update lanenet eval tools

WeixinGithubJiang · Jun 15, 2020 · de1ce80 · de1ce80
1 parent f1d12fe
commit de1ce80
Showing 1 changed file with 11 additions and 10 deletions.
diff --git a/tools/evaluate_lanenet_on_tusimple.py b/tools/evaluate_lanenet_on_tusimple.py
@@ -15,16 +15,17 @@
 import time
 
 import cv2
-import glog as log
 import numpy as np
 import tensorflow as tf
 import tqdm
 
-from config import global_config
 from lanenet_model import lanenet
 from lanenet_model import lanenet_postprocess
+from local_utils.config_utils import parse_config_utils
+from local_utils.log_util import init_logger
 
-CFG = global_config.cfg
+CFG = parse_config_utils.lanenet_cfg
+LOG = init_logger.get_logger(log_file_name_prefix='lanenet_eval')
 
 
 def init_args():
@@ -40,7 +41,7 @@ def init_args():
     return parser.parse_args()
 
 
-def test_lanenet_batch(src_dir, weights_path, save_dir):
+def eval_lanenet(src_dir, weights_path, save_dir):
     """
 
     :param src_dir:
@@ -54,17 +55,17 @@ def test_lanenet_batch(src_dir, weights_path, save_dir):
 
     input_tensor = tf.placeholder(dtype=tf.float32, shape=[1, 256, 512, 3], name='input_tensor')
 
-    net = lanenet.LaneNet(phase='test', net_flag='vgg')
-    binary_seg_ret, instance_seg_ret = net.inference(input_tensor=input_tensor, name='lanenet_model')
+    net = lanenet.LaneNet(phase='test')
+    binary_seg_ret, instance_seg_ret = net.inference(input_tensor=input_tensor, name='LaneNet')
 
     postprocessor = lanenet_postprocess.LaneNetPostProcessor()
 
     saver = tf.train.Saver()
 
     # Set sess configuration
     sess_config = tf.ConfigProto()
-    sess_config.gpu_options.per_process_gpu_memory_fraction = CFG.TEST.GPU_MEMORY_FRACTION
-    sess_config.gpu_options.allow_growth = CFG.TRAIN.TF_ALLOW_GROWTH
+    sess_config.gpu_options.per_process_gpu_memory_fraction = CFG.GPU.GPU_MEMORY_FRACTION
+    sess_config.gpu_options.allow_growth = CFG.GPU.TF_ALLOW_GROWTH
     sess_config.gpu_options.allocator_type = 'BFC'
 
     sess = tf.Session(config=sess_config)
@@ -96,7 +97,7 @@ def test_lanenet_batch(src_dir, weights_path, save_dir):
             )
 
             if index % 100 == 0:
-                log.info('Mean inference time every single image: {:.5f}s'.format(np.mean(avg_time_cost)))
+                LOG.info('Mean inference time every single image: {:.5f}s'.format(np.mean(avg_time_cost)))
                 avg_time_cost.clear()
 
             input_image_dir = ops.split(image_path.split('clips')[1])[0][1:]
@@ -119,7 +120,7 @@ def test_lanenet_batch(src_dir, weights_path, save_dir):
     # init args
     args = init_args()
 
-    test_lanenet_batch(
+    eval_lanenet(
         src_dir=args.image_dir,
         weights_path=args.weights_path,
         save_dir=args.save_dir