def render(self, tree, size=None, window_name="Render"):
obs = tree.root.data["obs"]
img = obs[-1] if type(obs) is list else obs
if size: img = cv2.resize(img, size, interpolation=cv2.INTER_AREA)
if len(img.shape) == 2: img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
display_image_cv2(window_name, img)
def render_tree(self, tree, size=None, window_name="Render tree"):
get_img = lambda obs: obs[-1] if type(obs) is list else obs
root_img = get_img(tree.root.data["obs"])
image = root_img / 255.0
for child in tree.root.children:
for node in child.breadth_first():
image += 0.4 / 255.0 * (get_img(node.data["obs"])-root_img)
display_image_cv2(window_name, cv2.resize(image, size, interpolation=cv2.INTER_AREA))
def render_tree(self, abstract_tree, size=None, window_name="Render tree"):
get_img = lambda obs: obs[-1] if type(obs) is list else obs
root = abstract_tree.root.low_level_tree.root
root_img = get_img(root.data["obs"])
image = root_img/255.0
for child in root.children:
image += self._get_image_from_subtree(child, background=root_img)
if size:
image = cv2.resize(image, size, interpolation=cv2.INTER_AREA)
display_image_cv2(window_name, image)
def render_downsampled(self, tree, max_pix_value, size=None, window_name="Render downsampled"):
if "downsampled_image" in tree.root.low_level_tree.root.data:
img = tree.root.low_level_tree.root.data["downsampled_image"]
display_image_cv2(window_name, img/float(max_pix_value))
def render_downsampled(self, tree, max_pix_value, size=None, window_name="Render downsampled"):
if "downsampled_image" in tree.root.data:
img = tree.root.data["downsampled_image"]
if size: img = cv2.resize(img, size, interpolation=cv2.INTER_AREA)
if len(img.shape) == 2: img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
display_image_cv2(window_name, img/float(max_pix_value))