def test_vb_init(self):
coll = pv.from_id('67a16de1-7baf-44bf-a779-2bf97a37c3bd')
count = 10
partition = [70, 20, 10]
vb = VedaBase.from_path(self.h5,
mltype=coll.mltype,
klasses=coll.classes,
image_shape=coll.imshape,
image_dtype=coll.dtype)
urlgen = coll.gen_sample_ids(count=count)
token = coll.conn.access_token
build_vedabase(vb,
urlgen,
partition,
count,
token,
label_threads=1,
image_threads=10)
vb.flush()
self.assertEqual(type(vb), VedaBase)
self.assertEqual(vb.mltype, coll.mltype)
self.assertEqual(vb.classes, coll.classes)
self.assertEqual(vb.image_shape, coll.imshape)
self.assertEqual(vb.image_dtype, coll.dtype)
#with self.assertRaises(FrameworkNotSupported):
# vb.framework = 'foo'
#self.assertEqual(vb.framework, self.framework)
#vb.framework = 'Keras'
#self.assertEqual(vb.framework, 'Keras')
self.assertEqual(len(vb), 0)
self.assertEqual(type(vb.train), WrappedDataNode)
self.assertEqual(type(vb.test), WrappedDataNode)
self.assertEqual(type(vb.validate), WrappedDataNode)
def test_store(self):
vcp = pv.from_id(self.id)
self.assertRaises(ValueError, pv.store, vcp)
#self.assertRaises(HTTPError, pv.store, dataset_id = self.id, filename = self.h5)
self.assertTrue(
isinstance(
pv.store(dataset_id=self.id, filename=self.h5, count=10),
VedaBase))
def test_vedabase(self):
vc = pv.from_id(self.id)
vb = pv.store(self.h5, dataset_id=self.id, count=10)
self.assertTrue(isinstance(vb, VedaBase))
self.assertEqual(len(vb.train), 7)
#self.assertEqual(len(list(vb.train)), 7)
self.assertEqual(len(list(vb.train[:])), 7)
self.assertEqual(vb.image_shape, vc.imshape)
self.assertEqual(vb.mltype, vc.mltype)
def test_model_create(self):
vc = pv.from_id(self.vc_id)
archive = 'dummy.tar.gz'
model = Model('CHELM SEG PREDICTIONS',
archive=archive,
library="keras",
training_set=vc,
imshape=(256, 256, 3),
mltype='segmentation',
channels_last=True)
self.assertIsInstance(model, Model)
# public properties
self.assertTrue(model.channels_last)
self.assertEqual(model.library, "keras")
self.assertEqual(vc.bounds, model.bounds)
self.assertEqual(model.imshape, (256, 256, 3))
self.assertEqual(vc.mltype, model.mltype)
def test_datapoint_fetch(self):
vc_id = '67a16de1-7baf-44bf-a779-2bf97a37c3bd'
dp_id = '7f30b1ef-1622-41ca-ab21-9b66d23d87fc'
vc = pv.from_id(vc_id)
dp = vc.fetch_sample_from_id(dp_id)
self.assertTrue(isinstance(dp, DataSampleClient))
# public properties
self.assertEqual(vc.id, vc_id)
self.assertEqual(dp.mltype, vc.mltype)
self.assertEqual(dp.dtype, vc.dtype) # should inherit
self.assertEqual(dp.dataset_id, vc_id)
self.assertEqual(dp.tile_coords, [965, 167])
# geo interface
self.assertEqual(dp.bounds, [
-97.7503432361732, 30.268178825289258, -97.74957054483292,
30.26895151662954
])
self.assertTrue(isinstance(shape(vc), Polygon))
def test_vb_init(self):
coll = pv.from_id('67a16de1-7baf-44bf-a779-2bf97a37c3bd')
count = 10
partition=[70,20,10]
vb = VedaBase.from_path(self.h5,
mltype=coll.mltype,
classes=coll.classes,
image_shape=coll.imshape,
image_dtype=coll.dtype)
self.assertEqual(type(vb), VedaBase)
self.assertEqual(vb.mltype.name, coll.mltype)
self.assertEqual(vb.classes, coll.classes)
self.assertEqual(vb.image_shape, coll.imshape)
self.assertEqual(vb.image_dtype, coll.dtype)
#with self.assertRaises(FrameworkNotSupported):
# vb.framework = 'foo'
#self.assertEqual(vb.framework, self.framework)
#vb.framework = 'Keras'
#self.assertEqual(vb.framework, 'Keras')
self.assertEqual(type(vb.train), H5SampleArray)
self.assertEqual(type(vb.test), H5SampleArray)
self.assertEqual(type(vb.validate), H5SampleArray)
def setUp(self):
self.vc = pv.from_id(VC_ID)
def test_open(self):
vcp = pv.from_id(self.id)
#self.assertRaises(ValueError, pv.store, vcp)
#self.assertRaises(HTTPError, pv.store, dataset_id = self.id, filename = self.h5)
self.assertTrue(isinstance(pv.open(self.id), VedaStream))
def test_from_id(self):
vcp = pv.from_id(self.id)
self.assertTrue(isinstance(pv.from_id(self.id), VedaCollectionProxy))