def test_train_test_split(self):
client = Client(api_token="57c60ade109be36ef1a1c89f56247109fa448741")
client.checkout_project(
project_token="4b003477-3b31-4f74-8952-8a9dc879b0ec")
client.create_network(network_name="test_creation_network_0")
client.dl_annotations()
client.train_test_split(prop=0.7)
self.assertEqual(len(client.index_url),
len(client.dict_annotations["images"]))
self.assertEqual(len(client.train_list), len(client.train_list_id))
self.assertEqual(len(client.eval_list), len(client.eval_list_id))
def test_dl_annotations(self):
client = Client(api_token="57c60ade109be36ef1a1c89f56247109fa448741")
client.checkout_project(
project_token="4b003477-3b31-4f74-8952-8a9dc879b0ec")
client.dl_annotations()
self.assertTrue(len(client.dict_annotations.keys()) != 0)
def test_create_dataset(self):
client = Client(api_token="57c60ade109be36ef1a1c89f56247109fa448741")
ds_id = client.create_dataset(dataset_name="test_dataset_0")
self.assertTrue(isinstance(ds_id, str))
with self.assertRaises(ValueError):
client = Client(
api_token="57c60ade109be36ef1a1c89f56247109fa448741")
ds_id = client.create_dataset(dataset_name="test_dataset_0")
def test_upload_and_create_dataset(self):
client = Client(api_token="57c60ade109be36ef1a1c89f56247109fa448741")
client = client.create_and_upload_dataset(
dataset_name="test_dataset_1", path_to_images="test_images/")
if __name__ == '__main__':
#unittest.main()
client = Client(api_token="57c60ade109be36ef1a1c89f56247109fa448741")
client.checkout_project(
project_token="d8e65668-9e18-421e-966c-7daa8d7c7497")
model_name = "ssd_base"
client.checkout_network(model_name)
client.dl_annotations()
client.dl_pictures()
client.train_test_split()
client.generate_labelmap()
a = client.tf_vars_generator(client.label_map, annotation_type="rectangle")
x = next(a)
print(x[:4])