/
_Img.py
executable file
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/
_Img.py
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#!/usr/bin/env python
"""
This is one of my first python files ever (its first version was probably created around 2009)... And it shows.
Also, it was created with an old version of opencv, before the introduction of "cv2.so".
I sometimes update/improve it incrementally by replacing the cv stuff with the cv2 alternatives.
Update (June 9, 2016): Turns out OpenCV 3.* no longer has cv.py (but still has the cv2.so). Started adjusting the code.
Author: Oren Freifeld
Email: freifeld@csail.mit.edu
"""
import numpy as np
import cv2
from pylab import plt
from of.utils import *
#from pyvision.essentials import *
#from pyvision.core.cvdo import Rect
from _imshow import imshow as _imshow
_NamedWindow = cv2.namedWindow
from is_opencv_legacy import is_opencv_legacy
if is_opencv_legacy:
from cv2 import cv
_lcviplimage = cv.iplimage
_lcvGetMat = cv.GetMat
_lcvGetImage = cv.GetImage
_lcvCreateMat = cv.CreateMat
_lcvmat = cv.cvmat
_lcvfromarray = cv.fromarray
_lasarray = np.asarray
_lzeros = np.zeros
_lzeros_like = np.zeros_like
_lempty = np.empty
_lempty_like = np.empty_like
class Img(np.ndarray):
"""An image class. Derived from np.ndarray.
In addition to std constructs, can also be initialized by Img(filename)
Version 0.0"""
def __new__(cls, input_array, info=None , read_grayscale = False):
#----- enabling construction from a filename -------------
if type(input_array) in [str,np.string_]: # Assume it is a filename.
input_array = cls.imread(input_array , read_grayscale = read_grayscale)
elif is_opencv_legacy:
#----- enabling construction from an cv.iplimage----------
if type(input_array) == _lcviplimage:
input_array = cls.ipl2np(input_array)
#----- enabling construction from an cv.cvmat-------------
elif type(input_array) == _lcvmat:
input_array = cls.cvmat2np(input_array)
# Verify we have a numpy ndarray.
if not isinstance(input_array,np.ndarray):
print "Expected isinstance(input_array,np.ndarray) == True"
raise TypeError(type(input_array))
# Now follow the example in python's online doc.
# Input array is an already formed ndarray instance
# We first cast to be our class type
obj = _lasarray(input_array).view(cls)
# obj = _lasarray(input_array).view(cls).astype(input_array.dtype)
# TODO: I don't really use info at the moment. I keep it as a reminder.
# add the new attribute to the created instance
obj.info = info
obj.rows = obj.shape[0]
obj.cols = obj.shape[1]
# Finally, we must return the newly created object:
return obj
def __array_finalize__(self, obj):
# This is important - otherwise only the explicit construction would work.
# See PEP.
if obj is None:
return # in this case, we don't need to return.
# TODO: again, I keep info as a reimnder.
self.info = getattr(obj, 'info', None)
def imshow_matplotlib(self,*args,**kwargs):
plt.imshow( self,*args,interpolation = 'nearest',**kwargs )
def imshow(self,winname = None ,
option = 'opencv',
float_min_val = 0.0,
float_max_val = 1.0,
divide_by_max=False):
"""A thin wrapper to imshow"""
if option in ['pylab','matplotlib']:
self.imshow_matplotlib()
return
elif not option == 'opencv':
raise NotImplementedError
if winname is None:
winname = 'winname'
if not isinstance(winname,str):
raise TypeError(type(winname))
cv2.namedWindow(winname,cv2.WINDOW_NORMAL)
_imshow(self,winname,
option,float_min_val,float_max_val,divide_by_max)
return self
@staticmethod
def waitKey(delay = None):
"""Delay in miliseconds"""
if delay == None:
return cv2.waitKey()
else:
return cv2.waitKey(delay)
@staticmethod
def WaitKey(delay = None):
if delay == None:
return cv.WaitKey()
else:
return cv.WaitKey(delay)
def toggle_landscape_vs_portrait(self ):
print """TODO: need first to check if L of P, and then treat accordingly"""
raise NotImplementedError
if self.ndim == 3:
axes = [1,0,2]
return np.ndarray.transpose(self,*axes)[:, ::-1,:]
elif self.ndim == 2:
return np.ndarray.transpose(self)[ ::-1,:]
else:
raise ShapeError(self.shape)
def imwrite(self,filename, override = False,create_dir_if_needed = False):
if 'raw' in filename.lower():
raise RawDataError(filename)
if not override:
FilesDirs.raise_if_file_already_exists(filename)
try:
dirname = os.path.dirname(filename)
FilesDirs.raise_if_dir_does_not_exist(dirname)
except DirDoesNotExistError:
if create_dir_if_needed:
FilesDirs.mkdirs_if_needed(dirname)
else:
raise
if self.dtype == bool:
ret = cv2.imwrite(filename , 255*self.astype(np.uint8))
else:
## from of.utils import ipshell
## ipshell('s')
## 2/0
ret = cv2.imwrite(filename , self )
if not ret:
raise CvImwriteError(filename)
def query_frame_inplace(self,capture):
# # Convert to cvmat is enough.
# img_ipl = cv.QueryFrame(capture)
# if img_ipl != None: # i.e. still cpaturing.
# self[:] = _lcvGetMat( img_ipl )
# else:
# return 1
raise NotImplementedError("PLease swtich from cv to cv2")
def imread_inplace( self, filename_fullpath , read_grayscale = False):
FilesDirs.raise_if_file_does_not_exist(filename_fullpath)
try:
if not read_grayscale:
self[:] = cv2.imread(filename_fullpath)
else:
self[:] = cv2.imread(filename_fullpath,cv.CV_LOAD_IMAGE_GRAYSCALE)
except:
raise
# raise CvImreadError(filename_fullpath )
raise CvImreadError(filename_fullpath)
@staticmethod
def imread(filename_fullpath , option = 'opencv',read_grayscale = False):
"""A thin wrapper to imread. This is a static method."""
FilesDirs.raise_if_file_does_not_exist(filename_fullpath)
if not option == 'opencv':
print """TODO: add the pylab option"""
raise NotImplementedError
try:
if not read_grayscale:
return cv2.imread(filename_fullpath)
else:
return cv2.imread(filename_fullpath,cv.CV_LOAD_IMAGE_GRAYSCALE)
except:
raise CvImreadError(filename_fullpath )
@staticmethod
def ipl2np(img_ipl):
img_cvmat = _lcvGetMat(img_ipl) # ipl2cvmat
return Img.cvmat2np(img_cvmat)
@staticmethod
def cvmat2np(img_cvmat):
return _lasarray(img_cvmat)
@staticmethod
def cvmat2ipl(img_cvmat):
return _lcvGetImage(img_cvmat)
@staticmethod
def img2cv(img):
return _lcvfromarray(img.copy())
@staticmethod
def img2ipl(img):
return Img.cvmat2ipl(Img.img2cv(img))
@staticmethod
def get_bb(mask):
if mask.ndim != 2: raise NotImplementedError
nz = mask.nonzero()
if len(nz[0])==0 or len(nz[1])==0:
raise ValueError
# xmin = min(nz[1])
# ymin = min(nz[0])
# xmax = max(nz[1])
# ymax = max(nz[0])
xmin = nz[1].min()
ymin = nz[0].min()
xmax = nz[1].max()
ymax = nz[0].max()
rect = Rect(xmin,ymin,xmax-xmin+1,ymax-ymin+1,thickness = 1)
return rect
def distance_transform(self,dt = None):
"""self is the bw. opencv expects uint8 and zeros values for the mask.
So negate by 255-self. Note: assumes nonzeros are 255."""
if self.dtype != np.uint8:
raise TypeError(self.dtype)
if dt == None:
# raise Warning('It is (much) better to pass dst as an arguemnet')
# ipshell('hi')
dt = cv2.distanceTransform((False == self).astype(np.uint8),
cv.CV_DIST_L2,5)
return Img(dt)
else:
if dt.dtype != np.float32:
raise TypeError(dt.dtype)
## cv2.distanceTransform((False == self).astype(np.uint8),
## cv.CV_DIST_L2,5,dst = dt)
#cpp and numpy.
#cv2.distanceTransform(255-self,cv.CV_DIST_L2,5,doer.dt1)
# c. More than twices fast. Maybe it's just the flags? Need to check.
cv.DistTransform(_lcvfromarray(255-self),_lcvfromarray(dt),cv.CV_DIST_L2,mask_size=3)
def signed_distance_transform(self ,rect = None,
sdt = None ,
two_dt_bufs = None):
"""self is the bw"""
if sdt != None and not isinstance(sdt,Img):
raise TypeError(type(sdt))
if two_dt_bufs == None:
two_dt_bufs = ( _lempty(self.shape,np.float32),
_lempty(self.shape,np.float32))
if rect == None:
self.distance_transform( two_dt_bufs[0] )
(255 - self).distance_transform( two_dt_bufs[1])
if sdt == None:
sdt = two_dt_bufs[0] - two_dt_bufs[1]
return sdt
else: # inplace
sdt[:] = two_dt_bufs[0] - two_dt_bufs[1]
return
else:
r = rect
if sdt == None:
raise NotImplementedError
else: # inplace
1/0
sdt[r.ymin:r.ymax,r.xmin:r.xmax] = (
(self[r.ymin:r.ymax,
r.xmin:r.xmax]).distance_transform() -
(False == self[r.ymin:r.ymax,
r.xmin:r.xmax]).distance_transform())
return
def get_diagonal_length(self):
return norm(self.shape[0:2])
def imshow_signed_distance_transform(self,winname):
"""self is the sdt"""
sdt = self
_sdt = sdt.copy()
_sdt[(np.absolute(_sdt)<=1).nonzero()] = 0
_sdt.imshow(winname = winname,
float_min_val = -_sdt.get_diagonal_length() / 5,
float_max_val = _sdt.get_diagonal_length() / 5 )
def imresize(self,factor , verbose = False):
if factor != 1.0:
sz = (int(float(self.shape[0]) * factor),
int(float(self.shape[1]) * factor))
if verbose:
print 'factor = {0}. sz = {1}'.format(factor,sz)
# input_cvmat = _lcvfromarray(self)
# output_cvmat = _lcvCreateMat(sz[0],sz[1] , input_cvmat.type)
# cv.Resize(input_cvmat,output_cvmat)
# Img(output_cvmat)
# out = Img( cv2.resize(self,(sz[0],sz[1])))
# I swear it used to be (height,width)...
# But now it seems to be (width,height)
out = Img( cv2.resize(self,(sz[1],sz[0])))
return out
else:
return self.copy()
def pyrdown(self,dst = None):
if self.shape[0] % 2 !=0 or self.shape[1] % 2 !=0:
raise ShapeError(self.shape)
## sz_new = (self.shape[1]/2,self.shape[0]/2)
## img_cvmat = _lcvfromarray(self.copy())
## img_ipl = Img.cvmat2ipl(_lcvfromarray(img_cvmat))
## out = cv.CreateImage(sz_new,img_ipl.depth, img_ipl.nChannels)
##
## cv.PyrDown(img_ipl, out)
## return Img(out)
shape_new = [s/2 for s in self.shape[0:2]]
if self.ndim == 3: shape_new.append(self.shape[2])
if dst == None:
dst = Img(_lempty(shape_new,self.dtype))
cv.pyrDown(self,dst)
return dst
else:
if not isinstance(dst,Img):
raise TypeError(type(dst))
cv.pyrDown(self,dst)
def bgr2hsv(self):
"""Assumes BGR ordering"""
return Img(cv.cvtColor(self,cv.CV_BGR2HSV))
if __name__ == '__main__':
cv2.destroyAllWindows()
img = Img(np.random.rand(100,100,3))
img.imshow('image')