def FromImages(tcname, id_discdds, image1, image2, true_plan=None): config = get_current_config() discdds = config.discdds.instance(id_discdds) shape = discdds.get_shape() rgb1 = config.images.instance(image1) image1 = resize(rgb1, shape[1], shape[0]) assert_allclose(image1.shape[:2], shape) rgb2 = config.images.instance(image2) image2 = resize(rgb2, shape[1], shape[0]) assert_allclose(image2.shape[:2], shape) # predict the result y0 = UncertainImage(image1) y1 = UncertainImage(image2) tc = TestCase(id_tc=tcname, id_discdds=id_discdds, y0=y0, y1=y1, true_plan=true_plan) return tc
def ManualMotion(tcname, id_discdds, id_image, planstring): # Get a random plan config = get_current_config() discdds = config.discdds.instance(id_discdds) rgb = config.images.instance(id_image) shape = discdds.get_shape() image1 = resize(rgb, shape[1], shape[0]) assert_allclose(image1.shape[:2], shape) chars = "abcdefghilmnopqrst" char2int = dict([(c, i) for i, c in enumerate(chars)]) plan = tuple(map(char2int.__getitem__, planstring)) # predict the result y0 = UncertainImage(image1) y1 = discdds.predict(y0, plan) tc = TestCase(id_tc=tcname, id_discdds=id_discdds, y0=y0, y1=y1, true_plan=plan) return tc