def test_loader_errors(self):
# check that images with no dark images raise ValueError
with self.assertRaises(ValueError):
images = {'temporal': {0: {0.1: ""}},
'spatial': {0: {0.1: ""}}}
l = LoadImageData(images)
# check that one image for temporal instead of 2 raise valueerror
with self.assertRaises(ValueError):
images = {'temporal': {0: {0.0: ""}},
'spatial': {0: {0.0: ""}}}
l = LoadImageData(images)
# Check that an image that does not exist raise an IOError
with self.assertRaises(IOError):
images = {'temporal': {0: {0.0: ["."], 0.1: ["."]}},
'spatial': {0: {0.0: ["."], 0.1: ["."]}}}
l = LoadImageData(images)
def _init(self):
# Create dataset to load
dataset = DatasetGenerator(height=self._height,
width=self._width,
bit_depth=self._bit_depth,
L=self._L,
steps=self._steps)
descriptor_path = dataset.descriptor_path
# create the parser
parser = ParseEmvaDescriptorFile(descriptor_path)
# create loader
loader = LoadImageData(parser.images)
return dataset, parser, loader
def _init(pixel_area=0, **kwargs):
# create dataset
dataset = DatasetGenerator(**kwargs)
# parse dataset
parser = ParseEmvaDescriptorFile(dataset.descriptor_path)
# load image data
loader = LoadImageData(parser.images)
# create data
data = Data1288(loader.data)
# Make results object
px = pixel_area
if pixel_area == 0:
px = dataset.cam.pixel_area
results = Results1288(data.data, pixel_area=px)
return dataset, parser, loader, data, results
def _init(self):
# create dataset
dataset = DatasetGenerator(height=self._height,
width=self._width,
bit_depth=self._bit_depth,
L=self._L,
steps=self._steps,
radiance_min=self._radiance_min,
exposure_max=self._exposure_max)
# parse dataset
parser = ParseEmvaDescriptorFile(dataset.descriptor_path)
# load images
loader = LoadImageData(parser.images)
# create data
data = Data1288(loader.data)
return dataset, parser, loader, data
def __init__(self, fname):
parser = ParseEmvaDescriptorFile(fname)
imgs = LoadImageData(parser.images)
dat = Data1288(imgs.data)
self._results = Results1288(dat.data)