def py_load_pickle(path, max_value):
depthmap, targets = pickle.load(open(path.numpy(), "rb"))
depthmap = preprocess_depthmap(depthmap)
depthmap = depthmap / max_value
depthmap = tf.image.resize(
depthmap, (CONFIG.IMAGE_TARGET_HEIGHT, CONFIG.IMAGE_TARGET_WIDTH))
targets = preprocess_targets(targets, CONFIG.TARGET_INDEXES)
return depthmap, targets
def py_load_pickle(path, max_value=7.5):
path_ = path if isinstance(path, str) else path.numpy()
depthmap, targets = pickle.load(open(path_, "rb"))
depthmap = preprocess_depthmap(depthmap)
depthmap = depthmap / max_value
depthmap = tf.image.resize(depthmap,
(IMAGE_TARGET_HEIGHT, IMAGE_TARGET_WIDTH))
targets = preprocess_targets(targets, TARGET_INDEXES)
return depthmap, targets
def py_load_pickle(path, max_value):
rgbd_tuple, targets = pickle.load(open(path.numpy(), "rb"))
rgb = rgbd_tuple[0] # shape: (240, 180, 3)
if getattr(CONFIG, 'DATASET_IS_BGR', False):
rgb = rgb[:, :, ::-1] # BGR -> RGB
depthmap = rgbd_tuple[1] # shape: (240, 180)
rgb = preprocess_depthmap(rgb)
rgb = rgb / 255.
depthmap = preprocess_depthmap(depthmap)
depthmap = depthmap / max_value
depthmap = tf.expand_dims(depthmap, -1) # shape: (240, 180, 1)
rgbd = tf.concat([rgb, depthmap], axis=2)
rgbd = tf.image.resize(
rgbd, (CONFIG.IMAGE_TARGET_HEIGHT, CONFIG.IMAGE_TARGET_WIDTH))
targets = preprocess_targets(targets, CONFIG.TARGET_INDEXES)
return rgbd, targets