def start(dset=None, frame_num=0): main.initialize() if not FOR_REAL: if dset is None: dataset.load_random_dataset() else: dataset.load_dataset(dset) while dataset.frame_num < frame_num: dataset.advance() name = dset name = os.path.split(name)[1] custom = os.path.join('data/sets/', name, 'gt.txt') if os.path.exists(custom): # Try dataset directory first fname = custom else: import re # Fall back on generic ground truth file match = re.match('.*_z(\d)m_(.*)', name) number = int(match.groups()[0]) fname = 'data/experiments/gt/gt%d.txt' % number with open(fname) as f: GT = grid.gt2grid(f.read()) grid.initialize_with_groundtruth(GT) else: config.load('data/newest_calibration') opennpy.align_depth_to_rgb() dataset.setup_opencl()
def run_normals(): global ds ds = [] try: shutil.rmtree(out_path) except: pass os.mkdir(out_path) for i in range(1): dataset.load_random_dataset() dataset.advance() name = 'dataset_%s' % str(i) d = dict(name=name) folder = os.path.join(out_path, name) os.mkdir(folder) depthL = dataset.depthL.astype('f') pylab.figure(0) pylab.clf() pylab.imshow(depthL) pylab.savefig(os.path.join(folder,'depth.jpg')) dt = timeit.timeit(lambda: normals.normals_numpy(depthL), number=1) d['numpy'] = dt n,w = normals.normals_numpy(depthL) pylab.clf() show_normals(n, w) pylab.savefig(os.path.join(folder,'normals_numpy.jpg')) dt = timeit.timeit(lambda: normals.normals_c(depthL), number=1) d['c'] = dt n,w = normals.normals_c(depthL) pylab.clf() show_normals(n, w) pylab.savefig(os.path.join(folder,'normals_c.jpg')) rect = ((0,0),(640,480)) mask = np.zeros((480,640),'bool') mask[1:-1,1:-1] = 1 normals.opencl.set_rect(rect, ((0,0),(0,0))) dt = timeit.timeit(lambda: normals.normals_opencl(depthL, mask, rect).wait(), number=1) d['opencl'] = dt nw,_ = normals.opencl.get_normals() n,w = nw[:,:,:3], nw[:,:,3] pylab.clf() show_normals(n,w) pylab.savefig(os.path.join(folder,'normals_opencl.jpg')) ds.append(d)
def start(dset=None, frame_num=0): if not FOR_REAL: if dset is None: dataset.load_random_dataset() else: dataset.load_dataset(dset) while dataset.frame_num < frame_num: dataset.advance() else: config.load('data/newest_calibration') dataset.setup_opencl()
def start(dset=None, frame_num=0): main.initialize() if not FOR_REAL: if dset is None: dataset.load_random_dataset() else: dataset.load_dataset(dset) while dataset.frame_num < frame_num: dataset.advance() else: config.load('data/newest_calibration') opennpy.align_depth_to_rgb() dataset.setup_opencl()
def start(dset=None, frame_num=0): if not FOR_REAL: if dset is None: dataset.load_random_dataset() else: dataset.load_dataset(dset) while dataset.frame_num < frame_num: dataset.advance() else: config.load("data/newest_calibration") dataset.setup_opencl() global R_correct if "R_correct" in globals(): del R_correct
def start(dset=None, frame_num=0): main.initialize() #with open('data/experiments/collab/2011.txt') as f: global target_model with open('data/experiments/collab/block.txt') as f: target_model = grid.gt2grid(f.read()) #grid.initialize_with_groundtruth(GT) if not FOR_REAL: if dset is None: dataset.load_random_dataset() else: dataset.load_dataset(dset) while dataset.frame_num < frame_num: dataset.advance() else: config.load('data/newest_calibration') opennpy.align_depth_to_rgb() dataset.setup_opencl()
def run_calib(): global ds ds = [] try: shutil.rmtree(out_path) except: pass os.mkdir(out_path) for i in range(1): dataset.load_random_dataset() table_calibration.newest_folder = dataset.current_path name = 'dataset_%s' % str(i) d = dict(name=name) folder = os.path.join(out_path, name) os.mkdir(folder) dt = timeit.timeit(lambda: table_calibration.finish_cube_calib(), number=1) d['dt'] = dt depthL, depthR = table_calibration.depthL, table_calibration.depthR bgL, bgR = config.bgL, config.bgR for depth, side, bg in (depthL, 'left', bgL), (depthR, 'right', bgR): pylab.figure(0) pylab.clf() pylab.imshow(depth) pylab.savefig(os.path.join(folder, 'depth_%s.jpg' % side)) pylab.clf() pylab.imshow(bg['bgHi']) pylab.savefig(os.path.join(folder, 'bghi_%s.jpg' % side)) pylab.imshow(bg['bgLo']) pylab.savefig(os.path.join(folder, 'bglo_%s.jpg' % side)) ds.append(d)
def run_calib(): global ds ds = [] try: shutil.rmtree(out_path) except: pass os.mkdir(out_path) for i in range(1): dataset.load_random_dataset() table_calibration.newest_folder = dataset.current_path name = "dataset_%s" % str(i) d = dict(name=name) folder = os.path.join(out_path, name) os.mkdir(folder) dt = timeit.timeit(lambda: table_calibration.finish_cube_calib(), number=1) d["dt"] = dt depthL, depthR = table_calibration.depthL, table_calibration.depthR bgL, bgR = config.bgL, config.bgR for depth, side, bg in (depthL, "left", bgL), (depthR, "right", bgR): pylab.figure(0) pylab.clf() pylab.imshow(depth) pylab.savefig(os.path.join(folder, "depth_%s.jpg" % side)) pylab.clf() pylab.imshow(bg["bgHi"]) pylab.savefig(os.path.join(folder, "bghi_%s.jpg" % side)) pylab.imshow(bg["bgLo"]) pylab.savefig(os.path.join(folder, "bglo_%s.jpg" % side)) ds.append(d)
def test_tablecalib(): dataset.load_random_dataset() dataset.advance() table_calibration.finish_table_calib()
def test_dataset(): dataset.load_random_dataset()
def once(): dataset.advance() depthL, depthR = dataset.depthL, dataset.depthR maskL, rectL = preprocess.threshold_and_mask(depthL, config.bgL) maskR, rectR = preprocess.threshold_and_mask(depthR, config.bgR) show_mask('maskL', maskL.astype('f'), rectL) show_mask('maskR', maskR.astype('f'), rectR) pylab.waitforbuttonpress(0.01) def go(): while 1: once() def show_backgrounds(): pylab.figure(1) pylab.imshow(config.bgL['bgHi']) pylab.draw() pylab.figure(2) pylab.clf() pylab.imshow(config.bgR['bgHi']) pylab.draw() if __name__ == "__main__": dataset.load_random_dataset() go()
def test_tablecalib(): dataset.load_random_dataset() dataset.advance()
def once(): dataset.advance() depthL, depthR = dataset.depthL, dataset.depthR maskL, rectL = preprocess.threshold_and_mask(depthL, config.bgL) maskR, rectR = preprocess.threshold_and_mask(depthR, config.bgR) show_mask("maskL", maskL.astype("f"), rectL) show_mask("maskR", maskR.astype("f"), rectR) pylab.waitforbuttonpress(0.01) def go(): while 1: once() def show_backgrounds(): pylab.figure(1) pylab.imshow(config.bgL["bgHi"]) pylab.draw() pylab.figure(2) pylab.clf() pylab.imshow(config.bgR["bgHi"]) pylab.draw() if __name__ == "__main__": dataset.load_random_dataset() go()