', 'nancumsum', 'nanmax', 'nanmean', 'nanmedian', 'nanmin', 'nanpercentile', 'nanprod', 'nanquantile', 'nanstd', 'nansum', 'nanvar', 'nbytes', 'ndarray', 'ndenumerate', 'ndfromtxt', 'ndim', 'ndindex', 'nditer', 'negative', 'nested_iters', 'newaxis', 'nextafter', 'nonzero', 'not_equal', 'numarray', 'number', 'obj2sctype', 'object0', 'object_', 'ogrid', 'oldnumeric', 'ones', 'ones_like', 'os', 'outer', 'packbits', 'pad', 'partition', 'percentile', 'pi', 'piecewise', 'place', 'poly', 'poly1d', 'polyadd', 'polyder', 'polydiv', 'polyfit', 'polyint', 'polymul', 'polynomial', 'polysub', 'polyval', 'positive', 'power', 'printoptions', 'prod', 'product', 'promote_types', 'ptp', 'put', 'put_along_axis', 'putmask', 'quantile', 'r_', 'rad2deg', 'radians', 'random', 'ravel', 'ravel_multi_index', 'real', 'real_if_close', 'rec', 'recarray', 'recfromcsv', 'recfromtxt', 'reciprocal', 'record', 'remainder', 'repeat', 'require', 'reshape', 'resize', 'result_type', 'right_shift', 'rint', 'roll', 'rollaxis', 'roots', 'rot90', 'round', 'round_', 'row_stack', 's_', 'safe_eval', 'save', 'savetxt', 'savez', 'savez_compressed', 'sctype2char', 'sctypeDict', 'sctypes', 'searchsorted', 'select', 'set_numeric_ops', 'set_printoptions', 'set_string_function', 'setbufsize', 'setdiff1d', 'seterr', 'seterrcall', 'seterrobj', 'setxor1d', 'shape', 'shares_memory', 'short', 'show_config', 'sign', 'signbit', 'signedinteger', 'sin', 'sinc', 'single', 'singlecomplex', 'sinh', 'size', 'sometrue', 'sort', 'sort_complex', 'source', 'spacing', 'split', 'sqrt', 'square', 'squeeze', 'stack', 'std', 'str0', 'str_', 'string_', 'subtract', 'sum', 'swapaxes', 'sys', 'take', 'take_along_axis', 'tan', 'tanh', 'tensordot', 'test', 'testing', 'tile', 'timedelta64', 'trace', 'tracemalloc_domain', 'transpose', 'trapz', 'tri', 'tril', 'tril_indices', 'tril_indices_from', 'trim_zeros', 'triu', 'triu_indices', 'triu_indices_from', 'true_divide', 'trunc', 'typecodes', 'typename', 'ubyte', 'ufunc', 'uint', 'uint0', 'uint16', 'uint32', 'uint64', 'uint8', 'uintc', 'uintp', 'ulonglong', 'unicode_', 'union1d', 'unique', 'unpackbits', 'unravel_index', 'unsignedinteger', 'unwrap', 'use_hugepage', 'ushort', 'vander', 'var', 'vdot', 'vectorize', 'version', 'void', 'void0', 'vsplit', 'vstack', 'warnings', 'where', 'who', 'zeros', 'zeros_like']
dir(numpy.sort)
['__annotations__', '__call__', '__class__', '__closure__', '__code__', '__defaults__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__get__', '__getattribute__', '__globals__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__kwdefaults__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__qualname__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__wrapped__', '_implementation']
import inspect
inspect.getmembers(numpy.sort)
[('__annotations__', {}), ('__call__', <method-wrapper '__call__' of function object at 0x7f854804e670>), ('__class__', function), ('__closure__', None), ('__code__', <code object sort at 0x7f854804f030, file "<__array_function__ internals>", line 2>), ('__defaults__', None), ('__delattr__', <method-wrapper '__delattr__' of function object at 0x7f854804e670>), ('__dict__', {'__wrapped__': <function numpy.core.fromnumeric.sort(a, axis=-1, kind=None, order=None)>, '_implementation': <function numpy.core.fromnumeric.sort(a, axis=-1, kind=None, order=None)>}), ('__dir__', <function function.__dir__()>), ('__doc__', "\n Return a sorted copy of an array.\n\n Parameters\n ----------\n a : array_like\n Array to be sorted.\n axis : int or None, optional\n Axis along which to sort. If None, the array is flattened before\n sorting. The default is -1, which sorts along the last axis.\n kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional\n Sorting algorithm. The default is 'quicksort'. Note that both 'stable'\n and 'mergesort' use timsort or radix sort under the covers and, in general,\n the actual implementation will vary with data type. The 'mergesort' option\n is retained for backwards compatibility.\n\n .. versionchanged:: 1.15.0.\n The 'stable' option was added.\n\n order : str or list of str, optional\n When `a` is an array with fields defined, this argument specifies\n which fields to compare first, second, etc. A single field can\n be specified as a string, and not all fields need be specified,\n but unspecified fields will still be used, in the order in which\n they come up in the dtype, to break ties.\n\n Returns\n -------\n sorted_array : ndarray\n Array of the same type and shape as `a`.\n\n See Also\n --------\n ndarray.sort : Method to sort an array in-place.\n argsort : Indirect sort.\n lexsort : Indirect stable sort on multiple keys.\n searchsorted : Find elements in a sorted array.\n partition : Partial sort.\n\n Notes\n -----\n The various sorting algorithms are characterized by their average speed,\n worst case performance, work space size, and whether they are stable. A\n stable sort keeps items with the same key in the same relative\n order. The four algorithms implemented in NumPy have the following\n properties:\n\n =========== ======= ============= ============ ========\n kind speed worst case work space stable\n =========== ======= ============= ============ ========\n 'quicksort' 1 O(n^2) 0 no\n 'heapsort' 3 O(n*log(n)) 0 no\n 'mergesort' 2 O(n*log(n)) ~n/2 yes\n 'timsort' 2 O(n*log(n)) ~n/2 yes\n =========== ======= ============= ============ ========\n\n .. note:: The datatype determines which of 'mergesort' or 'timsort'\n is actually used, even if 'mergesort' is specified. User selection\n at a finer scale is not currently available.\n\n All the sort algorithms make temporary copies of the data when\n sorting along any but the last axis. Consequently, sorting along\n the last axis is faster and uses less space than sorting along\n any other axis.\n\n The sort order for complex numbers is lexicographic. If both the real\n and imaginary parts are non-nan then the order is determined by the\n real parts except when they are equal, in which case the order is\n determined by the imaginary parts.\n\n Previous to numpy 1.4.0 sorting real and complex arrays containing nan\n values led to undefined behaviour. In numpy versions >= 1.4.0 nan\n values are sorted to the end. The extended sort order is:\n\n * Real: [R, nan]\n * Complex: [R + Rj, R + nanj, nan + Rj, nan + nanj]\n\n where R is a non-nan real value. Complex values with the same nan\n placements are sorted according to the non-nan part if it exists.\n Non-nan values are sorted as before.\n\n .. versionadded:: 1.12.0\n\n quicksort has been changed to `introsort <https://en.wikipedia.org/wiki/Introsort>`_.\n When sorting does not make enough progress it switches to\n `heapsort <https://en.wikipedia.org/wiki/Heapsort>`_.\n This implementation makes quicksort O(n*log(n)) in the worst case.\n\n 'stable' automatically chooses the best stable sorting algorithm\n for the data type being sorted.\n It, along with 'mergesort' is currently mapped to\n `timsort <https://en.wikipedia.org/wiki/Timsort>`_\n or `radix sort <https://en.wikipedia.org/wiki/Radix_sort>`_\n depending on the data type.\n API forward compatibility currently limits the\n ability to select the implementation and it is hardwired for the different\n data types.\n\n .. versionadded:: 1.17.0\n\n Timsort is added for better performance on already or nearly\n sorted data. On random data timsort is almost identical to\n mergesort. It is now used for stable sort while quicksort is still the\n default sort if none is chosen. For timsort details, refer to\n `CPython listsort.txt <https://github.com/python/cpython/blob/3.7/Objects/listsort.txt>`_.\n 'mergesort' and 'stable' are mapped to radix sort for integer data types. Radix sort is an\n O(n) sort instead of O(n log n).\n\n .. versionchanged:: 1.18.0\n\n NaT now sorts to the end of arrays for consistency with NaN.\n\n Examples\n --------\n >>> a = np.array([[1,4],[3,1]])\n >>> np.sort(a) # sort along the last axis\n array([[1, 4],\n [1, 3]])\n >>> np.sort(a, axis=None) # sort the flattened array\n array([1, 1, 3, 4])\n >>> np.sort(a, axis=0) # sort along the first axis\n array([[1, 1],\n [3, 4]])\n\n Use the `order` keyword to specify a field to use when sorting a\n structured array:\n\n >>> dtype = [('name', 'S10'), ('height', float), ('age', int)]\n >>> values = [('Arthur', 1.8, 41), ('Lancelot', 1.9, 38),\n ... ('Galahad', 1.7, 38)]\n >>> a = np.array(values, dtype=dtype) # create a structured array\n >>> np.sort(a, order='height') # doctest: +SKIP\n array([('Galahad', 1.7, 38), ('Arthur', 1.8, 41),\n ('Lancelot', 1.8999999999999999, 38)],\n dtype=[('name', '|S10'), ('height', '<f8'), ('age', '<i4')])\n\n Sort by age, then height if ages are equal:\n\n >>> np.sort(a, order=['age', 'height']) # doctest: +SKIP\n array([('Galahad', 1.7, 38), ('Lancelot', 1.8999999999999999, 38),\n ('Arthur', 1.8, 41)],\n dtype=[('name', '|S10'), ('height', '<f8'), ('age', '<i4')])\n\n "), ('__eq__', <method-wrapper '__eq__' of function object at 0x7f854804e670>), ('__format__', <function function.__format__(format_spec, /)>), ('__ge__', <method-wrapper '__ge__' of function object at 0x7f854804e670>), ('__get__', <method-wrapper '__get__' of function object at 0x7f854804e670>), ('__getattribute__', <method-wrapper '__getattribute__' of function object at 0x7f854804e670>), ('__globals__', {'implementation': <function numpy.core.fromnumeric.sort(a, axis=-1, kind=None, order=None)>, 'dispatcher': <function numpy.core.fromnumeric._sort_dispatcher(a, axis=None, kind=None, order=None)>, 'functools': <module 'functools' from '/usr/lib/python3.8/functools.py'>, 'implement_array_function': <function numpy.core._multiarray_umath.implement_array_function>, '__builtins__': {'__name__': 'builtins', '__doc__': "Built-in functions, exceptions, and other objects.\n\nNoteworthy: None is the `nil' object; Ellipsis represents `...' in slices.", '__package__': '', '__loader__': _frozen_importlib.BuiltinImporter, '__spec__': ModuleSpec(name='builtins', loader=<class '_frozen_importlib.BuiltinImporter'>), '__build_class__': <function __build_class__>, '__import__': <function __import__>, 'abs': <function abs(x, /)>, 'all': <function all(iterable, /)>, 'any': <function any(iterable, /)>, 'ascii': <function ascii(obj, /)>, 'bin': <function bin(number, /)>, 'breakpoint': <function breakpoint>, 'callable': <function callable(obj, /)>, 'chr': <function chr(i, /)>, 'compile': <function compile(source, filename, mode, flags=0, dont_inherit=False, optimize=-1, *, _feature_version=-1)>, 'delattr': <function delattr(obj, name, /)>, 'dir': <function dir>, 'divmod': <function divmod(x, y, /)>, 'eval': <function eval(source, globals=None, locals=None, /)>, 'exec': <function exec(source, globals=None, locals=None, /)>, 'format': <function format(value, format_spec='', /)>, 'getattr': <function getattr>, 'globals': <function globals()>, 'hasattr': <function hasattr(obj, name, /)>, 'hash': <function hash(obj, /)>, 'hex': <function hex(number, /)>, 'id': <function id(obj, /)>, 'input': <bound method Kernel.raw_input of <ipykernel.ipkernel.IPythonKernel object at 0x7f854a1658b0>>, 'isinstance': <function isinstance(obj, class_or_tuple, /)>, 'issubclass': <function issubclass(cls, class_or_tuple, /)>, 'iter': <function iter>, 'len': <function len(obj, /)>, 'locals': <function locals()>, 'max': <function max>, 'min': <function min>, 'next': <function next>, 'oct': <function oct(number, /)>, 'ord': <function ord(c, /)>, 'pow': <function pow(base, exp, mod=None)>, 'print': <function print>, 'repr': <function repr(obj, /)>, 'round': <function round(number, ndigits=None)>, 'setattr': <function setattr(obj, name, value, /)>, 'sorted': <function sorted(iterable, /, *, key=None, reverse=False)>, 'sum': <function sum(iterable, /, start=0)>, 'vars': <function vars>, 'None': None, 'Ellipsis': Ellipsis, 'NotImplemented': NotImplemented, 'False': False, 'True': True, 'bool': bool, 'memoryview': memoryview, 'bytearray': bytearray, 'bytes': bytes, 'classmethod': classmethod, 'complex': complex, 'dict': dict, 'enumerate': enumerate, 'filter': filter, 'float': float, 'frozenset': frozenset, 'property': property, 'int': int, 'list': list, 'map': map, 'object': object, 'range': range, 'reversed': reversed, 'set': set, 'slice': slice, 'staticmethod': staticmethod, 'str': str, 'super': super, 'tuple': tuple, 'type': type, 'zip': zip, '__debug__': True, 'BaseException': BaseException, 'Exception': Exception, 'TypeError': TypeError, 'StopAsyncIteration': StopAsyncIteration, 'StopIteration': StopIteration, 'GeneratorExit': GeneratorExit, 'SystemExit': SystemExit, 'KeyboardInterrupt': KeyboardInterrupt, 'ImportError': ImportError, 'ModuleNotFoundError': ModuleNotFoundError, 'OSError': OSError, 'EnvironmentError': OSError, 'IOError': OSError, 'EOFError': EOFError, 'RuntimeError': RuntimeError, 'RecursionError': RecursionError, 'NotImplementedError': NotImplementedError, 'NameError': NameError, 'UnboundLocalError': UnboundLocalError, 'AttributeError': AttributeError, 'SyntaxError': SyntaxError, 'IndentationError': IndentationError, 'TabError': TabError, 'LookupError': LookupError, 'IndexError': IndexError, 'KeyError': KeyError, 'ValueError': ValueError, 'UnicodeError': UnicodeError, 'UnicodeEncodeError': UnicodeEncodeError, 'UnicodeDecodeError': UnicodeDecodeError, 'UnicodeTranslateError': UnicodeTranslateError, 'AssertionError': AssertionError, 'ArithmeticError': ArithmeticError, 'FloatingPointError': FloatingPointError, 'OverflowError': OverflowError, 'ZeroDivisionError': ZeroDivisionError, 'SystemError': SystemError, 'ReferenceError': ReferenceError, 'MemoryError': MemoryError, 'BufferError': BufferError, 'Warning': Warning, 'UserWarning': UserWarning, 'DeprecationWarning': DeprecationWarning, 'PendingDeprecationWarning': PendingDeprecationWarning, 'SyntaxWarning': SyntaxWarning, 'RuntimeWarning': RuntimeWarning, 'FutureWarning': FutureWarning, 'ImportWarning': ImportWarning, 'UnicodeWarning': UnicodeWarning, 'BytesWarning': BytesWarning, 'ResourceWarning': ResourceWarning, 'ConnectionError': ConnectionError, 'BlockingIOError': BlockingIOError, 'BrokenPipeError': BrokenPipeError, 'ChildProcessError': ChildProcessError, 'ConnectionAbortedError': ConnectionAbortedError, 'ConnectionRefusedError': ConnectionRefusedError, 'ConnectionResetError': ConnectionResetError, 'FileExistsError': FileExistsError, 'FileNotFoundError': FileNotFoundError, 'IsADirectoryError': IsADirectoryError, 'NotADirectoryError': NotADirectoryError, 'InterruptedError': InterruptedError, 'PermissionError': PermissionError, 'ProcessLookupError': ProcessLookupError, 'TimeoutError': TimeoutError, 'open': <function io.open(file, mode='r', buffering=-1, encoding=None, errors=None, newline=None, closefd=True, opener=None)>, 'copyright': Copyright (c) 2001-2021 Python Software Foundation. All Rights Reserved. Copyright (c) 2000 BeOpen.com. All Rights Reserved. Copyright (c) 1995-2001 Corporation for National Research Initiatives. All Rights Reserved. Copyright (c) 1991-1995 Stichting Mathematisch Centrum, Amsterdam. All Rights Reserved., 'credits': Thanks to CWI, CNRI, BeOpen.com, Zope Corporation and a cast of thousands for supporting Python development. See www.python.org for more information., 'license': Type license() to see the full license text, 'help': Type help() for interactive help, or help(object) for help about object., 'execfile': <function _pydev_imps._pydev_execfile.execfile(file, glob=None, loc=None)>, 'runfile': <function _pydev_bundle.pydev_umd.runfile(filename, args=None, wdir=None, namespace=None)>, '__IPYTHON__': True, 'display': <function IPython.core.display.display(*objs, include=None, exclude=None, metadata=None, transient=None, display_id=None, **kwargs)>, 'get_ipython': <bound method InteractiveShell.get_ipython of <ipykernel.zmqshell.ZMQInteractiveShell object at 0x7f854a165a60>>}, 'sort': <function numpy.sort(a, axis=-1, kind=None, order=None)>}), ('__gt__', <method-wrapper '__gt__' of function object at 0x7f854804e670>), ('__hash__', <method-wrapper '__hash__' of function object at 0x7f854804e670>), ('__init__', <method-wrapper '__init__' of function object at 0x7f854804e670>), ('__init_subclass__', <function function.__init_subclass__>), ('__kwdefaults__', None), ('__le__', <method-wrapper '__le__' of function object at 0x7f854804e670>), ('__lt__', <method-wrapper '__lt__' of function object at 0x7f854804e670>), ('__module__', 'numpy'), ('__name__', 'sort'), ('__ne__', <method-wrapper '__ne__' of function object at 0x7f854804e670>), ('__new__', <function function.__new__(*args, **kwargs)>), ('__qualname__', 'sort'), ('__reduce__', <function function.__reduce__()>), ('__reduce_ex__', <function function.__reduce_ex__(protocol, /)>), ('__repr__', <method-wrapper '__repr__' of function object at 0x7f854804e670>), ('__setattr__', <method-wrapper '__setattr__' of function object at 0x7f854804e670>), ('__sizeof__', <function function.__sizeof__()>), ('__str__', <method-wrapper '__str__' of function object at 0x7f854804e670>), ('__subclasshook__', <function function.__subclasshook__>), ('__wrapped__', <function numpy.core.fromnumeric.sort(a, axis=-1, kind=None, order=None)>), ('_implementation', <function numpy.core.fromnumeric.sort(a, axis=-1, kind=None, order=None)>)]
help(inspect.getmembers)
Help on function getmembers in module inspect: getmembers(object, predicate=None) Return all members of an object as (name, value) pairs sorted by name. Optionally, only return members that satisfy a given predicate.
inspect.getsourcefile(numpy.sort)
'<__array_function__ internals>'
print(inspect.getsource(numpy.sort))
@array_function_dispatch(_sort_dispatcher) def sort(a, axis=-1, kind=None, order=None): """ Return a sorted copy of an array. Parameters ---------- a : array_like Array to be sorted. axis : int or None, optional Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis. kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional Sorting algorithm. The default is 'quicksort'. Note that both 'stable' and 'mergesort' use timsort or radix sort under the covers and, in general, the actual implementation will vary with data type. The 'mergesort' option is retained for backwards compatibility. .. versionchanged:: 1.15.0. The 'stable' option was added. order : str or list of str, optional When `a` is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties. Returns ------- sorted_array : ndarray Array of the same type and shape as `a`. See Also -------- ndarray.sort : Method to sort an array in-place. argsort : Indirect sort. lexsort : Indirect stable sort on multiple keys. searchsorted : Find elements in a sorted array. partition : Partial sort. Notes ----- The various sorting algorithms are characterized by their average speed, worst case performance, work space size, and whether they are stable. A stable sort keeps items with the same key in the same relative order. The four algorithms implemented in NumPy have the following properties: =========== ======= ============= ============ ======== kind speed worst case work space stable =========== ======= ============= ============ ======== 'quicksort' 1 O(n^2) 0 no 'heapsort' 3 O(n*log(n)) 0 no 'mergesort' 2 O(n*log(n)) ~n/2 yes 'timsort' 2 O(n*log(n)) ~n/2 yes =========== ======= ============= ============ ======== .. note:: The datatype determines which of 'mergesort' or 'timsort' is actually used, even if 'mergesort' is specified. User selection at a finer scale is not currently available. All the sort algorithms make temporary copies of the data when sorting along any but the last axis. Consequently, sorting along the last axis is faster and uses less space than sorting along any other axis. The sort order for complex numbers is lexicographic. If both the real and imaginary parts are non-nan then the order is determined by the real parts except when they are equal, in which case the order is determined by the imaginary parts. Previous to numpy 1.4.0 sorting real and complex arrays containing nan values led to undefined behaviour. In numpy versions >= 1.4.0 nan values are sorted to the end. The extended sort order is: * Real: [R, nan] * Complex: [R + Rj, R + nanj, nan + Rj, nan + nanj] where R is a non-nan real value. Complex values with the same nan placements are sorted according to the non-nan part if it exists. Non-nan values are sorted as before. .. versionadded:: 1.12.0 quicksort has been changed to `introsort <https://en.wikipedia.org/wiki/Introsort>`_. When sorting does not make enough progress it switches to `heapsort <https://en.wikipedia.org/wiki/Heapsort>`_. This implementation makes quicksort O(n*log(n)) in the worst case. 'stable' automatically chooses the best stable sorting algorithm for the data type being sorted. It, along with 'mergesort' is currently mapped to `timsort <https://en.wikipedia.org/wiki/Timsort>`_ or `radix sort <https://en.wikipedia.org/wiki/Radix_sort>`_ depending on the data type. API forward compatibility currently limits the ability to select the implementation and it is hardwired for the different data types. .. versionadded:: 1.17.0 Timsort is added for better performance on already or nearly sorted data. On random data timsort is almost identical to mergesort. It is now used for stable sort while quicksort is still the default sort if none is chosen. For timsort details, refer to `CPython listsort.txt <https://github.com/python/cpython/blob/3.7/Objects/listsort.txt>`_. 'mergesort' and 'stable' are mapped to radix sort for integer data types. Radix sort is an O(n) sort instead of O(n log n). .. versionchanged:: 1.18.0 NaT now sorts to the end of arrays for consistency with NaN. Examples -------- >>> a = np.array([[1,4],[3,1]]) >>> np.sort(a) # sort along the last axis array([[1, 4], [1, 3]]) >>> np.sort(a, axis=None) # sort the flattened array array([1, 1, 3, 4]) >>> np.sort(a, axis=0) # sort along the first axis array([[1, 1], [3, 4]]) Use the `order` keyword to specify a field to use when sorting a structured array: >>> dtype = [('name', 'S10'), ('height', float), ('age', int)] >>> values = [('Arthur', 1.8, 41), ('Lancelot', 1.9, 38), ... ('Galahad', 1.7, 38)] >>> a = np.array(values, dtype=dtype) # create a structured array >>> np.sort(a, order='height') # doctest: +SKIP array([('Galahad', 1.7, 38), ('Arthur', 1.8, 41), ('Lancelot', 1.8999999999999999, 38)], dtype=[('name', '|S10'), ('height', '<f8'), ('age', '<i4')]) Sort by age, then height if ages are equal: >>> np.sort(a, order=['age', 'height']) # doctest: +SKIP array([('Galahad', 1.7, 38), ('Lancelot', 1.8999999999999999, 38), ('Arthur', 1.8, 41)], dtype=[('name', '|S10'), ('height', '<f8'), ('age', '<i4')]) """ if axis is None: # flatten returns (1, N) for np.matrix, so always use the last axis a = asanyarray(a).flatten() axis = -1 else: a = asanyarray(a).copy(order="K") a.sort(axis=axis, kind=kind, order=order) return a
2**3
8
1+1
2
#a,b ctrl-_
import math
math.cos(90)
-0.4480736161291701
import numpy as np
np.cos(90)
-0.4480736161291701
#if
if 1>0:
print('1>0')
else:
print('error')
1>0
x=[1,2]
bigger=x[0] if x[0]>x[1] else x[1]
print(bigger)
2
state='oklahoma'
if state.lower()=='oklahoma':
abr='ok'
elif state.lower()=='texas':
abr='tx'
elif state.lower()=='hawaii':
abr='hi'
print(abr)
ok
alist=[1,2,3]
#for
for l in alist:
print(l)
1 2 3
for i in range(10):
print(i)
0 1 2 3 4 5 6 7 8 9
odd_numbers2=[c*2+1 for c in range(10)]
print(odd_numbers2)
[1, 3, 5, 7, 9, 11, 13, 15, 17, 19]
odd_numbers=[c for c in range(10) if c%2==1]
print(odd_numbers)
[1, 3, 5, 7, 9]
states=['texas','oklahoma','hawaii']
for state in states:
print(state)
for i,state in enumerate(states):
print(str(i)+': '+state)
texas oklahoma hawaii 0: texas 1: oklahoma 2: hawaii
for i,state in zip(range(3),states):
print(str(i)+': '+state)
0: texas 1: oklahoma 2: hawaii
states_copy = states
states_copy.append('kansas')
print(states)
['texas', 'oklahoma', 'hawaii', 'kansas']
states_copy = states.copy()
states_copy.append('tenesse')
print(states_copy)
print(states)
['texas', 'oklahoma', 'hawaii', 'kansas', 'tenesse'] ['texas', 'oklahoma', 'hawaii', 'kansas']
''.join([c*3 for c in 'computer vision'])
'cccooommmpppuuuttteeerrr vvviiisssiiiooonnn'
print(states)
['texas', 'oklahoma', 'hawaii', 'kansas']
states.pop(1)
'oklahoma'
print(states)
['texas', 'hawaii', 'kansas']
states.insert(1,'oklahoma')
print(states)
['texas', 'oklahoma', 'hawaii', 'kansas']
states.remove('hawaii')
print(states)
['texas', 'oklahoma', 'kansas']
odd_numbers = [i for i in range(20)]
for i in odd_numbers:
if i%2==0:
odd_numbers.remove(i)
print(odd_numbers)
[1, 3, 5, 7, 9, 11, 13, 15, 17, 19]
states=dict()
states
{}
states={'ok':'oklahoma','tx':'texas','hi':'hawaii'}
for key in states:
print(key)
ok tx hi
states.keys()
dict_keys(['ok', 'tx', 'hi'])
states.values()
dict_values(['oklahoma', 'texas', 'hawaii'])
abrvs=['ok','tx','hi']
states=['oklahoma','texas','hawaii']
state_map=dict([(abrv,state) for abrv,state in zip(abrvs,states)])
print(state_map)
{'ok': 'oklahoma', 'tx': 'texas', 'hi': 'hawaii'}
state_map.pop('tx')
'texas'
state_map
{'ok': 'oklahoma', 'hi': 'hawaii'}
list(state_map.keys())[list(state_map.values()).index('hawaii')]
'hi'
from datetime import date, timedelta
date.today()
datetime.date(2022, 1, 28)
date(2022,1,16)+timedelta(weeks=1)
datetime.date(2022, 1, 23)
import numpy as np
np.array([1,2,3,4])
array([1, 2, 3, 4])
np.array(range(16)).reshape((4,4))
array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11], [12, 13, 14, 15]])
np.ones(4)
array([1., 1., 1., 1.])
np.linalg.eig(np.random.randn(4,4))
(array([-1.61226399+0.j , 0.13438399+0.7220566j, 0.13438399-0.7220566j, 1.15480839+0.j ]), array([[-0.26707588+0.j , 0.85268107+0.j , 0.85268107-0.j , -0.48108992+0.j ], [-0.05860576+0.j , -0.08843047-0.19978734j, -0.08843047+0.19978734j, -0.30548625+0.j ], [ 0.00756215+0.j , -0.10661846-0.41158421j, -0.10661846+0.41158421j, 0.79339786+0.j ], [-0.96186208+0.j , 0.20826294+0.03251999j, 0.20826294-0.03251999j, -0.21389361+0.j ]]))
np.linalg.svd(np.random.randn(4,5))
(array([[ 0.73969236, -0.02899523, 0.55166424, 0.38429292], [-0.19412164, 0.01641544, 0.72292436, -0.66289342], [ 0.46550684, 0.71814685, -0.2863295 , -0.43079449], [ 0.44550575, -0.69509345, -0.30176539, -0.47676763]]), array([2.42354756, 2.1042065 , 0.87177739, 0.69399659]), array([[-0.65048421, -0.60047173, 0.08502143, 0.42851417, -0.15953354], [-0.32268762, 0.72888761, 0.20900236, 0.31471129, -0.47103118], [ 0.48572049, -0.25415016, 0.7688339 , 0.11360871, -0.30898349], [ 0.32242936, -0.19189616, -0.56925114, 0.06212163, -0.7289096 ], [ 0.36449678, 0.08209819, -0.18421982, 0.83699843, 0.35482203]]))
all_one=np.ones((3,3))
np.zeros_like(all_one)
array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]])
x=np.ones((1,3))
x @ all_one @ x.T
array([[9.]])
with open('opencv basic.ipynb') as fpt:
print(fpt.read())
{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Linux terminal essential" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "cd .. \n", "cd # back to home dir \n", "cd ~/p2 # ~ means home dir as well \n", "\n", "ls # dir\n", "```\n", "\n", "\\# install vim: sudo is to notify running as administrater, \n", "\\# apt-get install to install package, \n", "\\# vim is a common editor (extension of vi) \n", "```\n", "sudo apt-get install vim \n", "sudo apt-cache search vim # search packages relating to vi\n", "```\n", "\n", "```\n", "gedit tmp.py # open to edit a file \n", "ctrl-z # break the current job \n", "bg # send job to background \n", "fg # send job back to foreground \n", "ctrl-c # kill foreground job \n", "ps aux | grep gedit # list all jobs and then search for \"gedit\" jobs \n", "kill -9 12345 # kill job with job number 12345 \n", "```\n", "\n", "\\# extract the audio channel of dummy.mp4 \n", "\\# audio format suppose to be aac though \n", "\\# change extension (.ac3/.flac) accordingly \n", "```\n", "ffmpeg -i dummy.mp4 -acodec copy -vn audio.aac \n", "```\n", "\n", "#extract audio channels from all mp4 files in current folder \n", "```\n", "ls -1 \\*.mp4|sed 's/\\(.*\\)\\.mp4/ffmpeg -i \"&\" -acodec copy -vn \"\\1.aac\"/'|sh\n", "```\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Setup virtualenv (tested on Ubuntu 18.04) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "sudo apt-get install python-virtualenv\n", "virtualenv ~/p2 # create a virtualenv with python2\n", "virtualenv --python=/usr/bin/python3 ~/p3 # create a virtualenv with python3\n", "source ~/p2/bin/activate\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Install opencv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "source ~/p2/bin/activate # make sure you have create virtualenv already, see above.\n", "pip install numpy # install numpy (matlab like library for scientific computing). \n", " # Note that we don't include sudo here as we are installing to the virtualenv \n", "pip install opencv-python\n", "pip install opencv-contrib-python\n", "pip install opencv-python==3.4.5.20 # install a particular version\n", "pip install -U opencv-python # upgrade to latest\n", "\n", "pip search opencv # search packages relating to opencv\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load image with opencv" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "ename": "ImportError", "evalue": "/opt/ros/kinetic/lib/python2.7/dist-packages/cv2.so: undefined symbol: PyCObject_Type", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-1-0a4d3346cd9f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mskimage\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mImportError\u001b[0m: /opt/ros/kinetic/lib/python2.7/dist-packages/cv2.so: undefined symbol: PyCObject_Type" ] } ], "source": [ "import cv2\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from skimage import io\n", "import os.path\n", "\n", "filename='Lena.png'\n", "if os.path.isfile(filename):\n", " im=cv2.imread('Lena.png') \n", "else: \n", " im=io.imread('http://optipng.sourceforge.net/pngtech/img/lena.png') \n", "# note that io.imread and cv2.imread handle images differently, io.imread compatible with plt.imshow directly" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Display with matplotlib" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.image.AxesImage at 0x7f472ff99750>" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "plt.imshow(im)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## resize image" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "ims=cv2.resize(im,(128,128))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## rearrange color component and display image" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.image.AxesImage at 0x7f472ff86f10>" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "im2=np.zeros_like(ims)\n", "im2[:,:,0]=ims[:,:,2]\n", "im2[:,:,1]=ims[:,:,1]\n", "im2[:,:,2]=ims[:,:,0]\n", "\n", "plt.imshow(im2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## set r as the first component, edit r, and display the original image" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.image.AxesImage at 0x7f472fefadd0>" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "r=im2[:,:,0] \n", "\n", "r[:,50:100]=0\n", "\n", "plt.imshow(im2) # note that the original image was modified as well. You may find this surprising \n", " # if you are used to the MATLAB world\n", " # this article may help \n", " # https://jeffknupp.com/blog/2012/11/13/is-python-callbyvalue-or-callbyreference-neither/" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Define a new filter f and convolve with r" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.image.AxesImage at 0x7f472fe74950>" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Af/H1mwEA9XORPrtoBuMxJFnV6korYKtJi3EndJyXzCYq/vrJZ+S9hwNTiCTU68sYiIqrN7x3bGMP5wiKmkWQAGYcB/LIVMGgqK7ZwOESujKfIQ3t2dp+7LuOgMYWD4T37Xsen72H9ve/ugCAnlsjGwULCz1QVvpINNWhRWWr0AxkFTOBc10Dd2mPTArGwtYyIAlQu0xvQYKZpLOHc+6j0oE2CiZ906GFjTyPhSdBBlhR22XcpM6kECakDYuhvnQzdw3lMHgegYkAJA9RdyxKH4FnAMmbAIS1ONzHIGGTfwOL4CLtTOfZrtmqImrS30Nm4eWZgWX0XBJErXYISDTG4sImmQ9xSI3stKroc3TXQp0GcGAsOjxpnOrQwD1Udxln/u7b/wwA8PDGdQCA5754YsIjIYBwODSeP57fnXUsSqVue+zC8cQ41kVEuwCmutVJRieAzEyMBXeim4TVc+AFcuW+J0PmGtnmcRP8BUq2Ocp7cYIZnm7j/MIMAKA9RatIHKR48yKBjg8wILnwqGuHTjBi9kaOJ6PmbujCAWQfeTLYFEuKHqPdSGk+lFJKKQXZG5pCbmB6IcJBMJmV1lttBWhKm7me5wcDAYAfgiy+YFHLghQTgEzSNoi3xkCa1Jutx8OqrbuXrOw2ci5JkQLQI3jjuIkB53qzMTA8IOgmq7MrFW6XpxZ2XMqxtCtLM68S7QSZ8Ct45eoN6BoL0x1EHERwoLWt989YdVpj1+RCvYOFGqlpr2yT7306ppUu8fTZN01Tdr03/cgF3Pf42wAA1VPUIWL62RgugMvjJuxkOml7xuItoqEz0xyPY1K9D1LAjqWWQ+ABjkFRM/MTnoTeGBpnlfrJcx3A7dphPY1GLwLSZk+vkTaw1KDEKwcrG1iqU8afxkWJ1ckngpeM5KszxrEWRZNKHeCexU47cBoQnZvWitd8LVJqCqWUUkpB9oamYClmIRx4iVE6PONJiKlxtpRLemoKbkSAgUe1QenXT2kl+IFI2HfbCgQbMRHHotpgoQlVChiEaCUSIuyBWype5mnRStI7yJavf7WFtE4PI2QkebaklbsVQ9LTjQJYZa8wUNVxnZFLRB/P+6ubLVQq1KApXvnPd2bQiOnBTkxR4tHVYVOTkS61aIVbGVJ48GK1gz6rXY0aJRPZTBv40TsfBgC8cD2lOX/2j09Ss7ru/fmp68y4DZ1PRnXKb1b17GoPSJxMm2+Qx2Ph9tYxPl3sgHMTT0RmZi7i048kBQDjZbTWtoY7jA8PaO6dJffk8jylb1usbONTD74DALD/osQ0GF3dRWNQoNHrq3DonkWITH5yVtGARUOodF6F3vktSKkplFJKKQXZE5qCsbQahAODeLvIo5eYg2AEWC7M4ifmlLh6mdH9lUiTbYg9NpokHvkU2oJbZ8wk87UIW1yE3SqOYtSlIuheQhd5NrGraw/RQyVNl3TVRXI6e1a1Dk1PlwOciMawK9cGzt7Mt+kGsnoGtUw1hVOb8wCAg80tnN8mhDzjfBSL9Q4udGnbm2eJVbPGWUEXqh1scwbbmJf52GRoRASovHX2NADg7h+jOkD/8o/fi8p60bVcSGDj98+440AwmWCS5qzPCneeX6fBEc/cSxSPgfR7Hu9AZIvsBB3a5ckYI5OBx8HYOy4UouEmPXXxIADg8cevx4EHBauQe1sXMyKUZnGbWnd9Od4GToM0PbmXwWiK9lc3nUaxW9kTkwKZDwZR3wsUkjgBnRy8j13GQ8XCSNCQ5xIcP9ev02Ay7jRhpaXeAJR5xQ+4gTtX//YyLgHMW/B4DAAnBxnPhuxNNKNZ2hgOQj1mImOzZ/ZouKy4+7oBMukH+fB7IewcnWRHdN2wThetVBMMB/RFCCCX5QGma6TXi2syMDnacRE1zfj4WpBgmpOJXBrRxJHmAWr80sTsaHBjf+h7H8Rn7ycQsn454OcFINmifQbpGFdEweHEMzP4+LSZ6yKgVaNyOLaiTsL8jr2+1WCwdoZ4U75k6HnjpQYd8O25Vz1Tx5+8AOciNZmRvD8In6GJf/a09fgxYid55qvGXVi9vkhS9xY9DWlnE7ReZDcCwNVbqZGH/w1es5TmQymllFKQPaEpmJxqLYQDi+EsAyWbTnUGiiu6EldyW1jd5VrjobZ+7UdXHs3df1y9z+o7uLy89Fm5FwdBB7mVTSSte2qsBz7JvVtnw0Ib/TYlbb4nr3zhwCibT2JB0mbuEoDoc1iYNWqIWaDVOuvTfYY5EMZcU4MDLtIs0JiHiKsjTUVD5NyQFzsEHF7XIDfayqiNk41lAMDpPhGb9le3cGFIWsN3Tb1Ax0cEQs61BvhH/+GXAQADBv0+8Il/jOp6sT9ynxgkLkwPaFQXnCSdyY2aUYbJWjbOYSAuZQbietJ/3jVES4kDvZ64H4PUaQGRmhsewOiF1gM0Jsa3qfZTzRHyu2peEJXeRbu68xwwLiLAYx4ZBQ59TViAVxlzWd2gukwd2DlEB3ZP+nbsa5NSUyillFIKsic0BeQ0m4cDqBtJZvRCgVK1/XiG7wdqYyuNNZ10E6nGsEOClCApaghAkZSiTfT4+lLF2t826d7yVhS5vpfRWDUEfqbRjAdSjuUlCAfeasK/UcfN57LiBUngohGvcAfO0s3zbgzDGkjM/sFhEmMfJwJ5ap3AsHqYIOalaKZSLNfdz2I8vHkMADBXId/x+9tPY8QP3WQG1zT/vpzMYTskotT1EbXjv/+Pfg+/+qsfkV6jHw9IHE8mEw1cdS4t+ttzBXfV7k69ZC/8m2fUR/UrrlbCcEYIcO6efnIYsef1GlITwhsPqsVU4FzEDH6rdpgbtM4UqcdB5q4jz5nUgSArqgppTepVOE3YJydJKsHBHP3GHSBp0d8bd8mgx65l15OCMeYIgE8B2A8aqh+31v6GMWYOwO8BOAbgDICPWGvXX+06AH0gcc9SmXcGABWJFZMhNcjHMibnVeuAHfnIcuMBMfQ7HmrqH28NNExXJoe04fvGi2314yL87EnKQ+fjgsx5JcaR6cqGAzJdxWMPGReUuy9gmhscsi1pO7vDFUZ1E0U+/majHDkP3O0OzX61+ghXmIMwzKiRm0lNgcbVAe27lFPMxIcOPIm31U8BALZy+lLPJAuYCWnySPiBVzLOcBz08FD/OACg3STT4l31s/jTn3wKAPDEJ2/nxpkJD4NOqF5OQumE0WzueYDcB6VjYSy/Zx4DjcsycdK2rBa4oCo4Tsx4mXcNnY68fTt8cH5BGQCoLweorxVdAOHIKgtxOC2mDpBJ7I3wDjTFv9GMSvI++4vBjiD8xl3yYNy4Hapyf6tyLeZDCuAfWmtvBfA2AH/fGHMrgJ8DcL+19gSA+/n/pZRSyt8Q2bWmYK29BOAS/71tjHkWwGEAHwbwbj7sPgAPAPgn3/Bihmc941wqCkIJvb9unUvIC4lV15EATxYTYaSFQrA8UyvHPnGrdu6BmjvlLgQY6BkDhgAX2uqi2dw+4RtUtmT5c3z+AsgkoKmXWk7a6Kd5k2NSKbSqvnLH29BGSq2MegrLf+dsfvW6NWxN0YrfiGmlacdDPPjKMQDArQcIVPypw38JALi5chlPjyjhSsgNnwl7aAfkphxw3biNzFU6OVZZxbj8dwe+CAD4/rdSluP5v/JyjEm3eMvVeBhwkBqnHYnaPpqs7aDZkb0o1irHuaRXjfIBJFkNlSGUvh8D+DxWpPRx1PU0HG5kZZ1OaJ/LVRuQ9GpJwyhrMfS8vhqPo65u9/6TRnG8wjrNV8bH1s0pgir9J5d4mGvgKbwuQKMx5hiAuwB8FcB+njAAYBlkXux0zk8bYx42xjyc9ruvRzNKKaWU10GuGWg0xrQAfBbAf2Ot3ZJoOACw1lpjdk73YK39OICPA0Bj3xFrA3LPjJcADzm+IOoajGaZpCNunQq81dW7tq74AhrR/7OKKQCSIhLhGCrIabwqRnx/xtxG05OuzsCrfStxEcihU25l07EyAQK5xsk0SduVJFcgU0viQTUK0ToKvSq2biOjkuz0MHQtLoaaWgBMcsqG9FDV1hC9hFSQqx1afi5tTOF/evPn6Dju3OcHB/VWb65SPoAzCbkhV7IpPNM/DACYiwi0XIy4dFq0hnPpHB9HqtFMMMRRJt385jv/FQDgF7/6UURd7vtasQ9sAIji4RLk2EKqNerAQOs8WI1UDLUfNf7FYxy6Qrjs1oysi8TMi9qaDRxuJOQvXwORd906Z/U8YRcKyQjwsDIlzzkWZYHJKJcdi58ZzLtkM+k0u5ibCfKBpDHkZ2rsPh/bNU0KxpgYNCH8jrX2X/Pmy8aYg9baS8aYgwCufEvXyumD0qjRfHK/stgYbbeeD1mYbSYLXfae2HU8QKbJOHssj93HJynV/RBamRwErQ4yuMQbXlYmVes900XVQcmoI9mEPH+4siJ7ThWVZDKaldrPPCySGzcAJNV7P1T/veQuTKf86jTcNo4VDsMc584Q3+CuW84AAI43r6r6v81g4k01Uvwe6x3FStouNKMdDnBPg7JEP9y7HgCwlhJAuZxOo8ax04vhFl+zgmcSuv/RiPDnP/zFX8EHH/vPAADV/4cmG3lPSdMvjsPtz4wOelHzs0au7FYVsaRSwAVH0TH1FTdry70kizZdly/hFf4Rs8svbCPH1VZ4ot3M3DW5OUJBDkaeJyJ1ZrJwEWTSEcAxabhrJE3n3ZDJQGju1kM+LSfmCeLd2w+7Nh8MqQSfAPCstfZXvV2fB/AT/PdPAPjcrltXSimlfNvlWjSFdwD4cQBPGmMe522/AOCfA/h9Y8xPATgL4COvcn5BrKFV1gWpjK2WXsGVQiHaeCwoyECnOs2Ky6ooMSdZ9Wp6wKTHVgSkHfR3OJY8JfMYjb4mMM6izGMPKBxTAX0QzS+Gq2GynKQkk3DYVq5agaou1XyiyKqtZzASSyG8f9Gumq7PbJ9ee38rxoff/ggA4GCFUq49uX0YQ37AIxwefXZE2sRSZQ0Zd+4rQwqqWoi3sc1L+FubLwEAElazMhjEoE7YyEn7qJlEzTR5T5tpgE/eeR8A4O9Xf4ye+XcIigqHRQYhANiWBwSKGzI17kAJrfcS9QjAJ+Or0s2BVTanqpIx3KuqraHW/Js5d7kck1csQq5BMv1ycWU2uVXAUFmauTMbXC5F6wKckuK9w5HTjkT6B3OgKmoMP1MaaGq+V7HWX5Nci/fhL/HqFIn37fa6pZRSyl+v7A1GI2gWzr3S8lrezYs0HM+sDAOMlwcHMBna7CVaVQ1BTO0Yk4la8rEirPCO8QGncWwBRQAw7qDwDO4gADvgQAJ4JlNFQla8GSIRO1JcjbmroqW4gZckRPPJyarTCWAj+s+Nd1BIdGoD7OMqvAsMDl5XX0OHwY3nuuR+fOsUYQYv9vejyi/ozgaFR8cmxUpKZCXREAIGXS4k82gzUiz7ZsKu4gwJo3QzXi67XzpB1uZ/vfSfAyDXnmOOCrHNuZat7x+WilBhUctE4MC+uOdWdElEUlsVt5+ZIJo5t7Cr8eAXv22f5osJy7E6uU76JfxcEhnGDZpGEwopAc7LOC5kp95hfrbZkZa28zUj0RBy9tdfi8ZQxj6UUkopBdkbmgKTl3ZKrCqzbNpwVFKNDgytouzijsqRI+W5TtKaOZeQdQVjI6cxuNqAfJQ3o++UK9snJgE0o0vEZOcE11t4PJ7wPvgybrPa0HNvcXM1KtBiwtMA41ZEv55i2C02TjCLtA7UjpAHQHIn3LvvNL62fgwAsFgjtWaptq6xD6tMgRb84EhtDe2AHlS8ECeqyzhcOwvAkZeeHBwBALSDgWoITjuIMOAlXI6/Ib6CGrtt7q6QxvK//tQnAAD/9Jc+OpnWzhMlKgUWkL7Jina7X0RYcQGPKFdflxDNQD0F3SUmHDEWE16OXFUqgXVWDWobtF/dx5KgNrdetSY35oKRc3sDnDxIPC1egmGAqP/9RdZi9pM2FcY50sQb/wBgLFJ2v1rujyDavfdhb0wKACQjj7w8AQTFFZPVrOdX5o6NXf5/FWsmg2oYaPRdgRN1BuDUNxjHUBT2mFwD1ot54JcYd92HP7OPBvVoak6vKxOGf2+NVhBzycvUI2XjBGTK6hYBlz3L+cxgZBQ994NbAAAgAElEQVREFD+7yaCsvnib6z8coc646egyjjQp5+LzGxQS/fjaEpZ4W86q6B+dvw0nZylf4xwHRO3j6iObaQMzHGp9ICJgcpBXcCYjf60ERMm+q1kL80GHj6MObQd9TLFt9vSQ+A3TwRBDnhEHbJPdXSWQc/2DXUz/CV1f3msKNwYUgA2hpeEEiJaw5zwyheQ3IgIwxl32948CfPSjfwwAeHfjeQDAI4OjAIi5eSSmcnv/8/m/BQA491snFMBUUHvgFjWtXieZlQMgqRR5GDAeW1bBamac7gtcCDSP87QbA/zBh+ySzDODMCq6J/O/ptiHUkop5f+Hsjc0BetIP6LWh3mRuRcOjEYGajhrANiK1JKj+c1fQWWFFhaZXz9BVMes6ggoCj5awIwxGX0QSNrkaw8cGIiNi/RHA0WACZiMrgQcKSqrWc0jqOQsITg1c4TbId+Tk6w0ct1f41RnWc2toI07iBh0vE2ay/aoipWQzIFWhaMge00scmWoEdtEJ2dXsJWQirLAYdVXRvRM01EfXbaxXhgSCHlDzXHTXhjQtuNV0jQORJu4kFDtiBsqdNxKNoUpNkFuZnbkZl5V8+Eyq2i3Vejhfu2e38cv/dFPUn+ISzr2zCmtBWGcaSVqtajSSdGUoF/HJFw/Sff8H//e/4XllCJCP7N5DwDgB6YfBQDcGmdoBdQvP7b/awCAXzYnXJFhXtA1tmFktWiun7dTwqSVRGd22Mdmx+YtKcIaDbzMM5lFQwhCSZpjkPH4F/PBprtf70tNoZRSSinI3tAUAAbO4FXcKdpEJvV53cr8cPHjsjoEVi/ir/wAgzo8s6eSCNN6tr7nhppI6eYVPB1PwQUA8Z1km4/OEwAXjjARdy+g33DG1bcIpGZmYgo0W8ArspuFijNo/MfQ94N6f56k1f22RYpwXBsSKHJ1q4ntAa3yHzhC9vJfDY6jx6CjpGCrBJkmVxGcQQhLs1FX3Ygij3WO4s4WuSdFQ8j4Wv6xX+3eAIAo08+NKJbiENOcN/KGag9zIbX/ckad9R3VAa68h8HbR8hwD/sG6TTX2Rx4pDXpvmQMaDTQvARCM85D4MKHaID87+8k4tQnL30X/t6hLwEA3t2g/A8DfoazqUXDUNu+n4lC/+h9Qyz+KfWpgIkBv4y0alCRiEylMU+i1sZCAaaUwcft63lfI1XavwymSnOk2kDSd1l+4jq1KUu8zN67lD0zKZicPuZQOlcy07SNd4z8wb+ZAThbMfqSFdnjge+A8Pt5EifEY69NcN+93HoaxNR0x988Tx/Eky9Oa/u1rNwYGbGyVWQ+AkDWcKm+x4usSpYhAKisS45Gi+oGHTCYp/0H37yMmRp9TKe3COgcpZzVd24TCSdSeXaL1PyDTVe+WMyHG5orCPjremyDvAjimWgEM1gZ0aR3Y+MyAOBYbRWnBgRcTjMn4SLnbLynfRohd6rET2QIFIiU5CyhySfCrmWSmgsHGjj1P/zlR6lbcuM8UOr4BwIptFuR+ALaFXXdZCBZkd/2sw/jA9OU7OUfPvojAIBfv/v3tT9eTKgad8OQqbWd1zET0gyeg9r/wVuexlf+/G56hrG4i2hoXb5HBh8L1ck9ro3GwfDkkR2jfgzggtfko0+TUCcFERNYZCkHfw0l1hu7ltJ8KKWUUgqyJzQFG9AsaVIgi4ouHpEgwSRnIICXZIOBltB6DEXhx8uN3DV2Cj1WBpznF/cZlQABjrKiiwlgcmCbwblwrKAL4Edh0m9W9bIKewVG/GKmAJBDQDQ4RiPnjqtsGIym+dzjtJJ3hhWs9yhEWcrNh6xGXt5q4+ZFWt0DfvgrvTaOT5GbbRpcSq4/izaXlbtpio6XAjD3L9+E79pH6djWGSGN40zNhhf7FK9wqEqm1LP9QwpEXmTAcTrs4QudOwAAN9dJezhSuap9dS4hTsTheJ3bmuNNvP8Xf55DrT/5n2imZD/BjLxUyeIs5leQWWzcQP326//Fx6itwwO4b5lKuP2Lt/wOAOJNbLB7VTSWQeBU9ANs2ghpcSutamyMRsJKkZ8NuLGWi+bi3JRiSpjMImem6eZJdidH9O6SYaQRrSmbBWHkeArCRbC5cd+GhMxLfMQupNQUSimllILsCU3BsEvS5NAZT9yIGt3mJUwtxD4IWaPqALhxgpLiA777J/GuL8d5uIFgGpro02ObyXVE2xi1gc6IDoilynvgIizFtpWsxBTfz885dIBnMAZgqvu0b2DYZpTVb7CYIzjcL5zQ7Vcx6lI7Dh8i8o9Ud9o/NcByl1yL109TirRbZ5fx/CbhAfNcfr4dDbE24oQrPcJHpit0n0Y8UtBxg49J8hALHORxmDWEFpOTQpOjw8CKVI/67TPvwA8uPUH34uO6eRU9dnUKAUpcg8vpNJIKgaYnYtJIfu2jv4X/9hN/FwAwmnHuRyW+dYruvjt/8in88MJDAID7rpB2cFvrEn72EKWFW87oXhtZYyIuQ1ywR+KriMeSfDy1chDV1B+MfpZmoziGNZK3wcPFWKqDXLMyVw5SP6YJJ0wxVl3jLrbBqEtSY29yM4EzZMnu1/s9MSnAUtKJPHZqUCHrEOhDVaZi5j4kfSWpGwgaqizqm0wKkTMl/Gw4mvuRP8pw4AJWxDzRbEheFWQxEYbzOZaXCVxreCaIppIUwElCuC2QtV2bAPaMjE02wluwsXum4TxzNRoZsp7MIvQTt0YKli5fpYF+dL9TzYWfIB97HGTYX6dZbIUzN18dNDFkcPJQiwC1aTYnamGKF7cJgLuuSer9peE0WmPx5TIB3Fi9jC9t3gIAeGmbwq/fvu+0Bl9JyPXAxmjwLCyei5pH5nioT3D8kZgmutDk6N9CbYou0Ecb9YzyOw6+hwK+fuH4HwEAPrH8TvzR+psBAB+epyj/dtDHmYTatJWTyRUiR8YfsExY82wyHIk2EXNHrzKXYvC1eUQaRk1t9RcCNTmtTA5uPMv77M+GSo2viLeHTeEgzh0z0bgxLxXFjYSIxznysSApmxQnidcipflQSimlFGRvaAqgQBI/PFo9TV45seGC6Es7nC/pubqhXiQYy8sXpEA2ljNfTBfAW9lj59rUAKqKF8AyVidi6ebLOH+ZgLTcAzXHzQAJuDKZWyl2Cr+WwBsteJID6Q20cuU9Vi37AQyDmvk0+6gvNRDuo6WqWqOH7yWcMKW9oebDgDWBG2dW1RUp2sHF1RncukQA4IUOaRSDOl2jn8bo8/Vm2aS41JvC5ohW/KUGmQ9fvnQcADDX6KtGsY81krO9OWwkZHrc1iJG41LlqgJ8qxxo1eOl97b6eWVUiko/F3bxD+5+AADwW6e+j9p4ZIT/8m3EMTjLJe3+75V7AQAzlT7+zhyZD8spaXRXk5aaKuI2zbw1UraJ+bCZV9Fmosky01eray4rdzCG6wWp9Zi0/D6rRt/zgMsjDhaAoEGDQcBEGThhlAF8rsY0eGaCYRDZ5sb7Wx9g11JqCqWUUkpB9oSmYA2De4lbmcfJRTaAuqE0NqDioTZSaNTLyKuJWztyEXddIZQIkAm4exfuq+Gv7hoFkBLATTNXcO7lRT6er9X30ryNZZDOI3eciLEOdJTnk9Dv3tEEGITuQBCgms2RhhBfplU1WxqohhCyK2uzS0vZYBRjrkmgRj2i8x69sITZNm0bMri1OLeF85ukIdw8z/EKjDf0kxibfdIKLlTomO/Z96xGQH5xmfCD/S0mO0UjHKwRLrHGTK/r6uvqwhTC0p9v3owqYwh91hDaHLjy79Zv1xJ1mxyyupq0cV2VsJL3fD/FJtxYv4LHt5cKffre2eeoX2yAUyNO7+YVRJDwb8k+HZtUSVOSgu6u+hlta8VQmyTLdXUznwCzJfQ6ggM+/QzSgwVmPDLoPDo+gBkz/0N2J9o8UM1A3qfNA8USVCxcOzztYbdSagqllFJKQfaEpmA4R4FfKl5knKoMePjBIHB/98Uem7y+X8NB8xfEngbA+6UaT9Rz3ocJOrSB1ukTDaCfxZpAVuoyEBmJ9mseAF4dooFL415dZx57AxNJU/oHePmJLWEl3r5sPoHp0LZkVlwTIQKuCTDo04or/Phjxy8i4hL0L63QKhgEVitDjdjlmWYhqjFd7+qAVndxtzbiBIenaeWXehFf2TiOGicpECLUKx3CV7I8wIUB2fDH6rQvsSHOj4iCfZW1h+VBG5sj0mjunLkAwHkf5ipdJU+d79G1bplaxqUR/S0uVQC4o03n3lqjX8Epnu0fwskauTVFO+nlFaVli/awndW1bWf6RKK6sUoErpmwizMpPfMy17woVI0SDVQ9TFY1SSUvZVZT9G2fkAhHi5wTpAQxb4ucDz2U3CFcLDeuplo4V7xwQWT1b9EQzN/02AcbUMXnqGddRiQvDkFEXXX8geS1XMuiWQ4xNb0QQSpquLu+3kcmA3UTOTdoZZvNjsjA8kwh+fnFFPEL0gq41EmqCDkGQ0JY02Go6r88gwyIrOpqGchEkVfctuF1gkLyg48CV1SXE4hULsUYzfIzy7MHFr0zBILlbbpGxCDW2bVZNKrMn+c2Hl1cR8gdPWQAcTiIcd0+cv2l3HGtCs1ql7dbWGyRKr+8RvfJrMF0lbMxdcnMODJF4OJSYwPPb5LaLpNCbg0e26SYikZE1z1Q28Y6B279+aUbAQA3zZHp8sL6ok5cP7JEmac/f+lNODFFJsiHDlD8wv54U0HBMyMy5QSYPFjZwLjMhV3NHykl8JrBEJ95mVyXMoFKfsrHekdxT/M0AOCXP/dDAIAFa9UFrC5ujXMxjmsTu0VEqkMHLXommxnHxKzIGOJJIsh1PMm+PAtcnQe5l/f9m4lsXK9dSvOhlFJKKcie0BRMzuXhrFtVte6DN8tKbsScAUYqmsobMzd7ZkwokXJtSoDyyEsy29oALmR64O4tmoqGvUrlJ8Cp8OyO2k6qTpXrS2o0o6ncxIxgwh8l/bByffoNB0D/EK/4UrOBgcc88tKscQHT0ULqKgRxHQeMDMzCkJ+BtSUhtVSB1QsEDs4epOjIzqiCjLP/TjeYHdnoY6VDavccb3tlldTlhdltbA2owfMzpPZcvDiHeIkYkjN1On6NzY7tpIbbZri6FEdcAkDEKpZEcs4t9NCMSWsQ1+j5Dkda7juHF7do5b9/9WYAwFvmXsFtDTIRLif0TOdHczg3oOvNxKTDCwGpFQ5UI5I6FBkCzR+5wRrGfWffhoTdgsf3k7b0yw98CADw3rufwfMhhXxPvUjP4bMWtUShB2S7WhO0bfuowfAwPafmlswN6m16Z2IihFGm+8KxXIvWGgSsxUjm5jw1CDhuxpGdsGspNYVSSimlIK9HgdkQwMMALlhrv98YcxzApwHMA3gEwI9ba0ff6BoiNjDO1hfShh/hqDflTVngMqBKpaC+R+4YS7LiE5U0+jGH1mDw60y6ClEuXt81lPcxBnBuZVbLvO80QUtBUI1zgNM8OHkxNm9JHWFqULxKvG1gAwYV5xiM6oeKo7iUZAHsGq16AWsMYm/2NutYOMwJVdfI9m+2B5hnN+WVLdqW5wYBg1RXu6TqVGtk/3YGVXS3uXR9i67fmu1hyHkaUl655FXVogQPr1wHAFioExaxnVRxfZvwhZc5IvKp9YN6rlCxRR5bPYzb5wgkfEv7DAACC8WduMnqWtWkmGJykWgI4uYMkSt9WghLsUn1b6Fbr6y3cWSR8JCnHztG7TlKWtXKsIWlOu2rdIRUZpE0mCjHT62gct2l+VM3ZMMq9pR7eT+EtGR90hKANA1VUxCcwXqFi306tLznvZLN+WcAPAuAsxTilwH8mrX208aYfwHgpwD85je9iuGAEclrOFaUI0hRSKgBABgG7m9OcpHXcoTsidCCpF5mW+UR+AU6xvL3EeOwODlpabYIiPoMICnQMzkR2ch62ZZpm0xEUc9dr3PUvTwxPSScWoKfACA9TAM4WKOL5FMp0KXXF3H+xnQmRcAFRjNhPjJAVW0NsbFFH3nAk8hwEOMqaJuAj0cWNjQZyxpPCt11+vCas31EFbr+iM22xZmOJnLp8sAVMLIWpti09BJe2SRzYLbRx8PLZErUKvQScmtwYoaAw8cvU4bn/Zxb8m8ffkoBw2d6hwAAF/vTONkiIFKK09SCRE0EmQwkHX077KsnIuZVoRkMFZj81a+/HwAw3e7j9AXyzBy6ma6/ukXnvXv+Bdz3CWJP1qpuApAQaA16q3ogt4KQ9JvNJohZ9c+GBOzG9QQx9+lwQO9WA6ICB1wbMXEDZ2aoh8F6E4oWncWu5ZrMB2PMEoAPAfht/r8B8F4An+FD7gPwg9dyj1JKKeXbK9eqKfw6gH8MQOqTzwPYsNZKnOJ5AIe/6VU4esykO6zM/F+/wKxL8Tx5qaATupWZf+OumzaFq+6X95oo826gRT2c6SFMQneYrPxT7R7WBqQoSdyCDT3QVMOk6TfqW3Su854LVAJOslSLK1MSsWRTKcwGawg1yQUXaJ5GKU1emRkiucwPyJmNG/N00zQNMDtNK/hCg9OKWYM5ruPw0gatkOdWZpGucLgzXz9eomOMschZi5ieYnNgUNVVSsJ7N5j1uNZt6DY55vSFBczOEUgp6eCu9Np4bp34Bj9y/DH4crq/gCG/SAldvqG1qhpCzJ1cDRJUQRqChD/X1HywmArItBCToWYSPDXkdHOzpJVcujyD6BJ1+toLlLKufS+BqLfXzqF5iQE+HlejttHyghzOoe8s6rmaIaNZHjvVzMU3eNq9aAgat+BZj46Z6DEVffMZgM0cx0E0BE3LtgvZtaZgjPl+AFestY/s8vyfNsY8bIx5OO13d9uMUkop5XWWay1F/wPGmA8CqIEwhd8AMGOMiVhbWAJwYaeTrbUfB/BxAKjvP2KtobwBIkpUSou/ADRppw2tm9ZkhqzmCHmWHK/MFKQeLDGWa2GifYplTJJBZKWIJCOzgabNmqgv4N1DEr1SMlpePQQLqbiYjbTlngUATBIoqJmxBhN1A6Rc0kyIMPnZJixnOY6naUXsrnGugM0IW+wVXD09x9c1mrpMSvLN3ryGrEkdt7nJiVS2aCWL4gwN3tcf0rZ9Ux1cWictaYr3zdVJs3jxmcMAR3AeP0QrbhDkuG2BgMPHlilW4T1HXsTdrbMAgBf6tEJLlKTEPQBOK4hNhmmmDsq2ELmmmZOEsNt5zTuXsQcBrQB89hUiKq09R4DnzItGazVs3UGI4a/c/HkAwM8+8RFMC37AWk/cccl2Q03K41zokog1WZDMKyGCSpFwBkDrN+Ss+goIGUY5pKCwnzRFtS+Jg4lyB0gK3nANQOOuNQVr7c9ba5estccA/CiAf2+t/Y8BfAnAD/NhPwHgc7tuXSmllPJtlzeCvPRPAHzaGPPPADwG4BPf9AxD9vmOyVlZbOD2aYyAgVvyxSXZjdTtOB634LskzVhmp8LxxkU47pToVYve8srfHVRc/ETbpYVjFq2mcpN7kx1atBUz45LPZo1ibQeTAVm9uM2GUMDFMt6QNXIYXlHEhSUusKCZYLglNQo4yu9qoM9S4W1H37qmKy64HKa4C1Mb4skXWN3gd3D+bEtXx45EU/Jz1wOg/gTTdH+U2j9TH+Br544CAD584kntU9EQthj0ma9IWvmRRmGKFyI2mWoDI5elV/dLFGND8yVY3fZvNu4CAHzuobsx/wgdPyWertCge4ie68NvogxNEucw9Xtt1RpdWj3rKodJPZGaw5Qk9b5QzdOhS88uXpwoyr0cCa7iE0CeB8FihJxkLVOj4VGajefWFJeY5/J8rfK6TArW2gcAPMB/vwzgO1/rNaT4qwxS/bAFbKtbVaFzDTQxCryZgej71rkix8JH89CBg5q52boJQI7WfXDcBeRuVgjG4jKqcYr+kAZzMMehy2drar6YtSKzbafni7oB0hY/yxgrzQYegClFU0PrJiyNi8iU5WhW6MLhIfp4/FBay8Fb5q5tdWt1VmmGe+zsEbz1+BkAwFceO0lt22LAsWNw+J1cZOYv6CPu3zDCzJfpo42GdN21Wx0LtPZ3KKDo1DKxEm9fuoifveN+AMCZAYGbwzxCGBTV3U4qHeP+bkUMEgaJZlsW86GXV3AoJsqoMBWlTsOvn/0Alv+EJrPKJj3vVM0oKidqfvdIjhveTKncDlaI0/G/few/oHtWXB0HGRN5ZBD3qN2jFrMRNfTfYHSQBnMgfW8NYo4/iZiLMBrGE+HR8k5MAIQhu5j9bM7jZc+9c3ThvIZJoWQ0llJKKQXZG7EPHPMQ+3xxKc/Nq3HUMZq0VFfQyE4UGoUFQilJPvZ0fuh0Lkk1R1bdoIVs0WNmjJ8eTlNv8bY79l3Ewwn5GAc9p2aIe2qwj0uHs6YTbxo1W8T9mDaslk53xQGExOTm7oTNAZMZ3Z7McIMyA9Ohh86nmGS0zmpTNUNrnrSGzgZpNeZr02DLAFOs8m8fD/F4jbzItQNMQrqOVreNszPonSebYopDhGsL27AR2xmsGU2/RL9H/tOX8MRXKerx+95NyVDO92bw1U1KxCoMwV5ewZBfVs4vd8gvY9500QF1pLAS19ImFmJJjOLARwmB/vOtmwAAf/Upqt5kQxpbftfaCNiiSnaITpBr9M59lzHPLto//KfvBQA0K84NKRqCI7bBMRrlFXCszmDOuQ4lqWoQZxr2POLfIMwRvIr30BirCVgkStIYC5ONZyDCJJX2Gpb7UlMopZRSCrInNAULmsFtYBz9eIcU7xM50HPAVtzf4zJ+LZO5FGrByNl+ofc3/TqykrZR8Jua0eKdYj+e2ZpHMhJqKtupVav1B0wirinOZ9AK0TjHsQxT7nh5FjOUGAhXL0C0CNGMwn6AhPMpuBqKuWIamSSdkbLlGzHSMww0zonm4p5vRHlR0Dq6iW3GF6a/TlrPxk1MjKnlqLRH3Cbat9jsYmuLTu4sUTsOfd8rAIAnv3IjTn4HuRqvDAmEXO030YoJGxCsIM1DjHgoDjmzbp0Tt2xmdcUSJL5A3JGAS5Dycn8RH/v8B+nZbyENp+pFoIqrsXeAwcJ9Q31Xiy263qH6Fh7+DQIireQ9kBR9Broaq6aYAUOm7QkZTsZN72iqhCJJohJGuY5diS8JAqtuxHxMAzBBrthDKrUic6Pag8Q+mMB6OASP5d0XiNobkwIMfbhZ5CH0kqCCeyCv2olCGgK6AfBSMXssSDYHuFgwezcYqGMt34bAqC4TBR+fu5BtZSVKma8cyNnckEG69UcHUXkXAVOS8SibTzAENUDMhuopcUO4sOuk5a4bsjmgJlEgz+GBrPxM6XSGkGMesrZkccmVFRet0YH1y6zO3tNF/QUC5xrLAtRazSm4/+2UWfnsy/uw+CCHZ3M0S7RAtkXSj9H8UlP7DQBeuriI+GZWhW8jNfzFp4h/8KMf+DIuDSm0WYrSHGhuYYrrSFwacDFeYzHgyUASr3D3YG3UVK6CMBRzG2gg1Mf+gCYCkwCDIzR4DnBY99bb6P+dy02dHLV6cyNRf/9Jjrt49H+5a+KLkGxcMC6vp8Q3hIlVfoIsEFLYxdRTnQz8/IkCJkqsSRBYZSFKDMSI4yLGCq/TeaNIP/y4xiBkFuhEoYFW4ynMXoOU5kMppZRSkD2jKWQVYiCqS3JMKwiGxgFxss9LxybTWzAK1H03Xm3K/1tNhZDSwNE+tyqoy1BMD4+pqNs8LsPbl84AAJ7fIA7/WrcB4eIFPKP3Nrk02ukIab3IaERgNamKgKGjGVHzA6c11NwKoCnrxIWZhqi/QNrIcI5XLvaV1x5uqsk0nKfjW+dybNxE27rPkItx9jmD4QyvhO+jEOd9HM24/ZUD6L6HVuH5f01ax0Y3xnCRGmwukInwrrc+DYASmUiaNUmsMh0PsDokbcPnP1T4oVusKQjwGAeZVo9aGZGu/qmv34vZR2g1rfK7SN+zCWySvdBltqWsyqjlgIwJ1hgWpjs42iag8/lfu43abz0gmgcPZ4IrVBQTN2RWMa5QMGtw3SWv6KuEMdfponkWTGRZLtRx0DgR6K+aDV6ORuGgCDchijNNuKJu6vGMz69BSk2hlFJKKcje0BQspyjLHFCjmXAlBiJxWIG6XzKjzDphcOX1DCmvCpWt4sobJP65MpN6M7UPzojS4MVcAFyfQjJCC2iZWPzpU1Tz4B23kD+un8TobXMQA2sKU89Td3eO5upCFU0h3g6UDemIVUZ/hKRlhbk5MooNJA1eOVpWy9Pnh7j+47OchGTNov+3yeZvfZZW3LTugN3ZJ+SZgK0beJV8mGIC1g9R+yuLVqMwVz7MKGUv0na+7y3EUGwyMJjmgVaN2kgEJXCyndDKPl3po8eZkiN+CTMVdp9mVZzqEcnpLx+hPp59OtAVcfMWalvwSps0AgDbl6nfjx4nrKC7XVO3s0Rohsbi/K+coHuy6pnWgkIRYuoPwV/c+NBaINZptkmTWYizQncNJkBFY+xERGmeBQ4cFPail4lZjjMeuUu2RbHbJliSaAjXQl7aG5MCqP9s6PzUUbcICMIY5wuOPGqzpLQW9TAz3kdLv4GqgJ75YByYpwxJBRXhUar5V2cJbxtvCkfAzKN0sxP3UHKOxy4dxswx/iA2moVnrawFGByUtOz8Ybdz52GYZYSfE6VkFeMBZXyRUaimgTQt6hgMDvJH9WX64CRz1NYNQJibwvE2BGKeOMORU4mb54sDKuCkHye+7xSefIUSnaQcdGYqOe4+Tt4GCWcWj8BG0sAmf/gj7vj5aldNCpF2PNQydFKsVkwFAFhkyvPxmynf48ppV/Slsi4JdSwWj5A5sL5J/S3ZpKr1BCcXaYJ44vHjtO1BgOkPjk8QeVyEscJAYeIYpPLek7pBWheeCR8o43EQIFrsF67hzzg6OQS5Myl4XEnmJTIZeAKIHEDpGJDeZCKvVgHH3RsBpflQSimlFGTPaAoAAOut7mMBSe43NvAAACAASURBVNa48F7V+BOnoolajXwHJqNk2B1adY3JqpxFxgGXcvnMujoP4lXygE8Bl7QsWGrUZfnpz74bAHD8PWdwaWsKvnQPc0bh7QCVtVCfCyCXq7hYgyt8Aw6MimeG+pwJMyarq6EWoJVnGS2kqF2KC23UArkxkFyiFTTaz+6wBGgs0/7+HG3rH7DIuS8lFkOWjn4aY25WErTQtpvmVtSdeLFPz3uAi8luJjV0EmqIuBqvDpuIWeWTTNL1MEHCfH7RNuR3vtJRoPFwkzSv09cdwtRLdG5tlTpwNGXQf4DiK2pvL9Z5yLIAp/+A6Iv7VnLtd9EQNQ8noGNAApt0s3ExLxpWn7kwdy1+7MWoyKodx8I1CHQFd2aEMw3GczVSUhsGY4UVGWZqXii4CE9DkEzg8e6JCqWmUEoppRRkz2gKJndgIzDJJTe5y4act2Q6N4AwGmVi9Fw8yjwTuCE2qokUCsdq6Cwfn2LHClUAH8vuJx+zEFtUyHZZHqhWIsBQvO0YigIwarn5zCguIolb400GENOaPlfoJZ2JV8X+pd/NO1Nd6YShKEuIsRb1Q2SbdzOy1xceMcrjl74KX3HPnNbp/ht30k1PLS/iu28gIPVyn66xMaqjwifPctzAqS2Ofswi1LiYrVRcSrNQ/5ZUcJ20gjkGFiX8WUKnAZdteYoBzHBxgIABVM7NimBoMOAKchKVONvk0vFXp1EbFjECk0Nri2htj8y6MHd+/6GPLSjLld9dxUvKysltpHyhjXPVECTJLRGVHJYAsOtSsjOzVtBo0nMOh5FqABX2jQ4HsWoKPunWenUk6PqlS7KUUkp5nWTPaAp5BIpwHIwRlIx/zNjsV8kdv1yW+8Q4t50U3fRcmVpPQrgefoSaaBRVM6EhFBK2jDWDEp7Q37LiLtY7WKzTavf1L9/qnhFUXFZcrRoQOXLUZ4l+lDaEvQCzzxTv2T0MVDaKGEvr+YreQyIzm+doZ/8AkD5LNv+Jt5O3YPOrRxQ7EQpv1LfK4199O61+9TOkGt3+t05hX5XwAikiGweZuh0lvmF9QA+SZgEl6gO01sPXrx5CKK467rQbWisYl8DvZF62hQDVbvWR1TldPddgiLsWQ8kr8QTRp9fv5NONhRcuQcdEfqo/JnrNOs+VjhmP+i7aYObhTYNFKSVWJA9FzUQp71HsyEtm7MVba5CnxcpQwyFHjGahVwOCyUsVV2C2yq7uYT/WdGxpVsQldiN7ZlIIUurktClqOKtIXs0EUavh57vXBBZ8odjqi1SQUPZ5k44W+kwmgck8dreYEIPJwBjrPmBJ8HKscRUPLJ/QewAeeGqM8gnkvDwuhkgDDljNGjkCHghrt9PNFx7PkbA7LFZGJrB1I/3duEjHd9l7lx3uo/YMfaxXewQ4dm8IkLIptu8h7u8AuPwuDkdepY45+T2nAADPre5DMyqCfgAQ8Ee7yYlmpCDsdl7BUouOe2yVwrG3ejU0a3SNiiQQ8RRWARWHTBudDvuYi2hyHVVo27PNAzhfIw6FBHVFPYs6zy2jaeqXQzMUj3Kl00LAL0YWhXBkNVuSvMe4OzkWRIxFITMXAKQNg7whFEj+yJuu2EuehIVrBEHucRLcpcTFKJmypSycMVbHt9Z/qGT6wUuMhAk8F7EGRO1+UijNh1JKKaUge0ZTAIg9GKST2wAG5zh5ihSQRWhhx9Q2JMa5lSQSsempyHIqA09Z1QE9mnsvgW7TzM3MQ0mbLiuzrFKBmYyReKU/qxx8cQ9K+bio67Iopw23QkuodXWNH4lXtawaIOWYB0moYk3AWaGhBJpKx2LqFP09pNSCkCrsw9xoAdvsEQIC2xcsqlvFIJPLbzWIV+hhDt1DZCGp7hSHmar1bY50rIcJTnUWCteosgYwNTXAV04TWUhWxnpjhOkanRtxZ20nNRys0aouVZ6muU7DXNTR5CodXu1vmFrFC0eJRFVdd6txlc2pPpdpEyJcuzZEr1YkqKHiQGdlKgbuPeq7VcDbxT+IxjBYsF5uUN7YdImAIlbvBVTM0hCQHKFS8cmLZlQNwVvtI3Et8nFZGjqA0bewJCGPlKzPd7/el5pCKaWUUpC9oSlY/me8ikmSAER445lx4EDkkWpkoRMbKrYwUoNRCB28ImSZmdiWR577US6bOQ0lVL47/SZNoLLF16sUfwHXxIf+7e34wA88BAD4UkbpyiqbQmkmWi61w2ELCowK3ZW1mfqKRcpx/ZJzIY+NIz5J1auRwy9cg7j93QjV/Yy2rZE7cfjhDdQ/SX+v3uFUnegkgYmrXJL+zQeodMcgi9DPyI597AphBD987HFMs9Yg9GUpJ//CywcRNblaU51+4zDDYo0wAnFDzsQ9zEXFgkCSwXmQx5pHYalCYGViQ0RThD0EHFMRJlACWeMK/b70IpWOP3niIrYaRfqyHWESMI78MVDcGaROQxDcKJnKnQtcCHJaqcm4Wg1GiEfWRUVaiYdwuJgkZJVr5JnR45XmbI1iCnJ9mxvVFJKeJNz4mw40MngXeC9Kc+kFTu1TFZ0DQWwa6Msw8jK67pGkxJufYSgt0u7pnjKHiCUSwOlQXvIWgAaNTAISLhukrt2aQj4DXtjaVzjOVSS2OhnkDWp37WKM1jlbaOP6d9DHcODfubT1GaunWTXU/hAvRNo0iBmNF1Va2lW7EiHbJO/A7CnaePv3nsPX990BABjN5np9AbD2z5NKf7hONsjaqIkVTuN+gAvANsKhhovLZHD1Kh1Tn+2jysh7zCh6JcywxpPHDMc7xCbDGufLl4rR8bgdCUrVDgAL0Tb2z9HMvDnHodlDC2uKXpupZ6k91VtSUvUBTBFm6vJxwgOMRx6wLYl0UscIlWC9tMYfYysFBOCbpper/IAciKpjrgxjYfkGmmxlFE6EUyfMEEVuNOJbvRqVDElXsgdZd085Tu6/+6pxpflQSimlFGVvaApsPuSxp74N3S6gyCewXmksLbIpgGNstdxawC4eTaVmXWo0vV6wg0syAoy4M7W0PP1GPc/EYfBR2Ji+pE1g9Xcpw3PM6r0G/h3pY6ZNqvPaeQLx6lcsVu/hBCAP8/PxarJ2m0GTi+8dfID2rZ80SKZpf4tKFSCrGXW1VtfZ984JVYIh0LqH1O/KQ8Qx+Npn7kTnLbySb7DqOtfHqM/FV7j/JOFJNUgVvDvcIC3ii1duxVqHVmsBzWrNkf6/WWUXI2sRzXiECttkWxxBORP1NNbh7IBcjXMxmRNhZAsuSxEpXf+VBiWHSZoGlS33ngHiZohE3bEl1zpQO/G0x5gtLDEzhJMAOMB4i8O10Q8nllWJXzDGAYd+LINoCGIiZGmgq7yWfkv98c1mI2vHo65nq0oSl0qu+Rod8QW7llJTKKWUUgpyTZqCMWYGwG8DuB00BX8UwPMAfg/AMQBnAHzEWrv+Da8DWm2jvl+Fh389DUGrQQnQaDFZHiszCtipmiEmXeY0EU3catw2wQrCkRcBKdOm8KZSTLTRj+4UGc5lsAHn+D9KdrJoM+3GEJ2v04pY74trEsCUqBu0JO3fR6tx8IcLSOt07uqb+PhmhunnODai5tyaWydpBVr8Gh2/dSet1K1nKwh/lwDPAZN7uncM0HqKVuvZ95P7caNfU1BrkDgNASBi0XyVHlSwheeeOoJogRO61OleMWsCYWA1ziFgQlM3qahGsZo19fozcZFyKDEQiQ21xLy/TzQJSUxjLhj3btl1GHLf1sJEcRpNhlJ3WIxPMhQNQdy8xvMICilKEvuYJICt8rOOFXSN4kxrgASa+CTUYrKiMdQaI1eKXuMiJglIAjgGcTaZ0i0zCPj+OeMNpjGJyXyrcq3mw28A+IK19oeNMRUADQC/AOB+a+0/N8b8HICfA9WX/MZi6YVp8Zex4h0mh0tlzrq9qWUw1UzPBwDb9x7Joy3LQRr2yuPMD2rR03JvUjLF432E2nrApORElGxIB//SwGR04Cp/5Pd+z1MAgK984Q4w8I54m87buC3H4v103GCWr1Glj62buXYoUBYFiLvCzuR2Z0D9Aicd0UAxOrFzfYr2OZ5YbqN9zadqeNMPEX/6oXNk6txy4DKevkCo/ew0fXhSeAUA/t9TxB1ufIFsoeaMQc4h2UlMv51FeietpS20q1LqjbZtj6pY69MXOlsj+2szqSm3YWNEtpaYFttxDW12RYmHYi1t4gtnKAtT/YqEgVstW+cSdjJPIRpiNMcU6TOSDt9ouTh5/3HX6iKk71s8DjF5jaijnQmiC5RmUmKTa+AyKqlqD2hldbaOkWehhjvrZCBBTV6exUI2psiBlACKGZ04H6QPuL9W2bX5YIyZBvBOcAFZa+3IWrsB4MMA7uPD7gPwg7tuXSmllPJtl2vRFI4DWAHwSWPMmwA8AuBnAOy31l7iY5YB7P9mF7IgM8FkOwM84P0CIIKTithBCFNjV6SmGnMzKrvUEbkoXGeOWHd4oJwId5yGzvKUnjPI5AdGiSsrrbu/O0fpj/pK4FK+3UQr3KOfJvdfxbrVPefMyZV9PQxnaCnqfiez+Ti0eKtiMGCWnrgm445Vt1r9qqO4dZd49ZMEIhx+3bwQYDhdpMJNv29ZGYdvvu4cAEqGIur9d+57Bb785gPv18zRw3exSWSNrkrT7AKcepmBsgenceEmZkPeQaZQFOR6/ZUuaRZhkGsRmJQ7uMn+29VhE+d7dI2nXyENpvp8XVmfPp9A+ls0wxrHQjx6eQlmhlPcRaSBBCPnYhRXsQ8WS8i0xJfAAIN9gkwyuB1bxFWpKB3pcUAxbkFN3NAlXrG5cAyc6zIbi5UwxoG3woqMIlcgpssUXGuNmiha96FSNGdei1wL0BgBuBvAb1pr7wLQBZkKKtZaoSVNiDHmp40xDxtjHs763Z0OKaWUUv4a5Fo0hfMAzltrv8r//wxoUrhsjDlorb1kjDkI4MpOJ1trPw7g4wBQP3jEpnWascVNJGw+V/LNOExBQqh3iH0IminsgG2tccaacXERfrzDGMa1Ywk6DWPOHKg42Meg1OIIwQYt240lUkt656ad65Jn9v5+JhatGVQZet26l7SC6hNtdI5yuPPDZFc/2KHirItVx9OfukjHJE2D1e+g6x75Ajc7NFj4Ov3dPcD29Bl2UW5lOP9BBuU4huTKRgvTUzQh39ymkvFfvHAzrt+/CgA4VCXS0u98/Hvp2eouvDvrc+KTl4Gr93Alpuu4bVyWPeoaXa1Hj9BqP7ytq+446ZeKsodcPIQkqHlpbQH9RwmUrYqdHwNDrmkbdwUQtBjMMr4gBDJOorJ+pe0Gg1TQGjhNy48y1uzNY4zG0bQBRFMVjMA4DWGnpCaaWZnbYUKLjMdmUHEabtKrjJ3HoGFmtPis8dyaDpCkfdXqSF2hGRPPMAZGvhbZtaZgrV0GcM4YcxNveh+AZwB8HsBP8LafAPC5XbeulFJK+bbLtXof/isAv8Oeh5cB/CRoovl9Y8xPATgL4CPf7CImp1j2nWTHXBEKMnvxEJKQdRgWIs8Ap3WYHMjUJcm2/LbDCVQbGNmJWrYZu7k6Ryyq1xPFNjvPcHQ/VLpy/yxtqzSgadz3fY4TuPK1rr4pRzbDCUzqUnS2hqxOjauuMR7AtSL7+4xro5d8JmjRub15WrUrXasr3NQ5TgXGq/bVW0M0TtP1pr6btILBKMY7Dp4G4JD966bWcbJFyt0f/Pp7qT2pi8EYj8sIUuDIv+W+55Wxt8geldtzVFdYa+PVO12pIeMiuGnk1iTxPkjNiFe6pApsvTCLNmsbjSuZ9oFEkKrND6I6+/0sbkUkBiGnSxvNVPRZRPsSTTEcOu+UvHfBFqwxk0k2QlfYVWNqpH5kDoclsH1v+yECdhUW3IpyHHsVhJAHY2ElOlIaloQOl+Bb+ynawqorWb9buaZJwVr7OIB7dtj1vt1cT8qaAQ78KXAMdgrykKATKYyRG81/OF48xuReth3+ePLIAVSibkoFbLovvxQOgrnh7nN46UnKXFJdZx7CDLS4i52nhjeeq6KxzCW/eJxkP8To2AuzOHCY7IeVZygDMY4M8P4bXwAAPPllAiQl6Uq8bZGzm1LU2+qmxdz91Kj5HydA8NTD1+HAg8VBKoV6+4cz3PumFwEAD509CgC4fv8qbmeq5JkBhT/vq3Vw/6++g87NbeEaNnBcAPkot5YC5O8kM6P5GZr8asym3Pegweqb6W9hf8Ia5Ow2Dlsuo9JxzpCyyn6/U39I2ZfnrlgFBIcz1B9Jw6B1kStue+54eVdijeQ86YT9ALPX0aTXj8j+yWJ3nAZJBQ6ITseA7tGsBQbFgrFxa+QCkGRykGCF2AJh0dww9UxV/lyyM1cyHTsyOQRVZ1qIqVBh2ynPAs3sLPtsZpBLIRllSu4++KFkNJZSSikF2TOxD8GIai0IaUl45qoxAK62g6oAFhBGme+C2aDHkvBrreiUeyuBV35eNYTQMSFFk1AXIPPqV3sN5C3aKNFs4dBoVF3OgGPaMKiu8Tlvoba1/z0BZvZYjuSzFFkYswuxfqKHMx1SmUUbmOZoxjwkdRdwrsxw5FTbq/+KiEeLfYvOIXpADiGg8F4AlbUQj5w/AgA4vEAr+4kplxtxgyl/X/vYXZBuCAXYE63gaKDg3NyzDhz8/bt+GwDwJycpF+W//BiVhx8sWAUCQ9YU8hhI+PlkpZut9HEopjb9H39BSub+S1LKzWh/bJ2kbSfufAVr99Ezq0vSAqJXp5LUhlmMUdegGtE725wVzcUg6hcZjUndaJ+KdiTayWg+dQeySzwZREokUsJRzfWLmgiRYyhqOLXUbhiGE5GNPnlJ/h4NqOPDKFdNxYrm7JVP1NyM15CjsdQUSimllILsDU3BEPBnjbO/hTTki9Z9kFqlgVW3T+7hDYZnZllhJHTeBj4pydnJgh9oPEQAJAwsSgUl0Vj6WYj6DKkgt960DAB49NEbcfjP2HafcwERK2+jVUMKy8oqX10JNMFqzitNO8xxyzRd7yv5Erefn8eLwlz7buqYxfurupoJSStILGprbKcz77+zRO255f0v4nKP7PVbZ+k+tzfP4xQXS3jgc3dTe66zGjtSXec+uCI5HJzG0jnMsQnv4IwzcElXNzneYurpioK3ornAuLR6kqn4luYlrKRMmz5DfXX5uzkpy9VIx0J0kBDB7VFVAUHR4ExuNc+Brvxtfnd9g2bMcRlcOzOtQ93C4joO0h3yKMgXElq1+U00WX1JYw8G4kN3x4tmURC/rqdHbgIcVd9WM3dddr2nWejAzczTFEQBkZiK1lgdy9cge2JSsOAPNnOqqg/6AfLC+AR56wYTQU+AA/3GYxRM7l6yBM2ImULn0e/0y5nuv/JBGpF1Dge+9+AruMpJQi51CVibec5g7Sa6SZ2z/lz9rhFm54mzYJ+iL0JCCLZPZAg4hFu8EGsbLRw7SqHNDzB7sXXBBX7JIJ1/gBo8ahvNAOU/Z8IZhtbeVZxVnzx/GLcdJqLpW1pnAADP9A7hi7/7NuqPKf4IYiBh5t5wkVXXNnVM7SqwcS9dd2k/fVEHmlv49OZ3AAC+tHySbpYKIOi4/vJhW2/ENeu08frqlf+vvTcPtuQq7wR/J5e7v7VevVollUr7LsSiBQzYCISwwWOPbXAzNu0lPN12j932OKZNOGbsiW53TLfd7XHHGLppg2GMjWlkmh0jQGDRLAJJiJKoUkmqUqlU+/LWu+Z25o9vOSfvK6FSFSq96cgvouK+yps38+TJzPNtv+/34XA6A1/CLp1z/pbjuGaGsiUbazSBH3nwVmwSxCEXOAWpczPExZHFLciBizs03sM5uR1Zay2i0Rq7pg5muHHsBYQrcMpHoT6LglDULugF1G2o8bOTLDZcQNwXOXQ2FjT3WJZ0QYoLxeFIViNs5mv4HYPgDOc5S6nch0oqqaQk68JSUDq21GuSoizKYsZ5rei90slxJFmRhC6wo1WMkkS2+nepuQt/LZWO9hmD43fQ31s3EmZfmJkfObkNq8yGLBq61gDCW0kTLe8l5F7riTqGIWn1Nl/Dyk6+ptXAuTETpEU2Ta/ikVVyG1avJNO5dVxIYqBNWyQQFi1Yl55kRmZjrTI8T3yX0pWvePsuAMDuxU24apI0rrgMX/7QbciY9TmZdtrJNe2lTcPNNPHDTUB8kK7p+EFiMHl2ywZ8J6MLu+Fqqp8IdhLO4RnMo36CA5+sccORQ5WudrlPhBnhihq5NPZVNN/5Mn13+MAcTj5I5TPCgL3pYKGt3uQ5aSwUYIgDRvydkuDkzsrwXQoROVY0tGsaywqRDSwU0Sj1BSb0gn7W2wYAEeESAC89WCsUYyNpxyILgKSs+f20ph0nTzGU2gScVSDpSgBeS7kq0FhJJZX8kGR9WAoWtIIa10VJ8euSrUmAkQRsPKCSpGxqjAxMCgN0o9IxpCsUgZfG0prGBfFqS7Tt6F0JNm/mVmhLFB2Mv0efWQZkm+j8M7vZ554yyB8gn/jtb/8aAGAq6uMrJwkBfvSeHQCA9iG2GK6w2Ho9ae0lriEIjFV2Y/FLxV+Oe9axS0u/ippxCD5xO+MAK1dJDpXG+N+eIS3+yosOYgs3gfjL971F56eoi1XAx2pmCPi3gs4TcBcAJNImzfOx4ylS0ce6FCwcJOTUt+d7SJYo7iKWWRFZBZfVuDrwZD6Jq2sU77hmnuZlV0p9HdJhQ7tYieXS2xLocyJEtTY0CkISyj2h9EMAHOhTXCfZQFq2dTByVHsyfzWgsUTX1593lZAAAefUJpVHyGNR9rcBpMUlPal8Cp6br92jLFwcQiwQtgTsKFyDdjTGam8HkSCwGkPIFLRUWQqVVFLJD0nWhaVgLIFFgsyt2uFY63BrXDS59FsBgfgrdCIZDNqn8CLgqh28rINP9y0nO/4EwY9F68g+yQ19tL9N2QdhN+pttWheTr6w9I9cvH8z+jtJnc1xTGE4yxmHmRSnv0rcAL/+C58GAHzi6M2471n67d03EUPTw1+92RsTf4SSETCOMp75A1YuAyafoFs6cRf56EJwem3nCN77ibvpO9auwzmj0XbtOQGg3uBeDZNkufQGNFkbp7qu6xXfqMnGCJ0aqeR+St8JHduRZzbAMCW9WAdB6u6hNE0dFjEm2Fxrca/KNlO7DeYsRssNuXj6XcugYG6IgFPRWQbU0nIaUSyLIKGeFQCc325cBirynjXZlkyOpQlDqx2f5FmzWaCUadp2QL5Lg7Uq12AN2Kmk0CU+IQCnzCiwqT5Jc9xqODTfkC2yLAuUOl4kOkPa9GxlXSwKAABLJmY0hk+QGxwmgB0z1Uxc6ORq+amxCNgUlqBRjd5XBBmQj7M0h0DC9Ur51YSPv2Hrcfz0podpG9u9f3P4VQCAw1/frmlMIfPIJzJsnqRA1rOnKXI3/7qjaH5ss55XrkEkuYFeuD/5+psBAHfeuBu/cfFXAADv/vAvAgDqnKWLu1ZRejXpstx3+AR5+G0IrFxNL9cU+13CZfjZIzdgw6O8iG0JdH91G+ThtAZpwu4Xz7ekDgGgxezMoRbqGKScKxbU4OFF6vqMyELoFaXPRThwxV2jVbqo5byFacnoybjbND8HVja4wBtL1rLq8gm2JMhdkFAa7krQNe5ZLAyJ0CVu0Q+bJ+I1lHt+E1np2q0mvzVeIxfe30MXatdnxikE9bzkSgDkjmmpv5wzLMhNAJwbIVIvNJ0Zc01DmruCP7lPdH6uBXnOzshnL5X7UEkllZRk3VgKxpJml6CgosxYo0tTVwC6tJvQulXbI+pQ8NIZgE3iUgy5ONFeu4r0CB185zxVMe49No9/95mfofNyCkvM6zBxx+1exuoqtDh4itT6rRcfAAA8cs/1CKV+g81TIWmdfqiGpRu4So6JY77xiZvw3ZNEippcz2QlbMFMPmW0tFzSkNZAl/SlqwUwYzQteAWXP2+uc4rvP25Czj0hJEhn20DUZWy/NDIdBsijsq4QzRQYq9aAVOUNR3XV7l12LdR0NYDlknLT44rRmlf+zWbyqbSDHoPVhKT1xCoHeOsZRn1G+HlEueMM3EVoNIgsFoMEHmGJ8g0AOm1ubjtoIh6Uka+wLsUpZexGgoSTqWph1w7OzZH2ahCClJEz51V3e6jIkniBczoYuzXtVOfSTzHmefn+hFGuDNxTLcrDbmiSpXUGYPDzSmUpVFJJJSVZH5aCJR8/7lkv6FcGp0QDV84uK6ktzBoyCVsYDWb5mgUgTgQhhBVtie9OwPA5n3qKYgDRcoTupRwI4F4TtaO0U23FYHQ7xQ/qj5M2u/J1T2PvMQIEPfTp62m/AVBjy0BiENrINreY+R7XDrD2bpyyqrlqSxyA20xjCNJQ1Y1owyAHMtEshcQ2ckQcLDk+IjPj639KsZAwtDoOiaHYwMGPZc4KaxQwk3BKUtJdaZGjwxaZ9HMYZZGmVUVWF72WS8mY1ZHDWXccJDyZTKAt9Se2zBUAwNUOpGIBGv2tAJSC3AHT9GdC3OM9It0+99QYeMFFcekLlwZWK0B9f6ugJSvz0si0JkEtAMkgtjKNL2hw0et9KrwHRRq6ZrACy+b+HyYokHodpwDiU4hr/FywVdKsp9qJa2uHLMMJDs4dwguX9bEoiFjvxRHkl7wEfrBJSChyA4tyMEduGOCCiWpqxkbLaaUOwQaOQEXw9r9695fw1/uIO2b1KOXesxYdf+buozh9L+XQ5XdP/MOlmLyF6hYGOS0URR1IxxihlbUo8fP2vC11uPucsQOTj9OG5R/rY+7TjGeQAGkALF/OLwbDG97xxm9qg9a/eJSIUqQOiX6E0v7pBJC1y7n9omP1wU45EJhxQKvoBIh1geCFIwv1BR4OyJbX3P1S7C2E7lPOlTKC9HB/St2HGzvk/nzFEj9llkZOCUgmwHjPiU+yIlyICkUxun0ippsgjMlJO0Dcd+XZAN2LPnNbKh8oK4Urt57A3gNb/pV3oAAAIABJREFU4J/AFsbxMI41ICpyU25aBNACKQVOglPIjVfgQx8SNIyiQoOJOR8/rmfqxjS5L8h0c4hNTXqghQ07tefuBFTuQyWVVFKS9WEpGAr2GGu1bbxWSYpGjZ25qe2/W5mu0JKGzL129iKOd88iv41W1OBrZEP3tlu88033AwA+vv8mAMBH33MnVm+i1fpl1z0NADg1IAtg8fNb0R1DDV6+4zjunH8cAPDA5A4AwP6PXYERU6hJubF0dKKxuGsHKFAmufHGNVRHMUooeFl7tKW0Zlu+ySi52CBjDIBYIK0gQYcncP6/ChBD5tFZWlpVGbk5lZQhAA0ASrchYV/OskAtBMErxGGuqTrN33MfiDBx9Srq/iRuHCHTzaVFiGX2Gy+rEaKxlFqTVF0qAUQPe5JIINjVh6i2VisM2LdANpOY+ys7DWb3lPEsYWKRTpZTtCGb8k8c2rSG5dvmgboBqpglZpiEZbcBoOdFU79uf2HXtu2sdO2joQPQSGVmOorQbpJftLFNn9tay2oZdBOuohVcBlxp+9lKZSlUUkklJVk3loKNGKsuiz1rNokplIA2LEFoNT2UDyQiWUD6yGvfSI8E1jzMWPwfJW1crDTVQugxO3N0ETCzlQI2j+yi2oGACV6aEVCbIW188Rwd4465/TjBfeafWZ7R8cbcmUr8aa3yjIGU/djeFvqceMZi+TrSFGGP4gcTN1OKtHbPDNIlvgaeguWdIZiAGbff9SgAIA4y/NUf/TgdQzWSmzNFQApJTQHYutO0AGlNK+g8Tn1lnHk1WYBTTIYiqMdREWgQTD+9tJv4/Aq48+IBEic6ujyJh4aXAABe3ngGANDv1nV/BS/JsxEB8YKciy8lcrUPErzV6+5aDDjAKPGOdLLQ/QUQNpoKkLcZBDTg50rrFoyzWCTi7XEjSCrSsp7128iXOD88Nm76zsByjUTQKKcfg8B6HaI4zjQxxKYOPVid2CUc6/xwdTjAKLGFc6FaWR+LAmcfitAoo7NAT6MBF6hkgZq60lHXWhfZ1UOlgcMUjDUJDTIob2Lv+4Q8tFtSRSM+1eA2ZidDLB6lxaM+T1G5Yh+5D/mtK7AcJHrqGSrpTfMQL99AjMrZfVRW3TxVaKZDyp2TjoNML9xC1zDxBJmIC9cDU9+n21Fb4Zx+TItDmFhEFMfEcJrLcZvO5N/CWIT3fvmN2NYv4zzkTR3OGH34BQ0YpEZh00XsBxwZF8BU7FICbCOrC4YEFQFoJ2VtWVa4zIAspsk0nzu0ALsQEvXPsgCHEuKn/MkOddAtdU9mZWD6gY5f3AcfayAEMyJSLBUmFuYwzWV8Ca2kSSdEXuMsAiueZMo4U14yHl7hnGYYztT4RQLd8sz5AUTrLQ7jC4UFwF3DxU0ToXZwTPvP5dEXTS7rYtDPaBIWkyY2cIvBNsPEm6wBlteM9Pmlch8qqaSSkqwPSwGUuw9HrgW9mL0awDGuhiBnhBuamQYYtXQULnUlxS2aYmsbZG8kO7x4kvD5taMx9q1uAwA0uI9D1rZavjpaYTN2hlfxJyew81ayCo58lkzei69ZULNtwGQig1v76PwDWR4JA/vbzFAcpBatA7TKr15GFzX7vRCrl3Cq6RR91lccQk8US+9tFDgaLjZhOKD30AJRjE3vMVofInMl/y9qAUQ9SUDOBs5q0IBnzc0fVkQde4E+KavOvACv9B9gi0IUaW3ZOEwEHyOpAZG002PbNhnGWOFmqSelwEg0to1ckJLThMHIaD2L49uxWhyVl2ETCDKr3IwzU2R6Hx1GyOvlprDDjVZ5QPNG2RowYeFKyBWb4HEyisXKcxfEBQpxM3zLYsxSMIWBEcxCvhajEbKlsGmCxt2KErUQhlz8UgtyxOw+BGdu3fqCpLIUKqmkkpKcl6VgjPltAL8KWvceBbWN2wLgb0G4mYcA/IK1NnnOg4B+HWSspQSXz4FGxbb7I5UAj3FxNMGDk+bi3/BvhQatcRoI76NYQoO1SdYGMM3Alh5ZBXmrcFVvvLK39tEApl93TEEsbSGBtYEGKze/nEqWb5w9gge+cAtfC+0nxB2dwznq3EWpvihdpAzyFjMxj9V/REOL47fSbze0KMh51cYTWE4oYnjk78lSmDnqkDzj6L6s6cA84kOHI+N6YoRiPTjw0hqejqiAZStN0pW2IIZhAK4seSBoTWjudWIfjT/qWwzmx9B/h+rYcxGhST8Y3EHHbXuoJOmm5AUtG4vMMC1krZGLIQk4SwO7tUDTwq2YdrJZgFqXj8GWUzqdI1rmdPcMPYiBxBlzR6hiFZTkBR8FXSqW2SByeWdJpUfWbRNawLqrWyg43SuxmVojxVSbzKmQo7NJESqadJYvdDIeqoUQ8UXX/dZZL1DO2VIwxmwD8JsAXmGtvR7UyuIdAP4NgD+11l4OYBHAr5zz6CqppJILLucbU4gANI0xKYAWgKMAfgzAP+LvPwTgDwG892wOFiRQ7eE0AK/iE0A2Ua4mC0Jb6vcA0OJtGdQjRJ+MnKUuVEK7wJ2L8jqU1CLjbkq2kSM/RVZDyL6t4Oi3dZaxxDUSElEvrMFUkzT47+z8IgDgt7/2DmxbEc1P5xrMMVinHWhdhFzvqbuHmLmvwfsxpJWj52nLoLiIjt8d0rh6tTpS1tDT+3Kdq3F0q6T/0gnr1YDw/OVAJp3LhXas8ABNzTFOgdy4JqjSz9Brsqo9CthiSCeAxkmGQ3NsYThnVJPXVlyE/+gK7XBslVKeSmzaj5xPznPVOOU1j/VcaK1h8HpDyvwJcKybyAMADDbwfReyVls4KLU0LBawVeHBlmWOrXWpyLHKRUSFguxUMuBMLeK1J6QSATPhTCPBTIMshekafdbDTK2CJptGUZAj44vvMfFGJj3sz6FO8pwXBWvtYWPMnwA4CEqH3gtyF5astWK7HAKw7fmORcxL7Cqw+6BEJnzDktlc02GKPbcuFSTmfp67UIsRkosxTDz9hz6GGwtEC/RmTO2lbadfVaB+mnsdcGe12Z+m0pI9n7wKgxvoBZUc8sHVGSz2yJT/108Qu9HOi0/g2FXEziwNZaTuYuWqAtu/KC88PUyTX2uo+btMsH+MmA/x8iuPon8vtXwbzNHC8bYf/xo+/C8JkyBot/58qJ2ZxQWR45tibYGYDd3fUo8gNR4AlMFK8QEGzlz2AmpCJiJ4fsOmfx6H6PECHS/Rd+HIoH8RjbHPaMF33fQtHBoSvuMbh3bQuSTYFlsEy4yQ7JcXS/9aYBwWQtrSyaITJq5YShZS0w8VcSq4DZMaTfNKUZgyKuWm3Cnamxf6W1wFyX9bN1fed4rKVTyOhyPhZ1gQjTOtgTJRBXyMXlZDxCt94D3QPfazZaHYUKPA5JMYpxV7fjkf92EGwE8CuBTAVgBtAG9+Ab//NWPMg8aYB7Phc/Shr6SSSi64nI/7cCeAp621JwHAGPNxAK8GMG2Midha2A7g8Jl+bK19H4D3AUBr/iKbNTk9JjEZ1nQSlDK5cakylmIQ6WosLb494mFdhf36CU3HyXkGBtM3nKJznWTmldxoH4TZ24ms5Mj9pPXjAghO0qosWqU3WcMls4RufOJhCvp1L+niojdQ6vLE39E2WdijlQDdrTxeiVkFBotvodV9qkOWyJUTlH48+Hc7kc7Tj3/uzq8DAP7y3/8EcuZ8FGKa2qpF1uRgVVROP5rCacHc4Y7WdtGyXo2J7sT7xF4Q0qMmE9BNzhdYStPlwqvI1tK2Ed58zW4AwH1PEyflRDhEm1O6cv+UpxAeIlRS0h6/pqRUs6ZDNEqq03WMMmotCtM0rNctjOclGAXlGhBArYOgnitximH3yCaBNoVV10nmJTMKupJAKZG4SKCRP+JCCVrEUugw/V07TpTMppvSRUdBvoboJgpyTAV00R0uyT2f1OT5pCQPArjNGNMyxhgAbwCwG8BXAPwM7/MuAJ88j3NUUkklF1jOJ6bwgDHmHgAPg0Io3wVp/s8C+FtjzL/ibe9/vmOZnPw/G3raQGjHNGXmaSnxwxKjK7X499kgcnDoomwVEKEn+9oMOZ6/+TgOHyGIbUuwLIXBTS8nuO3THyVtVlPYMFA/HZSOu2ynEFzKMY0ZuoA3Xfo4FhIKIhzhxrLda2gVn3q4jg6nD/tzdAHLdwzRYj7/V24iC2PX6a16HgmQfu4vX0NjXS2AVQkOOrCWBGY18+UF3USrSg1EXnPz6/MdaMxG4gZSnTgIYAVUxDRrxTBCoc05xrRT5vgDLGvXVnuEG9sU+X1silK7nXCoWk8YnkvEI/xn66ikBOGBf/g6M3du5eBQwlwXZO2dbvHvnDUkkOkgA/J2GYQkYgujKlSrHgP3t7aFr3mml0TWvCpPk47NXxooJ0OzRc/HXKvHh7foZ3TjGyFXUBqLEVdASvygE44wYCCTzGNDAlTwzMKzlPPKPlhr/wDAH4xt3g/gVS/4WCGZ0IWgEaXmhIuKhhuNizR73XwlIqwcebEriBIKduUENF5g7bVUUXPywU0ILiFzXV68eOMAT55mV4KDUNJSzlgg4szFcBMH9foBFg4R/qF+ks79tY07JRWN+DVUuDD9BSrfDROLU9dFpXNiOcbcFhqTtDhb/fvNuk82y7Tru+h3ScdoYNLv0C1clobnTRaAIDFIpuRvnsaa90JIuj2CrnY6b/IC5p67wYQ0RbOAkRdDA2v8kRlYbrUWMFvQxokeNkZ0fUINf3F8GrssBVIdY7IXaFwSfAWPO3SLmKIXPQiAci5qI2K3AJihCwQGWujFv2tZZdqSF1Wp9dNAxxRy7U0+DBExXkNYltStqhWukEuUVGbc/GmTFxconuYMVo2xBkkRajBxkrMP3bSOjFeni1rksrYCBwOKTbl+4lykQjRWUkklJVkftQ+GEH02AIKxxphacusj7QIJLnomo+SXC6Dg7aLRpeV41gRWd9D+8bfJZaglQCqlqqw5RsebyHmVl3S4YB6yjkfEIXnw6RyG9092kPYLvzGnvR1ef9mTAIBvdshSCJaAZJZUxq/fdS8AYDlvYplzY595z2tp3BxQe9lPP4a977mOJ4TOPdpg0Hm2XCFaxEa1qTTm1QCip0AkZ1/UnOYSiyHqG9emTfLngkNIHbGLuBT145FuU5ITCf5mRlOBZolU+qHjm/G7z7yd5naGtN/vnP5ZZJzOTBe5xNlrTjP1FI/Re1pl3IJ5yFpwNRKCfGQLoQitBq5DrrQstg6BZ2m+Sw1/hN9TJw76GXAzGC3T93gb/V4k8n8rfRnE2oisoxX0qnvFbZhvkQUllgKymiIUhbtyqjZUt2GkLDIO8VjwgJe1Pv6FS2UpVFJJJSVZH5aCpeCQDYzSa8kS7ccDAmms6acdldmZ/l9kQalHA+Dc02TKIJvndM9h0kj923uwK+TYS+Vd1g488g76HG3gQNnhAKMNNMZbbqJg5O7jmzHg1mbRUW4//5qTuGaSfL4vPXoNfce/u/WnHsU3GaQzFZKq2xQv419+9Odo3Jxq7F9GF7DnP18Hy7EHbouA1lHrzRVfZ0AWF+D8auMZE5KK9I0xcbs1tpBAKwqlUlAAZEVsETL5yNQTtH+tW7iWehPleEBeN2gsSkpZAFwGySQHxSL67BwqMNhIx63zGLs7mXCmG7hWghK48xihtT9I4qE3Oa7SWKKdkrZR3oXWMbb4Lk+QTEk7Ov6I7Fo1ad2nq3r0vh5r/6ZBSP/WePURSkAjvR1aGWa4V8NUTDdXqNVqYaZAJamMnKk5RKPUN4SmQB3lWgcBPRF86IXJ+lgUAA/hRZ+KNvPKYJVO2+vzJQGhQD9zFEsxH8NF5QGg9epTaHySTPge4yzjWoZ8QKZWfwvn+xedGT6e7u3dOETtaRrUldxw5dEjW7UdWeMqihyfOj2B0wuUdmgcpCc9uYJu/v3336Cuyo+9kmzjf33sLoQDDmByy7K4w2i2NNYMg0iY2DWchDZwRUCSXYn6HmJuDPEaDh2aT8xwGxATNeAWCpnuom7VfVm5nHPrg0DnSlu58VOVTlh0d/A9YMh0PD3EJRtpsRQG4m88tdMVWnlBOQDYsMuUi+H4+HIucS+D1D07rhCKjjGYN4hGY5iOeopT3IFaiqCKqWwtM5Kjhtbzi3KyuXHw5rFWAyXNJe5UGqzBKcxM9TDboMmXxUBchVqQazZBSFSaYaLBxAZPwrCI1W0Y8k0LxwklX4BU7kMllVRSknVhKRhQcKikDceCRsiNY3GWst080PywkgbnBiG7CDkvlp0pVoMf34CMNai5ntCCxfemgNlyAVX32gRb7qWpEYov0XS1Z+vqWkjDldqDHQxfRue4fJbQkbt62xE8y70abiK/5Lo5Sk0+mm5X6+GBIaXivvWxm5AwanHqMtKkwacoGJq2CXkJOKSnsQBkvnwYp8wpj1HSlo0Fl6vX1J51WlWtYD/taJxFBgAYBkqW4hdQSfBMy9yl6WsGpNM0gLhJn9MTA5zuec1iQOk+vadMHNM5wJRwxksd8vXGIw+H4ZVTiyk/Uiup4Gt385G1PByHBKcFeZgEDmcg4iEUhXhH3YjQ5UHXpDB9VKio3tw1sZGgZRgU2FAn61KwBq78OVekp0jHM/ek+fFi1sAqm9TibiynYmKfxguVylKopJJKSrIuLAW/M5QGlZIy8jDIHOZdcPFBI0eRlte1iZk+RiNacZMFWi3NfyONawNgdSenbhbJmY6bFu1npaSZjtHeW8OQy6JT6cVwhKZquDVDayOt7Ae6dNyZO4/i2CKV/O7+CiEgb3vjbuyZpFZyl04TKOmyDlkRwWUWe44Q88vnFm4AQIG1me0c6fw8HVda3Ycj1z1KynyN9SZLPgpbii/4+2cto9WFomXjnkUqxCsclyoiIBUi5R8An7fSzcoCpim1AzJe2cmgcYAONtxM2vV0Giop60qPKiPNXALL2ldShoJeLCI/VsBWm7EaRHYDAoS0TgOjgu700rHaXNca1dZF3+sqNl4KLcZYI3dBxDNUiNq8bK2ZqFD0J/jTWKxhJL90cgF1jqAWKB8jDnINJkocobBGU5H7uhv1dwMORA5S+pzk7lHnIpWlUEkllZRkfVgKIKUXplapsWSVlzRh3ghUWwqO3hgglIo1tjT6vQbyLmPDD3FE20uH7byBeBGOfJl8+dFsoZH31StoNZ79bqipPWk0O/kEn/xIhH97598BAD50jPo1RqZAMyLHd/9BMje+ff81eOfd/wAA+OA3qV7h4RERJdhOhvhysja+deBSAEAwmSL4JFkICiQSAJJxlPduwtwcaX2IR8EmmlSuPRw62jGhzYeXAnbkLMZZCEIFz9aEbVrF8xcN+Z1Fxt9HY/Bok7ssQeMY90SshzDca8JuYpOicDUBm75Nm3KhnBcIv3d9RLAigCo+hEcwI8+J6y+xFsTVrKVYFAJgARzVCrVYJLZghLTWQE2nwAMeaYNjuQepZ03UJUcauPlgjgrDGYwtjWWkfAMDfh0F2jwRDUsQZgDYN5jDqSFltaQGoh0n2NggXHu9XU5NHsELl/WxKBj6V0RGXwghJHEsw9a5GIlw8+eappRAj4H1Akj8W8llp1aDXGqSpq5dm7AFW0MmO220pWMAwLUxuQHCpvvYga34hZsfAACcvJoWheWVFv7+COETpLHMyhPcKKae46I5YpXus7m3cv8mRV5K8E/RiUMXJMzqsmh6L76kwUP/RZCAICMPl2wpvSsipr4uuIFD3ck90Bev5s3bSNCOblFKJx13JgAUnQwhB+eEbTvPAi0RTvt8s9MADa4ZyRrl+Q6yMq5Cxixzo2nTwF9MURqH8dxTCdQO0whmKH0f6Lu8VjjmanYLQmaAytNAFwNBehpjS3/TCRyiUQla5HkN3HXVuYlsjkBdA61z4AtoBCkW+SYk3gO4rVXu5jDIY0U5ShOYfHzSXoBU7kMllVRSknVhKVhDQJMihK7uqgnGSntpI3/6yDwx7cIceVhe68TsjAYWy98nEx3cgj1eMQoWciQuxi2XHBiKuUw5nQC+2L8SALD7EJX+vuKyZ9BlbjxBpwHAsWcIKPXK6wn5+NAmWvXre5rYP6Qg5M4dBIAarriUnrabl2xY3agVoVWenlmtqbrEuQhaIOhR0Y03ew1HDhXpeAo9sBBvSrkWwuSAZWtD7ocNrQbPAqZXk6BbFBfotMsBr/7QlfKqJs0MZvew9TDGvVhEzgKQasYgc8AkbRU36blC/MzIs5M3sKaMvlNLsVAXRmgekPfYhNzCzW/bFkqj3cS9NnKtRrpYea3plf35DEp7mlmaW0GCPudwRcufTMg9GBRurmr8QkxGVgOS4j4kRYiVVFKSNMaFIVms9arBbCWVVHK+si4sBVOQ1sonPC0lms6Lr4mvW0ydAcIpWjWJtO+Aa+zqtGzUZX95guGuK0DEeP7VW0ir5Y0GCnGP+VgFa6ZwAOxjLZ8vkwp79N6rcOzVRwEAb7/oQQDAA8uX4gQ3Ar28Teyvu+pEmpJMW/VnD32L8NbNAKpSrC371WEKFNpwl7YVsQf1lR4CxjqLQiwur5+m0XmQuISDSteXufoxMwg5GCaxFqU186jKCgkWNgqM91bcsonjJSOn6cTHneoMkGZ07UurrhhjPEiocQm/MpL3iYbWkfB4ak1SuJK6VosrWxt8bMUJwPECZV32HjapfpRqyTDOYYuyDg0CqzBk/Z0PbBoTG7rY0EZuJx8HOXrcPl40v8QWAjirQM6zktU10JjzeOpRhlFGvx3xK73Kc+8x1521rItFwRoXOJNA0Iij/4lXAZrzgwgtgjIOScZiAlt6UIByUZCY3fWD/JLlVhuhBMcFCOFqAoQ0JerJy2YwFZLpd8N1xJD05PGdOLVK5tqHnyF+metnj+FN83sAAA+vEEfjqy9+GgBw3+lrUT9BU1/nbtI2xJoCJy1r9piGZIGLBt4L4QMPc+9v+AFE9/C6F8S9jKMp+iPuWVdPwIHMOgEskUy6/TMlcwkV7Sngv5NL9NC2m4kGGEf8kPaLoNScFgDaT0dIGesgFrNgDWzg5t7Hamg3cslItFz9htZx8HjymlM2MdeCDLPYmfeSfUgCdRc1gFgb8+XgSvazUai4Bv1OXKLCOFyDuCB5gKL13CQoS/ywz3KdQy+vYYIr4Abs43TT+pqF6GS/jVOMkzEH6BhTTz7naZ5XKvehkkoqKcm6sBQA1orGmYUiSqLRxhozFXDVkX5TGO1XILvzZ3+zwVt/5hsAgHsPXk1ffX4GQ4oHon3I5dm1Ycmyw/jTH0SIAgC3zZDm3z2xA8Vh0o5mO+1/ut3C/UNCNwqV1i2TzwAANt22gpvb9PcfP3EXACD/zIaSRQO4lCrg0dNJU9a28Zrx8j7e/mtmynjsxUqo4jRzxho3TNy5pHV9IfUWuUHMxDVSxWpyYDTHx5UmMKtkca2kIepc8zDgbSawWt8Qc3WizDXgYRzYTTKcrga8WgyCL5auxf9bqzQ74va4+5i2adtkfaga36xwX4mBQcYBaKGRU0a60GgzY7XaoqLUbwRAuWpSMAvefQ0YRyDt5BfTltYpCK+ilEkXto4eczRK+ntp2MRin56/7gky1zpPxpg/yLiKfIzw5hykshQqqaSSkqwLS0HAYiYFwtF4IwL6SCcMsrb4mS5NpG3pZVtUKJGFaJ3Tt5Af909+5Cv44MfeCAC45k5yuvbXZlHjrI2CdbzAlGhGny14X5dU44k++3FbhwC3mcNDxI66++YA12+h4KNw9neZZfToaAqfuOedAIBb3/ooACB/1zHsfv91pXGLWC9Ve6YArB8vcL722DE8QJa0bA8Tixr760mHfjCcMUqWIm3xNAhYsyjqopH4XnhYfvGvFQUIIOE6lNYk+cZBYDG5if6+ZIKCFdO1Ab6wl4BeEw80+fj+4KHjlfHkElyVFK1fTCiWhRe8HE8LrowaKFZ5bCe4liZ3FH55S9CiDKpqWmc1SFwgKrQrlp5aAE6JdwMk5pMDjRYFaqR1/IHeBq1bEEo1YW7uZTWs8rOzOqLPQRKje5ys0rlvs6U1KDSVG42B0c5F1sWiYCE3zpnErh+g5KMdRFRcBdOAhyBzd13Ke0fXk60d8Rv00ffciTY/WI99gyDHU6tWo9XphEP/ianKnoKanaYAHv7eZQCAO26hPnPzrVU8xK2tJTtw3dYj+OmNDwMA/veHfhIA8MQpylpcO38MeBmtRA9+nAqirnrrE/jx/+V+AMBn/x/iaCyZnXxcwRPkNe+a+aNEvMLi0JyubFheoLxu1F1LOu56s07pEB5dvFmzGJjMOMjzgMud5YdeaXF/SBNZ6yToB5yX77gX58evfgwAcNHNVDz2vRWCoX/309eitlzOKoSpdfgViT033IkV+Srvq3X3Vubj0MkZhVYLq5aNXHZKMl2WA7uxV/Zsu+4eyLOmPShjz32QILiU97cK1LnrtWQajnUnEHIwdqNQu/MFtKMEzyxx0ZjMY6+Oyb3s7rACtYGbh+H0ubsNIpX7UEkllZRkXVgKMITEC3JX5CP59SBjk+pUoGmqbCMti3mydk1rtBNcvoPKQB7bdQkAYHo3m8azRjX01GfZ9C88/L+YvdalRkXzrlxFqrpxPELrWVJBX69TIHFuy7IGN695G1kPr5t9Ar//eWItnryU8o6y2u85uUn7G7zp7VQB9Mjp7bjnc68DACQ/SpG32c83eQxe0ZOg9WpG02uCP5Cx07yNBUgBzRn63ZnFAtGaicQ4jMN4R+/Aavs3matwGCAQy0NcOCkjTs2aUuE8CxEz7j9hbTnKIy0oemZArtm2Js3Zjrd/Dft7tO2Jv6TgcK1rFcko3af9uhlFxabuU1wnwTIUizVlcc6bziWS4G7K6W8leLFujuJlfx75byk3FxxJzToUpcxLZjCYJyvppGINDFqxzAe7Azw/BQxadXI3jhwmJO7c12MtaPOZuNeQN5+HwVBZCpVUUklJntfM0OJ0AAAgAElEQVRSMMZ8AMBPADhhrb2et80C+CiAHQAOAPg5a+0i95T8MwBvAdAH8I+ttQ8/3znyOrC6w6Bx2ksFdsuamgbDn9LGrJUryi1nJFmWhnh0D4GF6gvcS4B95MG2DI1dRKEWpk6FCmqMu5mh81PHkP8F+f/JJB1j9iLSXL1TGxCv0v4bHqDpi/7HHG979UMAgC8euAoAMF/vKhHrXMe1AQOAa6aP4ftLVDdxYkgWy2vm9+Gzy4R4HJxs8LXzAK2zZnx8v1oIGlgzXtrRpQzHxdGluY5c2kquSWXW/nFlfyJMldiKh3KUYYz1QIA1AGtBacraaI6zowCnR20kbL7McQmwSDsaYUeLKMVe8c+/AAD4wBO3Y+JjE2uOI1YUY8scGMy4mJBYAjayyKZ4cqT8PjUopDqXr0UuyaRGY1pisYZDo3MV8bCV5zUxStojMZEgAYY8b1IdGwYWsw16PiTtuMwgpsV+E4vH6XmdfZDTuH2rgWCx+ILcD6quRXq+UDmbn34Qa1vM/x6AL1trrwDwZf4/ANwN4Ar+92sA3nvuQ6ukkkpeCnleS8Fae78xZsfY5p8E8Hr++0MAvgrgX/D2/9cSeP9bxphpY8wWa+3RH3QO08wR3bCMlWcn0DriCCkAoMGYfNM0LhovUNTCrKFjy7NA/Xvxe4vbKI5gjnTQOVTOakSDAgGvuCdfSw7hjmYXj7yWLIUtVxyj7x7eRMdqWww2lbVltmsen89o/x23kblx3ydfjox7Te5/lOobrriRvntiZR53zj8OAPjOEsU9PvGRH8HFP3uAruEzOwAAr/ynZGR9+z+9TCnSRBNkDeMqFSX74JGJSFZBtGWYQFWAtmqve6lFpW/zKdLlU1KZrqW81ml4jX81Oi/3JyoUwBMwr0KWBcgijvHkXrWhNJhl9bfCVaeBKbQWQEBj/+zqr+Kx39kOAHj4370MAFBbtRhqr4tyPCWvU0YJAHrbZLKsV20rOU9QU1zAI1mRFGOIPCpnv/Km0biE3AtJaVrj1d54dPQRZ8s2NMkkTvIQUSAD5f3levfNYOMjdDzpWzHYYDzIO31mTRcHUmLfc2d4P+dA4ybvRT8GYBP/vQ3As95+h3jbD1wU4jDH9uklHAkK9ArK8zdO80NSd2ZfqYUcaFFwIH++YcMI4MBRyg/nOy//LgDgnm++HkOunJaHJPQCa5099BYc/dJlqF9JD8fKQWryyn1HMZwDmpw2Wz5ATWVndhtc9Yv0ku/+KOXbR5cWqC3SMSJmjn7qKC0ct1xyEM/yQGYY7VjEwN7vkdtjNtPYvvgVeuCn4B6sUo8HJQehz7QNxL3yNnlIssbaYrMiBmqDcgDOF5lvl7u3pT4LAJGtqNk+KqcObWSVfUiCrEVhkHDxTpcLgZpxqq6VBODa3MwkK0LM1ugFkp4GQxvjNZPUjab9L8iv+vKf364vuTwSkr4Ncusa1kzxS1PPYYUdXJCygS11lC5JVFBnW7g0JBKDdJrdo0wUEfdsWDIuAMvl5nkMTHETWUEv1gLX8EXm4/gSuUbtQwFiDioOZ2SxMcpFmWmTHjdMSTufj5x3oJGtgrX44+cRY8yvGWMeNMY8mC4Pnv8HlVRSyQWRc7UUjotbYIzZAuAEbz8M4CJvv+28bY1Ya98H4H0AMHHVZpsWIbZMrOLQxbRO9ZbIYpjdzZom86wCXuGDTurYdOXAmXGBSE5ZfvEopbKueNuTOPpeAh6pNqkbDaSJxhtNGa0MFJ5EaUzbPGZQ20OAkinB1kfAtx4m4pUmBzXDgdE00egYRZya86TxnlqYwxSj+oRY4+a79+Cbe2hsW7eTJdL9Alkp3TetonMvp7CkFtYAqSAwPfq2XAhJ2IQezrK10nfAJr/SUTS+pmVrgML3xY1oiTVhNdimgS2vhLuIx3SDpy6kFDlAgILr0he6dAHthgs+1iIyf1JJzwU5emz21PlEscnR4xzg7R3qsLXvXXM4/J7L+dr5+lhD++i+bJIuKjxZQ94+A3OzoqH4OqVc2sBxOYq1Flm3n4CXhL6vZlzAkz8H8wU2tSgimfFxA2OVoKeX0M3LjtC8dLqW3AU4S84UgIUEPOm4acdq8FsqW7Nya40XJOdqKXwKwLv473cB+KS3/RcNyW0Alp8vnlBJJZWsLzmblORHQEHFOWPMIQB/AOD/AvBfjDG/AuAZAD/Hu38OlI58CpSS/KWzGYS1wDCLcOnkAnopaYUjc6QZfVy/GePWD6MceTaOPc9guXY/5I5Ph58m8Mvq3s1oCoFo5FZesQYaCzIgB3bRSkVmXy6WO6oplAR0zmDyCQ6QXU7H7xwM0L2Y/g579N0UU3Ct9BvYu0TxhRtnCWh1becIHmjsAAD0P00WQv0tRM7yoWs/jF//+G/p2ABgNO20gl57gTUAHqGRi72ekvLdaNq1oo+G9Ed9IVRodzJZrn0IEqNEK8pKbN0xstYYt0ButFNSIeikeo7RkAZZb3AFZRJjgn1tsRAabDEkRYTjzL8wxSWiJ9JJbKuRKdcwdIx/tvU+/OoryFLY9ACPN3cBUgU0TdD+ZrXhWZ4S3DaOkk94EuSRs+WgI1/UGiizzI9fayFau5hPtGK2z9WPhTVqNQz4uZVguw2splK1WXLoLETt39F1vU81fnEGkt6zlbPJPvz8c3z1hjPsawH8xrkMJDQWcZBjlqOyh9vCFsJsNLlnnnIEt8jdgqAl1LmBEfdBOP34QRjdMUDnHjLlNZ8fAUvX0P6zVJtEmPaxKP4kcw2a42014WUx6W+1mHmsfM7Vq1NEC1wLsJ1+e/IxWggal63gyCkKUgo1/GQ0wM4txBK93N3On/R29my8lpEq89yG1L3w4iKMGAPfPOmCUuIiCG7jTBHq0azLTvjl4jJXik8QwpvCqL3psAsCj4R7O4QRqnBvi6A6jbEYsuk80aBBSgS+l9Yww6QjwmgcwGpx2TFDbubVtaP43bs/DQD4q2/9BF1nm5mJluwZgqzWtYhjd9TWCwdMkKyWBCE9digHXnDug7aDkwYwxrqmNLxQRLUy/TpAi8MqBxgHJ+lt38BB8Dw2pcI3GrdXDCfr19BDugoO4wzMT2crFaKxkkoqKcm6qH2w1mCYRZiNe1hOmJWWW3oZtgbintW/FW2WBI49l48VhNarYeA1j8uawxNNJMxMLFo+7RhM7C/vbqzL70u59pYJSiseqW1QvH19hfbZ8F2Dk7eT2o6nSNPFe9vIriQNd8k8+SXHGpRq6h1vq/Z928u+BwDY09uKfd8nRGP9Ug5ePU1WTe/lrqmt1DRQhaNMoMvPi8ZoHeeUK7tByaRBY5H+HnHaLO56TMYyf4mHexiU3bV0wmkfl4JzwbU1/Rl6gdYViOa1gSsvLjjAF8e5cjh2R+UBxaFrx95kf6kRpGhxvm86pDnOYbCjRpbWkTfTZG37HI8j8TgdF+n4BnDcjCIFHHZBnqHAU8u+hQCQlSRuCfcMETM/mSm0xLo5RZbitpllxGx++ZRqixJwPSBNjd2QtJ2foEq9Ifu0c3If13BdnoNUlkIllVRSknVhKeRFgJVeA4Oihhb72MqmK6SquWtJrj5sYJV333XvgRJxFjXaccMVhJ3PHp/zNKNLJ8pq7De1lQBP9xI61t5jFA+Y7Vr0ttJ3EpgsYqCzn+sguGWdDQGzm5b8pzOh6nK1AfEMaY89PbIOHjh+CaKNtG3iIfqdnGd/Mu9SqE06Vtp25KViRRQ1h8WXQFPM2qS+ZL22cc56kHmwHlv0eHcuBQUVHqZeEHQDly4TpSot94rYoR39uhVJ8wUcaEySCO0maf6IA3xxyJZXkCviTz5zG2jMQdqxrxZNTAd0sb97O9VIfOzvHDrfhtJVjJ+T2K5BYJZMnbGg9pr/8zWFXQ5Sjh0imhti48wqAOpGBVD8KOXxynN+oj+B4VGyCKe4fkIt1sILHHoGlHbACtz+dszoqaokK6mkkh+arAtLwVogTSIM8lhZZ+I6xRQiTl/lXrWk4T4NNrSO/kqw+EmAgFuLC+w2Y981SF2j1uEMw1FXXI9KTc/1rcJF3/xagkh/9uEb6VgNgzbXTwhbkQ2MI3j1exzymIQ6fuuNXEfxzS3IuqQdAk5hvnHb47jnC9SwdusvU5BDSDv/7Xfugvlx0qSbP03Hymvlng4A075LPIAthv68i8ALsGk0RTsl0xbNE+V6gSB1v1VIsB+iEbdarRNvHNKeXvgDCgOTeIEaALZVqCpKBjSguJEp9Dnkgw35/1FcKCRYei6GpkDI5os0Z22YFD1L87U5ol6L3S3cgPVErnMklP2jixJHmaYMVhamKFsUZngGvelZUOP9K7MJ+t0rLjqECeZGO9AlSHstyDSmsMjFLCeWOmgekZ6W5dhM3jBrnk0buvut92nSI62NX7rahx+uFAbFMERkCgRi1vOLnLK5HPcLVwAkTUm8fI2w6ma5UWy6FPIsHaT033QMjOruJaFjuJvhY8mD/4GCVl/78MsBAJNqNjuTeDRLf3SetUofJy+csUDKeX5Bm4kM5zO0NxPuIbNSANTEW974HQDAfuaAlKKplQ9tdw1jpR5haF16TcpljXtgpIAmWHDprXRSUmR8jJ7RRUxZtI1fyFNG650JzB4kHjaCH8RQF20XhFTCkSyAaXEQ2WPnlv4Qhbst9GnsGYNzCzktqsJrOLQxJgJ6MzeEZIfP/0/PAAC6f7Ydg1m5gVK3EOiCpbUM1rhrFNfCI94ZLw03HkWbFinNki86V+/h1IjGKE1baoGrY19lBue0W0OTFxS5jz6tnNaR+MVs/L2klm3oFgO5Z9F5VA5U7kMllVRSkvVhKQQWUSvDqAhVKwjaLZmkqJexgQvAyOrctFp9l62w+qsVytmfznD6cYpW7yJuuV4Jaga7dJXUKnQvATqfJm3dv5RNOtaWtSUHAqpziq+U8lKL1CjzcfMAbTv9VSJW2fa6Y7h5A5WE7O9S04lnl6bRXaBr/a3bvkTjZyvi+l9/FPc9ci0AYOYRNpe9wKEEo6K+CzjZMTMfMRxm38usSdBR3KUi8oJa2tnIBQ79IBgAhDnWWBBqYWTOKlGNWytKAVcASItIKchEat7/pS/CREz28hQGmAjob3EphjZGw6alY7xpfjcA4BPpNteyXgJyoXVj8kTu8xq3x2uZZ4WUJTaIloVBlj6ERGYpaeLZVbJQY7aCmmGKVa5zOMXuY/NATa0BMwZGszBllmoAKMbcOdpRK1mDtfioFyyVpVBJJZWUZH1YCmkAe7SB4cUxJuvkDzZiWvKsrHzWC7awLxqEVmGzQYcx7QYoFkg9RasclzD0/7zp8Q1IgKhwQA/xwyYOOG1aXyinRvOGxbAtKUkXixjvP5DXLKItlCIbMU9/jeJfOLHUwUOWoMxXz1CB6eUTJ/G5/RS/uOf/oK5R6mMaYCvj+I/dwXGS2QQxA7wmvtTWqdSKxTFarqxpNNWoAcHYeqAYCTgCludG4dw8Z8bCxQ2U7PYMMQgB0NStbssl7eeR7YrGNWHhOizxxCfcb8HWjPriPday/aimFZMBByFikyFndZ3yBUpdRNoKkMzwNYkVlAUO5pyK5WJc7EMqImW4xRlSl16KVupsJDaSFCFGnIpstejBmoiHONQj62Fpgbs7jeAsLTlszVlS40FFk3uQZqHVS9xvRXyOhRcq62JRMAWh54Z5rHyJUkLb8wpCZDI0v5wbVzrNWIAgzp1rYMv71xftmpe31HhViDgmjboG2tJMblhs0DrBeAZ+yfK6QesEE2VsF7SghXmcFoPmKdp/8XV0Z5u1HJ0amZnfOULEKtumlnHHHWTu7vk+NYURnML0UwWyBh13irhFEGR1GH5JZF7yOjEQAW6hE/w9jBfV5rqFcGhgOMiaTvN3Piuw7M/NX0sdngUHsWL0e20ArG4elKVZ+Q1j63p18A0K4wKBNG3l5ipJSBcgBXIAMD9Nef/cBhjxzWoxyKSwgS4GIhsj2v/ojwCN47StELacqCgtBvSJNezTUkfjuxqyrXQ8znitnqaXfX9QaD1HyozMy2nTNX455a5Lu2OPlawbj3tR3TxvcddAc91hbRTZeB6LQuU+VFJJJSVZN5ZCbcVgZdTAqM74b65zSJi0t3HaOoy/oB3hkIyKQQ8shORYg0qTZEZmzYauuPCURMIVhYN5+m56r9XVOt1In4Jpry/YNRz73R0FGots0bCZN5h3HIrdN5JLNHUfWQ5v/affxpNdQkheMUnl0Z/fdT2eqtHJfux/3gUA+If7CBuxfGmgtQyiEUzhNIxJJAVrFG8AU7Yni9hVNkZ9mUf3vWZ3C1fVp7+VyrvYOg5CqSJtOqozOZ7UTNjQdd8qBSPFhVCcfqHt5QTJGnNF4SiL0OSuSsspTXwrSBTJWOOcaq+ou85KXBch6cpfff1X8Td/TUW9gVDGxZ77oA0UDMaDplYGWSt03BqMLAyCQXlbax+p6tVTs1r3MX0Tpbd7WQ2nVsmS0HaEXmxUnk0NfLe8dng8rrzp5t71RvFqHXwr7RylshQqqaSSkqwLSwGF04CDXPjwOa045QGUJLilZKBAkZXXNVMr1qSapI59uAFoHpfgAPvSEwYRN1kVf90GzjeLx/DoWcsFFSXQM7HfYDRVvqS8bjG5j/5emCcnMJijc3/mPa9Fl0IJuOuuBwEAzf019QPrV9N4/8PPfgAA8Id/+EsaCAzP0A1K04Mer4LESkTrFDWPGIU1en3Rrqm+s6ELRCpqkWMGwcho3EACiEXkLI9CWJyF2yL2fHQJbYwCJSZR6rJRqAQmGsfgwGOWB9ojIeVBdvM6ZjhiLGSus1HXWQg8MQ0GM22Klx2oi4PPtcXAxUKkF2YIFB3XPJYOJpx0nuUl/SNzF2sQbgjR2I1TBt0r6Rg1zhN20zqGfSZS8cBFaqiMBYejviOKUUJW61mIPpu3fM33sXES5yzrYlEwlkyhfhqjzh1363wzNOpaeC28JNCYBiUSDIBbyUngmBeaUZc5/oyFzJ7ciPqiM38ZTYs8BpKp8g2SzMFo1hGXSLdqIh+hv4f84s/scUQnne2049U3U6Zh131XYmY3HeMfTr0SADC4OkW0TLfj848TJmH/dsIwBKl7aUOfbck6nARAC4AEJP2XnDa4v+UYQeYWDXlBTOHcHlkAjJdVGHcVjHUvlT6kck7jYUoE2QhAaA+1TDkJ1vIf8v0cjGK0OVAn3bvrQYZF7rQS8ku5EasaaGwHEh0m2RwvYbCZjj/7qHu55XlKGK6aTAJ2mf+eZiyClIV7zNQqmcOixCvMKSkFaXWgOUNvvnSRPrgyA3OaWcGkuc/IuvJonltB9UZD92wOuVWiX84u05h2rG6XwHjcOwP89Cylch8qqaSSkqwLSwEWCIcWjSjDBC+10krr4IzHCWbW/k7x84I888w8bcPO5czhwKiJ7TeQlVVbufRCV+AkLczFpI5X3eklOFfrWe1PUWPilRO354hWSXtMstWzPKJA2WhjjkXuQNOgGBQaR2KYG8iiiL9OrcL2P30JAGBDUaDOqcaUCV6C3Ksn8EtttWkMf0pqKnB4A0m3mgKuMaqHWnRsxfKdcx8CoR8TbMLIIGuXU5FSiIYRgIZ8xxZJ3UJ6dCi/YTNX3kNTKyMbg8BiwPn+pM5tAL3cqAQXUxsqTmGJe7+1DBPeIMcdr+S+HHuoL0c6YbT+JWL+yrjn5q9xgi0u/n/acoFaIZspms5y0OCzPI45sKFDarvJJujicluPq0HCxHMf2GoLpDWgAYbM5hx67oY26/FQmuIGCnZGCv/ORSpLoZJKKinJurAUjCX/dphFWOK0k/hhkk4M8toaIlFY4zr6iPKp58hFm7FzK2izou40nJZOr1oYW4aUFbFDPooIrVnWMEil3wP7zs0Fu6bmYMv9gQYfF+ZI87e307Xcecv38eQypR+fPUFQu8mJAcLP0N9Rn7HyHCxKJgL1EaX6ERY6bqmBKCIvHiAWjsRVQ4DJkNFY4srC2UCboPpByzUksWJ9BR55biiRLVtCN9If0P1V7XiKS/H5fO+KzFW2WkY7ZRKMtIRqBFwHpenaAH1Wjcts3m2MVvUcMQccUz5W2yR4zfSTAIDHU7IUgkRIZnyt7fx7qZwFPwfNk47kZ8jVselEpNblcHvC88el/s0C7Zi2Sek0DjU1cB13ncUq1bnCvC0W2miDUctFn0fr5tJ68R1JQa4h3T0HqSyFSiqppCTrwlKwhrTTareJzjytrtJbsNak5TmPa64CUXzRyFFyS0orT4ISbBVwK2rtuDunwIGNddz6oiVqqVVtNk5yAXit2ln68wEap7nHw8htE6294Rs0gGdfSdbBW1+zSy0FaZCbZCEG19OYNn+DfqfprcUCSYe1qpJ6ODCXAJWK2FkxjnuCPoMUmDhMG1NOb41mHFhHMwguQaM8EIq1j102QfzrojBrLDiFo1s3p5IOhYGeM+twhN+nI5fYhvRWsNBKWOmgtDBqaX9JsRhOZhPYGi/Clxjl+ATg9cwMPK4CSYPWjAdrl9Qr9FOsh84RGnd/LkT3GrrA1iR3/DrOlsJ0qt2/jq8QAq+2aDTmJHOWTLoenzJXcg/Ttssm+IQ6DtbuMhKSCVPw2nnI+lgUImCwySBLQqxwmawEZ0Lm7MtazjRW9yE3COq0sWDMfNTIkElbOX4Qk01cht2PtW5BUnFpywUafXYbeWDkJkp6MfLcCglC1ZasK5gSrMGiXdOQY/pRmu7/vPQmvPlOwif86CYCR/zN46/AhsuI9DF/SFKRks93zVpckMlxNAoDFLwXepylefJgoYtBMmF0nzMSqvBzJcErP3imDWYlmAiHgJRtyv5j3SIii07Yd7USegwbIJc+H4pr4EUnC7Dao4lsc1lyWoTaSm6aSSgLG6DPN6SmDE10jKENsDmmnHL/dVxw943Omus0uav9EFyAmPlFbFDnFy9jPEGYuED3aEgHifmabG6w2KeDDQ7SorDhiEXMrqGkjk0OiKcsQe0R16GEI6dk/LRlMsn7c3PbqOdeY8GzoHbui0PlPlRSSSUlOZu2cR8A8BMATlhrr+dtfwzgrQASAPsA/JK1dom/ezeAXwGQA/hNa+0Xnu8cRQwMNxZotBK1ENrMbzfZIrNsWHOQQenCU8SFVkkatijyzAMvienXc1S3YiGIlo17rl7AqhnuNKho3OYJZzEIWEhSa8m00SCRmKd53aHRRLtK2qp53ODezxJoSbTmra/Zg71/QUEwGY8g3PKa0QCj4easpnD0ceomha56UdqgT+7P+do8JugJp+X9XhdyKNH84VDmyiEWZV6yjtP8qmm9cQBAMDTOk+MnLa27wGTooQCFwi0Xc41TmHEr1daAUpY8yiLlr1zhLrKzUU/rIRKPtxGgnhDy9zuufggA8NkvvRYF3ytpRBvANdd1bdrE9HJpZ7n/RQxNpUbc9m54qWNFWd7HQeQnuXJ2UJSeD4AsAQl4yvMhcxz1vdoIHkbWAtJJZrdmwJRvwcn9TM6jJf3ZWAofBPDmsW1fBHC9tfZGAE8AeDcAGGOuBfAOANfxb95jjBknn66kkkrWsZxNL8n7jTE7xrbd6/33WwB+hv/+SQB/a60dAXjaGPMUgFcB+Obznie0yLxmsUJsKTXpecPz+QWw5C1p4tsVaajbRZtJzXt9IfBAPQ7urD0PymxeAFyKR2DPWRswAqlmDZNMWwUhiZZfuYzw7wCwchU5jY2jDMKZKVB0aNv0RvJx9/7FNVi8jn47/+2x64SzbByBq1EtJh2rjLVocxCsscA0ZTNSbeqIW3XOcjenmcex4Or6yzGCIoJL/fZdEFK5EqQuInP/16Ajaz+pDqRxOwjxeD8JDUYmoW6T2ALaQ4U89yL6XPaIIKQ6cjJwEWEhdZ2PV9zxJV49xpkBeBqX/fdo4DpyiQVnrANb7dxIvUUOBJR+tLsm0WHW72hQ6DGdtUHHyhtAwkawgKLilXLgGwAyJmlNpl2/Cj8WprEPHuMaGrcXID+MQOMvA/go/70NtEiIHOJtP1BMAUS9AOko0oKoSebjazHufSV0kxQy7XbWzrVtnEgQ5yi4xFUWgHiBnsz6olXTT4JtNkSpFRcNCOhvou+lZFlLrr0uy8M5t+jkHDjSh2lDjtnH5EmngWhuuh8geg0tBv/oMmJw/vDUXZjeLefnl0sCq9Y6vEHsHkh52CSHbUOjD11vM51TXIy8ufY6/VoGLfLyyDm0sMl/SmS6PbdDFg09hqzZuVvYdOFoOBdEH9xhoJkIrWuBK0kOucRZiFiKIsAop0EtJrQYzNW7qHOy3udtBIDpoI8eByGFGn7lMqBFDb+VFZnOV/7UxQmAlca82sIPwDKd46njxOkZPUY71VfKzxgN3J1HgsOjGedC1sfK76OBC1Yr03jdOpIX61C0mgGypa/OSc4r0GiM+X3QfP31Ofz214wxDxpjHsx7vef/QSWVVHJB5JwtBWPMPwYFIN/ALegB4DCAi7zdtvO2NWKtfR+A9wFAY+tFNhwapIMQiZTHciBJyFYG8wWaJwSowAcJrHKJCDlHrZFi1KfLylu0fE7s44BMUXh8jIxQbDozvJBWZDWD0QYue112PQwAqlYTDSMyfckSFgzlkTY8RPu3DkbOPOZhr7yBF7+n27B8XZ84dBMAoH7nSRQfJ21TaM0BX2bmTNYgL1tGAHEQynkkdarpRF9jjJnmQQbYovzlmvZjcKXRNgCyNmttabTTsmuDlZxWLGBcqnPsmvzrRODcDC1R1qpJI8Wg2gvEGKtt4+Tz6HASIbuJS7nXoRUUcIzZipDU5NV3PI1nP7pT50HGo/gOIZYR68ebm7Bw+7cP0cbiWIfnii/Jw7ooDiHzKncp64ysbRUPUl8oYyOKiLEkcMHFolEg4EGJGxtkXtUq5FwXOCVpjHkzgP8NwNustX6d6qcAvMMYUzfGXArgCgDfPufRVVJJJRdczpJgH8gAAAmnSURBVCYl+REArwcwZ4w5BOAPQNmGOoAvGlLV37LW/hNr7feNMf8FwG6QW/Eb1tq1sLLxcxQECgq7Tk1trJHPvdShVf9kewbWBLo/gJLjJKi3ojBKghEuO4AIAAzmA9S4Mk5iC+HIgUWM0r3BBdSk2oz/n1wyQucg+adC2LLUnMbFVxJccvBt6u0w2FRg+rXEnxB/kKjX+lvoWmzTInmCIljJ9aQWTh2dQmMbHW/2cTrngCvk2scswoQuIuemuXls1GeVQCPgAFUSPzCeVhtv+WbOdGeMXdM7QGILeR2IuaFq1rJ6DBcAHvtdZLUgUunyvHvm14tIzEGp4IT6zFoUkqXkcyZZpH0T+nXy6bd1ltHlPN+JlOZWYgvTYQ897iglRCwvnz6IY71L+ZwuNeoIesuatoidJQRJ1eYez8VY/UdeNzqPEiOwgXUBazZm6ksG8Ur5XBJHKEKDEfcuydlCM4lR7oT6aZ4Xr9JSqiPXxMlegJxN9uHnz7D5/T9g/z8C8EcvZBCmoCh/MDLY2iTz7oomvWQdxivsnZ1HzlTpanamxkWCpXS6CBSzICKmVNhzJdNyg5OGC+iF/F3aNugc4JdPSos5erZ10xKG2ETHld/NjtDi4pcjxI+C6ccNTm/hfpGX0bFmH6VjLNxoMfE07bcUkB25+YYTKL5Gi4dEuRuLzv2QAKPkudOWcQ1olDHZldgaYfX1FodgbBGwoUPwGYXzGveyCiO0h1uQv30qeYE8l/poioy5LP7LJlkKA8fapCL4k9RBtXOGhJumxRTjAjJmbMmKQFvwCcNzl9+uk2YSGyPKOqwUtG0uXlVcgPJe1t1zIQFPWfyC1LlMMo9F5FyP8QXRFz1PalxQ0yP5UWZxwSLwvA/nvPJsnUeD+lIZL+G7CoKoPZ+mMBWisZJKKinJuqh9kPZlpgCmGBgg6SRBqU11BujyMqtmXABYrnPQnH4thx1y+e0MNzLdR5cZpB660MMphBx0FKRfEbk8cu8i+q7zDP3/xCOb0JHuzdIr4XQde08Q6eJrX/8YAODR91+PUY9U3CRHXSRohAJYupqOK4HMydoIR36KrKTa31Piun0s1zFKQZQfCFRkJVza0dUy0Cen80kbStDMO4YrFaZPn+8PfIwoGzPtAQ+paMfrshQJ6WtP0a5Zu1BXQQKx0cCzTqRkWiyHyHrqmz6SJMKCIfUbM4FNFBTa0HWao33yLOU2wJAjr8rfaFKsXEF/CzdnbcWRmiiw0qOdkzFJqXqQoZRmpPFDr308LZhMQy0msQ5GM577wPtLafZoLtemNCET9sSrARrcRyTuOxiq9vkYQ2mei1SWQiWVVFKSdWEpoKCAXm0pUHZewaoLOi3Lg3J6jX8XTZRhiGGUY8R49M5e0g4SDzDWan2DiAR+gDLOfMRtxgRQsngTqdKZXaGu9lKumk4Z1X7fvPd6AMDoFZkGy7Tmgesn6guuPVn7KG070r1Y0ZPLlwtoiG5PNHCAH1GaRezSlNqSPPCuYWy5L2pwqVzj9heNKL5omMJD7rEm74n2NK7MWayDzCCwVr+nc1n3nc84zNu0ivIMjWs1MilsyoVDq8Z1ugd5FiJqliF7p4dtbGlx3IAnXNKV9SDVAOMst6nPYfCq2/YCAL4VXQUAmDgQOLo9sUo0VWv1IvwGr+Ogr8AjOwk9yj/ZJvvJPQsTVyotVkY6ydaSZ5mJ9dU6ZtVCkCB4ERutn9DS8POQylKopJJKSmIc7uilk0kza281b3iph1FJJf9dy5fsPQ9Za1/xfPtVlkIllVRSkmpRqKSSSkqyLtwHY8xJEG/uqZd6LADmUI3Dl2ocZfn/8zgusdZufL6d1sWiAADGmAfPxt+pxlGNoxrHizuOyn2opJJKSlItCpVUUklJ1tOi8L6XegAs1TjKUo2jLP/dj2PdxBQqqaSS9SHryVKopJJK1oGsi0XBGPNmY8xeY8xTxpjfu0DnvMgY8xVjzG5jzPeNMb/F22eNMV80xjzJnzMXaDyhMea7xpjP8P8vNcY8wHPyUWNM7fmO8UMYw7Qx5h5jzOPGmD3GmNtfivkwxvw235PHjDEfMcY0LtR8GGM+YIw5YYx5zNt2xjkwJP+Bx7TLGHPLizyOP+Z7s8sY81+NYQ5A+u7dPI69xpi7zufcL/miwH0h/hzA3QCuBfDz3D/ixZYMwP9qrb0WwG0AfoPP+3sAvmytvQLAl/n/F0J+C8Ae7///BsCfWmsvB7AIarDzYsufAfh7a+3VAG7i8VzQ+TDGbAPwmwBewc2HQlAvkQs1Hx/E2j4nzzUHd4MoB68A8GsA3vsij+PC9Fux1r6k/wDcDuAL3v/fDeDdL8E4PgngjQD2AtjC27YA2HsBzr0d9LD9GIDPgGr0TgGIzjRHL9IYpgA8DY4zedsv6HyAWgI8C2AWVMX7GQB3Xcj5ALADwGPPNwcA/hOAnz/Tfi/GOMa++ykAf81/l94ZAF8AcPu5nvcltxTgHgKRs+oV8cMUbnbzMgAPANhkrT3KXx0DmHvtxZX/G0SEK5QdGwAsWWuFVOtCzMmlAE4C+Et2Y/7CGNPGBZ4Pa+1hAH8C4CCAowCWATyECz8fvjzXHLyUz+4vA/j8izGO9bAovKRijOkA+DsA/9xau+J/Z2nZfVHTM8YY6dP50It5nrOQCMAtAN5rrX0ZCHZechUu0HzMgDqNXQpgK4A21prRL5lciDl4PjmffitnI+thUTjrXhE/bDHGxKAF4a+ttR/nzceNMVv4+y0ATrzIw3g1gLcZYw4A+FuQC/FnAKaNMUKCcyHm5BCAQ9baB/j/94AWiQs9H3cCeNpae9JamwL4OGiOLvR8+PJcc3DBn12v38o7eYH6oY9jPSwK3wFwBUeXa6CAyade7JMa4qZ/P4A91tp/7331KQDv4r/fBYo1vGhirX23tXa7tXYH6Nrvs9a+E8BX4Hp0XohxHAPwrDHmKt70BhBV/wWdD5DbcJsxpsX3SMZxQedjTJ5rDj4F4Bc5C3EbgGXPzfihywXrt/JiBo1eQEDlLaBo6j4Av3+BzvkakBm4C8Aj/O8tIH/+ywCeBPAlALMXcB5eD+Az/PdOvrFPAfgYgPoFOP/NAB7kOfkEgJmXYj4A/J8AHgfwGIC/AvUYuSDzAeAjoFhGCrKefuW55gAUEP5zfm4fBWVMXsxxPAWKHcjz+h+9/X+fx7EXwN3nc+4K0VhJJZWUZD24D5VUUsk6kmpRqKSSSkpSLQqVVFJJSapFoZJKKilJtShUUkklJakWhUoqqaQk1aJQSSWVlKRaFCqppJKS/H90wwWud6ZAWQAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "f=np.zeros([5,5])\n", "f[4,4]=1\n", "r=ims[:,:,0]\n", "\n", "r2=cv2.filter2D(r,-1,f,borderType=cv2.BORDER_CONSTANT)\n", "\n", "plt.imshow(r2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## apply Canny edge detector on r" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.image.AxesImage at 0x7f472fdea890>" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "edge=cv2.Canny(r,100,200)\n", "\n", "plt.imshow(edge,cmap='gray')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Video capture from webcam" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import cv2\n", "import platform\n", "\n", "cap=cv2.VideoCapture(0)\n", "\n", "while (True):\n", " \n", " ret,frame=cap.read()\n", " \n", " cv2.namedWindow(\"camera\",cv2.WND_PROP_FULLSCREEN)\n", " cv2.setWindowProperty(\"camera\",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)\n", " cv2.imshow('camera',frame)\n", " \n", " if cv2.waitKey(1) &0xFF == ord('q'): # press q or ESC to quit. You probably need to hit the screen first\n", " break\n", "\n", " \n", "cap.release()\n", "cv2.destroyAllWindows()\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Edge detection with webcam input" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import cv2\n", "import platform\n", "\n", "cap=cv2.VideoCapture(0)\n", "\n", "while (True):\n", " \n", " ret,frame=cap.read()\n", " \n", " cv2.namedWindow(\"camera\",cv2.WND_PROP_FULLSCREEN)\n", " cv2.setWindowProperty(\"camera\",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)\n", " frame=cv2.cvtColor(frame,cv2.COLOR_RGB2GRAY)\n", " frame=cv2.Canny(frame,50,60)\n", "\n", " cv2.imshow('camera',frame)\n", " \n", " if cv2.waitKey(1) &0xFF == ord('q'): # press q or ESC to quit. You probably need to hit the screen first\n", " break\n", "\n", " \n", "cap.release()\n", "cv2.destroyAllWindows()\n", " " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting opencv-python\n", "\u001b[?25l Downloading https://files.pythonhosted.org/packages/77/f5/49f034f8d109efcf9b7e98fbc051878b83b2f02a1c73f92bbd37f317288e/opencv-python-4.4.0.42.tar.gz (88.9MB)\n", "\u001b[K 100% |████████████████████████████████| 88.9MB 602kB/s ta 0:00:011 8% |██▋ | 7.3MB 3.8MB/s eta 0:00:22 12% |███▉ | 10.7MB 3.0MB/s eta 0:00:27 30% |█████████▉ | 27.3MB 6.2MB/s eta 0:00:10 39% |████████████▌ | 34.9MB 12.3MB/s eta 0:00:05 46% |██████████████▊ | 41.0MB 2.3MB/s eta 0:00:22 86% |███████████████████████████▊ | 77.1MB 5.1MB/s eta 0:00:03 87% |████████████████████████████ | 77.7MB 2.2MB/s eta 0:00:06\n", "\u001b[?25h Installing build dependencies ... \u001b[?25ldone\n", "\u001b[?25hRequirement already satisfied: numpy>=1.13.1 in /home/phsamuel/p3/lib/python3.5/site-packages (from opencv-python) (1.14.2)\n", "Building wheels for collected packages: opencv-python\n", " Running setup.py bdist_wheel for opencv-python ... \u001b[?25ldone\n", "\u001b[?25h Stored in directory: /home/phsamuel/.cache/pip/wheels/62/23/5f/bb6a7cb3d2e5520cff9ebea1a3d6542b4932cc8ccb342435d2\n", "Successfully built opencv-python\n", "Installing collected packages: opencv-python\n", "Successfully installed opencv-python-4.4.0.42\n", "\u001b[33mYou are using pip version 18.1, however version 20.3.4 is available.\n", "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n" ] } ], "source": [ "!pip install opencv-python" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 2 }
import pickle
a={'hello':'world'}
with open('dummy.pickle','wb') as fpt:
pickle.dump(a,fpt)
with open('dummy.pickle','rb') as fpt:
b = pickle.load(fpt)
b
{'hello': 'world'}
from scipy.io import savemat,loadmat # save and load matlab mat files
x=range(10)
mdic={'x':x}
savemat('dummy.mat',mdic)
mdic2=loadmat('dummy.mat')
mdic2
{'__header__': b'MATLAB 5.0 MAT-file Platform: posix, Created on: Fri Jan 28 14:06:12 2022', '__version__': '1.0', '__globals__': [], 'x': array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])}
from matplotlib import pyplot as plt
%matplotlib inline
plt.figure(figsize=(10,10))
plt.plot(range(10))
plt.xlabel('dummy')
plt.title('hello')
Text(0.5, 1.0, 'hello')