def test_addfromfile_pca(self, bigimageset_rw, imgfile):
"Adding a file should still work after reducing the set"
sample = bigimageset_rw.sample()
extractor = PCAFeatures.create(sample)
bigimageset_rw.add_feature_set(extractor)
prev_len = len(bigimageset_rw)
bigimageset_rw.add_from_file(imgfile)
assert(len(bigimageset_rw) == prev_len+1)
assert(len(bigimageset_rw.feature_sets['pca']) == prev_len+1)
def test_reduce_fewimg(self, bigimageset_rw):
"More pixels than images should lead to less components than images"
prev_length = len(bigimageset_rw)
sample = bigimageset_rw.sample()
extractor = PCAFeatures.create(sample)
bigimageset_rw.add_feature_set(extractor)
img0 = bigimageset_rw.get_pixels_at(0, 'pca') # FIXME pca is hardcoded
assert(len(bigimageset_rw) == prev_length)
assert('pca' in bigimageset_rw.feature_sets)
assert(len(img0) <= len(bigimageset_rw) < IMG_SIZE*IMG_SIZE)
def test_reduce_smallsample(self, bigimageset_rw):
"More images than sample size"
prev_length = len(bigimageset_rw)
sample_size = prev_length / 2
sample = bigimageset_rw.sample(sample_size)
extractor = PCAFeatures.create(sample, None)
bigimageset_rw.add_feature_set(extractor)
img0 = bigimageset_rw.get_pixels_at(0, 'pca') # FIXME pca is hardcoded
assert(len(bigimageset_rw) == prev_length)
assert('pca' in bigimageset_rw.feature_sets)
assert(len(img0) == sample_size)
def test_reduce_manyimg(self, bigimageset_rw, tmpdir_factory):
"""More images than pixels but less than sample size
won't reduce the dimensionality"""
images = [make_filedict(t, True) for t in range(6000, 30000, 60)]
for img in images:
img['name'] = imgfile(tmpdir_factory, img['img_time'])
bigimageset_rw._add_image(**img)
bigimageset_rw.fileh.flush()
prev_length = len(bigimageset_rw)
sample = bigimageset_rw.sample(450)
extractor = PCAFeatures.create(sample, None)
bigimageset_rw.add_feature_set(extractor)
img0 = bigimageset_rw.get_pixels_at(0, 'pca') # FIXME pca is hardcoded
assert(len(bigimageset_rw) == prev_length)
assert(len(img0) == IMG_SIZE*IMG_SIZE)
def task(webcam_id, feat_type):
with self.open_dataset(webcam_id) as dataset:
if feat_type == 'raw':
img_shape = dataset.imgset.img_shape
w, h = settings.DEFAULT_FEATURES_SIZE
feat_shape = h, w, 3
extractor = RawFeatures(feat_shape, img_shape)
elif feat_type == 'pca':
logger.info("Starting computation of a PCM model")
sample = dataset.imgset.sample()
extractor = PCAFeatures.create(sample)
else: # rbm
logger.info("Starting computation of a RBM model")
sample = dataset.imgset.sample()
extractor = RBMFeatures.create(sample)
if extractor.name in dataset.imgset.feature_sets:
raise ValueError("The feature set %s already exists" %
extractor.name)
logger.info("Adding a new set of features %s to webcam %s",
feat_type, webcam_id)
dataset.imgset.add_feature_set(extractor)
def test_pixelsat_seq_pca(self, imageset):
"Read reduced pixels from a tuple of indices"
sample = imageset.sample()
extractor = PCAFeatures.create(sample)
fset = imageset.add_feature_set(extractor)
self.test_pixelsat_seq(imageset, fset.name)
