def test_style_predict(): from photonix.classifiers.style.model import StyleModel model = StyleModel() snow = str(Path(__file__).parent / 'photos' / 'snow.jpg') result = model.predict(snow) assert len(result) == 1 assert result[0][0] == 'serene' assert '{0:.3f}'.format(result[0][1]) == '0.962'
def test_style_predict(): from photonix.classifiers.style.model import StyleModel model = StyleModel() snow = str(Path(__file__).parent / 'photos' / 'snow.jpg') result = model.predict(snow) assert len(result) == 1 assert result[0][0] == 'serene' assert '{0:.3f}'.format(result[0][1]) == '0.962' # Check that there is no error when running with non-RGB image cmyk = str(Path(__file__).parent / 'photos' / 'cmyk.tif') result = model.predict(cmyk) assert result == None
def test_downloading(tmpdir): from photonix.classifiers.style.model import StyleModel model_dir = tmpdir start = time.mktime(datetime.now().timetuple()) model = StyleModel(lock_name=None, model_dir=model_dir) graph_path = str(Path(model_dir) / 'style' / 'graph.pb') assert os.stat(graph_path).st_size > 1024 * 10 * 10 assert os.stat(graph_path).st_mtime > start with open(str(Path(model_dir) / 'style' / 'version.txt')) as f: content = f.read() assert content.strip() == str(model.version)