def __init__(self,
top_shape,
front_shape,
rgb_shape,
debug_mode=False,
log_tag=None,
weigths_dir=None):
# anchors
self.top_stride = None
self.num_class = data.preprocess.num_class # incude background
if cfg.OBJ_TYPE == 'ped':
ratios = np.array([1], dtype=np.float32)
elif cfg.OBJ_TYPE == 'car':
ratios = np.array([0.5, 1, 2], dtype=np.float32)
scales = np.array([1, 2, 3], dtype=np.float32)
self.bases = make_bases(
base_size=16,
ratios=ratios, #aspet ratio
scales=scales)
# output dir, etc
utilfile.makedirs(cfg.CHECKPOINT_DIR)
self.log_msg = utilfile.Logger(cfg.LOG_DIR + '/log.txt', mode='a')
self.track_log = utilfile.Logger(cfg.LOG_DIR + '/tracking_log.txt',
mode='a')
# creat sesssion
self.config = tf.ConfigProto()
self.config.gpu_options.allow_growth = True
self.sess = tf.Session(config=self.config)
self.debug_mode = debug_mode
if self.debug_mode:
print('\n\nstart debug mode\n\n')
self.sess = tf_debug.LocalCLIDebugWrapperSession(self.sess)
self.sess.add_tensor_filter('has_inf_or_nan',
tf_debug.has_inf_or_nan)
self.use_pretrain_weights = []
self.build_net(top_shape, front_shape, rgb_shape)
#init subnet
self.tag = log_tag
self.ckpt_dir = os.path.join(
cfg.CHECKPOINT_DIR,
log_tag) if weigths_dir == None else weigths_dir
self.subnet_rpn = Net(prefix='MV3D',
scope_name=mv3d_net.top_view_rpn_name,
checkpoint_dir=self.ckpt_dir)
self.subnet_imfeatrue = Net(prefix='MV3D',
scope_name=mv3d_net.imfeature_net_name,
checkpoint_dir=self.ckpt_dir)
self.subnet_fusion = Net(prefix='MV3D',
scope_name=mv3d_net.fusion_net_name,
checkpoint_dir=self.ckpt_dir)
# set anchor boxes
self.top_stride = self.net['top_feature_stride']
top_feature_shape = get_top_feature_shape(top_shape, self.top_stride)
self.top_view_anchors, self.anchors_inside_inds = make_anchors(
self.bases, self.top_stride, top_shape[0:2],
top_feature_shape[0:2])
self.anchors_inside_inds = np.arange(
0, len(self.top_view_anchors), dtype=np.int32) # use all #<todo>
self.log_subdir = None
self.top_image = None
self.time_str = None
self.frame_info = None
self.batch_top_inds = None
self.batch_top_labels = None
self.batch_top_pos_inds = None
self.batch_top_targets = None
self.batch_proposals = None
self.batch_proposal_scores = None
self.batch_gt_top_boxes = None
self.batch_gt_labels = None
# default_summary_writer
self.default_summary_writer = None
# about tensorboard.
self.tb_dir = log_tag if log_tag != None else strftime(
"%Y_%m_%d_%H_%M", localtime())
self.log_iou_range = [
range(0, 2),
range(2, 30),
range(30, 60),
range(60, 100)
]
self.raw_img = raw_data_from_mapping.Image()
def __init__(self,
top_shape,
front_shape,
rgb_shape,
debug_mode=False,
log_tag=None,
weigths_dir=None):
# anchors
self.top_stride = None
self.num_class = 2 # incude background
ratios = np.array([0.5, 1, 2], dtype=np.float32)
scales = np.array([1, 2, 3], dtype=np.float32)
self.bases = make_bases(
base_size=16,
ratios=ratios, #aspet ratio
scales=scales)
# output dir, etc
utilfile.makedirs(cfg.CHECKPOINT_DIR)
self.log_msg = utilfile.Logger(cfg.LOG_DIR + '/log.txt', mode='a')
self.track_log = utilfile.Logger(cfg.LOG_DIR + '/tracking_log.txt',
mode='a')
# creat sesssion
self.sess = tf.Session()
self.use_pretrain_weights = []
self.build_net(top_shape, front_shape, rgb_shape)
#init subnet
self.tag = log_tag
self.ckpt_dir = os.path.join(
cfg.CHECKPOINT_DIR,
log_tag) if weigths_dir == None else weigths_dir
self.subnet_rpn = Net(prefix='MV3D',
scope_name=mv3d_net.top_view_rpn_name,
checkpoint_dir=self.ckpt_dir)
self.subnet_imfeatrue = Net(prefix='MV3D',
scope_name=mv3d_net.imfeature_net_name,
checkpoint_dir=self.ckpt_dir)
self.subnet_fusion = Net(prefix='MV3D',
scope_name=mv3d_net.fusion_net_name,
checkpoint_dir=self.ckpt_dir)
# set anchor boxes
self.top_stride = self.net['top_feature_stride']
top_feature_shape = get_top_feature_shape(top_shape, self.top_stride)
self.top_view_anchors, self.anchors_inside_inds = make_anchors(
self.bases, self.top_stride, top_shape[0:2],
top_feature_shape[0:2])
self.anchors_inside_inds = np.arange(
0, len(self.top_view_anchors), dtype=np.int32) # use all #<todo>
self.log_subdir = None
self.top_image = None
self.time_str = None
self.frame_info = None
self.batch_top_inds = None
self.batch_top_labels = None
self.batch_top_pos_inds = None
self.batch_top_targets = None
self.batch_proposals = None
self.batch_proposal_scores = None
self.batch_gt_top_boxes = None
self.batch_gt_labels = None
# default_summary_writer
self.default_summary_writer = None
self.debug_mode = debug_mode
# about tensorboard.
self.tb_dir = log_tag if log_tag != None else strftime(
"%Y_%m_%d_%H_%M", localtime())