def test_print_result(self):
device = FakeDevice(SourceType.IMAGE, 'dataset/png/')
# device = FakeDevice(SourceType.IMAGE, '/media/zis/Dados/dev/datasets/putkk.poznan/Dataset_1_Kin_2')
algorithms = []
algorithms.append(
RGBDSegmentation(
Parameter(Segmentation.GRAPH_CANNY,
os.getcwd() + '/results/graph_canny/',
resize=(640, 360),
fix_proportion=False)))
#algorithms.append(RGBDSegmentation(Parameter(Segmentation.RGBD_SALIENCY, os.getcwd() + '/results/rgbd_saliency/', resize=(324, 324))))
#algorithms.append(RGBDSegmentation(Parameter(Segmentation.FCN_TENSORFLOW, os.getcwd() + '/results/fcn_tensorflow/', resize=(224, 224))))
#algorithms.append(RGBDSegmentation(Parameter(Segmentation.FUSENET, os.getcwd() + '/results/fusenet/', resize=(224, 224))))
directory_rgb = device.datasetPath + 'rgb/'
directory_depth = device.datasetPath + 'depth/'
for algorithm in algorithms:
Logger.info('############# Testing algorithm ' +
str(algorithm.parameter.segmentation))
for i in range(0, 10):
frame = RGBDFrame(
RGBFrame(directory_rgb, 'rgb_' + format(i, '05') + '.png'),
DepthFrame(directory_depth,
'depth_' + format(i, '05') + '.png'))
algorithm.process(frame)
algorithm.write_results()
algorithm.finish()
#break
algorithm.release()
break
def test_print_result(self):
device = FakeDevice(SourceType.IMAGE, 'dataset/png/')
parameter = Parameter(Segmentation.FUSENET,
os.getcwd() + '/results/fusenet/',
resize=(224, 224))
seg = RGBDSegmentation(parameter)
directory_rgb = device.datasetPath + 'rgb/'
directory_depth = device.datasetPath + 'depth/'
frame = RGBDFrame(RGBFrame(directory_rgb, 'inp_5.png'),
DepthFrame(directory_depth, 'gt_5.png'))
seg.process(frame)
#seg.print_results()
seg.finish()
frame = RGBDFrame(RGBFrame(directory_rgb, 'inp_6.png'),
DepthFrame(directory_depth, 'gt_6.png'))
seg.process(frame)
#seg.print_results()
seg.finish()
frame = RGBDFrame(RGBFrame(directory_rgb, '8.png'),
DepthFrame(directory_depth, '8.png'))
seg.process(frame)
#seg.print_results()
seg.finish()
def test_write_result(self):
device = FakeDevice(SourceType.IMAGE, 'dataset/png/')
parameter = Parameter(Segmentation.RGBD_SALIENCY, os.getcwd()+'/results/rgbd_saliency/')
seg = RGBDSegmentation(parameter)
directory_rgb = device.datasetPath + 'rgb/'
directory_depth = device.datasetPath + 'depth/'
frame = RGBDFrame(RGBFrame(directory_rgb, 'demo1.png'), DepthFrame(directory_depth, 'demo1.png'))
seg.process(frame)
seg.write_results()
seg.finish()
frame = RGBDFrame(RGBFrame(directory_rgb, 'demo3.png'), DepthFrame(directory_depth, 'demo3.png'))
seg.process(frame)
seg.write_results()
seg.finish()
def test_write_result(self):
device = FakeDevice(SourceType.IMAGE, 'dataset/png/')
parameter = Parameter(Segmentation.GRAPH_CANNY,
os.getcwd() + '/results/graph_canny/',
resize=(640, 360))
seg = RGBDSegmentation(parameter)
directory_rgb = device.datasetPath + 'rgb/'
directory_depth = device.datasetPath + 'depth/'
for i in range(0, 10):
frame = RGBDFrame(
RGBFrame(directory_rgb, 'rgb_' + format(i, '05') + '.png'),
DepthFrame(directory_depth,
'depth_' + format(i, '05') + '.png'))
seg.process(frame)
seg.write_results()
seg.finish()