def extract_dynamic_texture(colors, states): """ extract dynamic texture of given frame. three frames are given, (i-1)-th, i-th, (i+1)-th, and they are 3ch color image. convert them into gray-scale first, then extract dynamic texture. It returns feature of i-th frame. :param colors: 3ch color image :param states: states == step :return: float64 image [-1,1] """ grays = [] for i in range(states): gray = cv2.cvtColor(colors[i], cv2.COLOR_RGB2GRAY) grays.append(gray) size = grays[0].size shape = grays[0].shape length = len(grays) data = np.zeros((size, length)) # size of image, number of images for i in range(len(grays)): data[:, i] = grays[i].reshape(-1) lds = LinearDS(states, False, False) # number of data lds.suboptimalSysID(data) for i in range(states): a = lds._Chat[:, i].reshape(shape) grays.append(a) return lds._Chat[:, 1].reshape(shape)
def test_ldsMartinDistance(): """Test Martin distance computation for LDS's (5 states). Config: 5 states (observation centering - default). """ fileA = os.path.join(TESTBASE, "data/data1.txt") fileB = os.path.join(TESTBASE, "data/data2.txt") # load data files dataA, _ = loadDataFromASCIIFile(fileA) dataB, _ = loadDataFromASCIIFile(fileB) ldsA = LinearDS(5, False, False) ldsB = LinearDS(5, False, False) # estimate LDS's ldsA.suboptimalSysID(dataA) ldsB.suboptimalSysID(dataB) # compute distances A<->A, A<->B dAA = ldsMartinDistance(ldsA, ldsA, 20) dAB = ldsMartinDistance(ldsA, ldsB, 20) truth = np.genfromtxt(os.path.join(TESTBASE, "data/ldsMartinDistanceData1Data2.txt")) np.testing.assert_almost_equal(dAB, truth, 2) np.testing.assert_almost_equal(dAA, 0, 2)
def test_LinearDS_suboptimalSysID(): """Test LinearDS system identification. """ dataFile = os.path.join(TESTBASE, "data/data1.txt") data, _ = loadDataFromASCIIFile(dataFile) lds = LinearDS(5, False, False) lds.suboptimalSysID(data) baseLDSFile = os.path.join(TESTBASE, "data/data1-dt-5c-center.pkl") baseLDS = pickle.load(open(baseLDSFile)) _, err = LinearDS.stateSpaceMap(baseLDS, lds) assert np.allclose(err, 0.0) == True
def test_LinearDS_suboptimalSysID(): """Test LinearDS system identification. """ dataFile = os.path.join(TESTBASE, "data/data1.txt") data, _ = loadDataFromASCIIFile(dataFile) lds = LinearDS(5, False, False) lds.suboptimalSysID(data) baseLDSFile = os.path.join(TESTBASE, "data/data1-dt-5c-center.pkl") baseLDS = pickle.load(open(baseLDSFile)) err = ldsMartinDistance(lds, baseLDS, N=20) np.testing.assert_almost_equal(err, 0, 2)
def main(argv=None): if argv is None: argv = sys.argv parser = OptionParser(add_help_option=False) parser.add_option("-p", dest="pFile") parser.add_option("-i", dest="iFile") parser.add_option("-t", dest="iType") parser.add_option("-o", dest="oFile") parser.add_option("-n", dest="nStates", type="int", default=+5) parser.add_option("-m", dest="doMovie", type="int", default=-1) parser.add_option("-a", dest="svdRand", action="store_true", default=False) parser.add_option("-e", dest="doEstim", action="store_true", default=False) parser.add_option("-s", dest="doSynth", action="store_true", default=False) parser.add_option("-h", dest="shoHelp", action="store_true", default=False) parser.add_option("-v", dest="verbose", action="store_true", default=False) opt, args = parser.parse_args() if opt.shoHelp: usage() dataMat = None dataSiz = None try: if opt.iType == 'vFile': (dataMat, dataSiz) = dsutil.loadDataFromVideoFile(opt.iFile) elif opt.iType == 'aFile': (dataMat, dataSiz) = dsutil.loadDataFromASCIIFile(opt.iFile) elif opt.iType == 'lFile': (dataMat, dataSiz) = dsutil.loadDataFromIListFile(opt.iFile) else: msg.fail("Unsupported file type : %s", opt.iType) return -1 except Exception as e: dsinfo.fail(e) return -1 try: # try loading the DT model if not opt.pFile is None: with open(opt.pFile) as fid: dsinfo.info('trying to load model %s' % opt.pFile) dt = pickle.load(fid) # run estimation if opt.doEstim: if not opt.pFile is None: dsinfo.fail('re-estimation attempt detected!') return -1 dt = LinearDS(opt.nStates, approx=opt.svdRand, verbose=opt.verbose) dt.suboptimalSysID(dataMat) # synthesize output if opt.doSynth: dataSyn, _ = dt.synthesize(tau=50, mode='s') # show a movie of the synthesis result if opt.doMovie > 0: if opt.doSynth: dsutil.showMovie(dataSyn, dataSiz, fps=opt.doMovie) # write DT model to file if not opt.oFile is None: dsinfo.info('writing model to %s' % opt.oFile) with open(opt.oFile, 'w') as fid: pickle.dump(dt, fid) # catch pyds exceptions except ErrorDS as e: dsinfo.fail(e) return -1
def main(argv=None): if argv is None: argv = sys.argv parser = OptionParser(add_help_option=False) parser.add_option("-p", dest="pFile") parser.add_option("-i", dest="iFile") parser.add_option("-t", dest="iType") parser.add_option("-o", dest="oFile") parser.add_option("-n", dest="nStates", type="int", default=+5) parser.add_option("-m", dest="doMovie", type="int", default=-1) parser.add_option("-a", dest="svdRand", action="store_true", default=False) parser.add_option("-e", dest="doEstim", action="store_true", default=False) parser.add_option("-s", dest="doSynth", action="store_true", default=False) parser.add_option("-h", dest="shoHelp", action="store_true", default=False) parser.add_option("-v", dest="verbose", action="store_true", default=False) opt, args = parser.parse_args() if opt.shoHelp: usage() dataMat = None dataSiz = None try: if opt.iType == 'vFile': (dataMat, dataSiz) = dsutil.loadDataFromVideoFile(opt.iFile) elif opt.iType == 'aFile': (dataMat, dataSiz) = dsutil.loadDataFromASCIIFile(opt.iFile) elif opt.iType == 'lFile': (dataMat, dataSiz) = dsutil.loadDataFromIListFile(opt.iFile) elif opt.iType == 'mFile': (dataMat, dataSiz) = dsutil.loadDataFromVolumeFile(opt.iFile) else: msg.fail("Unsupported file type : %s", opt.iType) return -1 except Exception as e: dsinfo.fail(e) return -1 try: # try loading the DT model if not opt.pFile is None: with open(opt.pFile) as fid: dsinfo.info('trying to load model %s' % opt.pFile) dt = pickle.load(fid) # run estimation if opt.doEstim: if not opt.pFile is None: dsinfo.fail('re-estimation attempt detected!') return -1 dt = LinearDS(opt.nStates, approx=opt.svdRand, verbose=opt.verbose) dt.suboptimalSysID(dataMat) # synthesize output if opt.doSynth: dataSyn, _ = dt.synthesize(tau=50, mode='s') # show a movie of the synthesis result if opt.doMovie > 0: if opt.doSynth: dsutil.showMovie(dataSyn, dataSiz, fps=opt.doMovie) # write DT model to file if not opt.oFile is None: dsinfo.info('writing model to %s' % opt.oFile) with open(opt.oFile, 'w') as fid: pickle.dump(dt, fid) # catch pyds exceptions except ErrorDS as e: dsinfo.fail(e) return -1