本文整理汇总了Python中utils.logger.Logger.error方法的典型用法代码示例。如果您正苦于以下问题:Python Logger.error方法的具体用法?Python Logger.error怎么用?Python Logger.error使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类utils.logger.Logger
的用法示例。
在下文中一共展示了Logger.error方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: vis_peaks
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def vis_peaks(self, heatmap, ori_img, name='default',
vis_dir=PEAK_DIR, scale_factor=1, img_size=(368, 368)):
vis_dir = os.path.join(self.configer.get('project_dir'), vis_dir)
if not os.path.exists(vis_dir):
Log.error('Dir:{} not exists!'.format(vis_dir))
os.makedirs(vis_dir)
if not isinstance(heatmap, np.ndarray):
if len(heatmap.size()) != 3:
Log.error('Heatmap size is not valid.')
exit(1)
heatmap = heatmap.data.squeeze().cpu().numpy().transpose(1, 2, 0)
if not isinstance(ori_img, np.ndarray):
ori_img = DeNormalize(mean=[128.0, 128.0, 128.0],std=[256.0, 256.0, 256.0])(ori_img)
ori_img = ori_img.data.cpu().squeeze().numpy().transpose(1, 2, 0)
for j in range(self.configer.get('num_keypoints')):
peaks = self.__get_peaks(heatmap[:, :, j].data.cpu().numpy())
image_path = os.path.join(vis_dir, '{}_{}.jpg'.format(name, j))
for peak in peaks:
image = cv2.circle(ori_img, (peak[0], peak[1]),
self.configer.get('vis', 'circle_radius'), (0,255,0), thickness=-1)
image = self.scale_image(image, scale_factor, img_size)
cv2.imwrite(image_path, image)
示例2: seg_net
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def seg_net(self):
key = self.configer.get('network', 'model_name')
if key == 'erf_net':
return ERFNet(self.configer.get('network', 'out_channels'))
else:
Log.error('Model: {} not valid!'.format(key))
exit(1)
示例3: get_vote_loss
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def get_vote_loss(self, key):
if key == 'vote_loss':
return VoteLoss()
else:
Log.error('Vote loss: {} is not valid.'.format(key))
exit(1)
示例4: select_pose_model
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def select_pose_model(self):
key = self.configer.get('method')
if key == 'open_pose':
if self.configer.get('phase') == 'train':
return OpenPose(self.configer)
else:
return OpenPoseTest(self.configer)
elif key == 'conv_pose_machine':
if self.configer.get('phase') == 'train':
return ConvPoseMachine(self.configer)
else:
return ConvPoseMachineTest(self.configer)
elif key == 'associative_embedding':
if self.configer.get('phase') == 'train':
return AssociativeEmbedding(self.configer)
else:
return AssociativeEmbeddingTest(self.configer)
elif key == 'fashion_ai':
if self.configer.get('phase') == 'train':
return FashionAI(self.configer)
else:
return FashionAITest(self.configer)
else:
Log.error('Pose Model: {} is not valid.'.format(key))
exit(1)
示例5: select_det_model
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def select_det_model(self):
key = self.configer.get('method')
if key == 'pose_top_down':
return ConvPoseMachine(self.configer)
else:
Log.error('Det Model: {} is not valid.'.format(key))
示例6: test
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def test(self):
base_dir = os.path.join(self.configer.get('project_dir'),
'val/results/pose', self.configer.get('dataset'), 'test')
if not os.path.exists(base_dir):
os.makedirs(base_dir)
test_img = self.configer.get('test_img')
test_dir = self.configer.get('test_dir')
if test_img is None and test_dir is None:
Log.error('test_img & test_dir not exists.')
exit(1)
if test_img is not None and test_dir is not None:
Log.error('Either test_img or test_dir.')
exit(1)
if test_img is not None:
filename = test_img.rstrip().split('/')[-1]
save_path = os.path.join(base_dir, filename)
self.__test_img(test_img, save_path)
else:
for filename in self.__list_dir(test_dir):
image_path = os.path.join(test_dir, filename)
save_path = os.path.join(base_dir, filename)
self.__test_img(image_path, save_path)
示例7: _validate_building_data
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def _validate_building_data(self, b_dict):
"""
Ensure a dictionary containing building information is actually valid
for updating purposes. The main goal is to validate the presence and
format of b_id and/or l_b_id.
If no b_id is present but a l_b_id is valid, it is set as current b_id,
which ensures the building does not get discarded.
Arguments:
- b_dict: a dictionary representing a building
Return value: True if data is valid, False otherwise
"""
b_id = b_dict.get("b_id", "")
l_b_id = b_dict.get("l_b_id", "")
if not Building.is_valid_bid(b_id):
if Building.is_valid_bid(l_b_id):
Logger.warning(
"Invalid building id: \"{}\"".format(b_id),
"- legacy id", l_b_id, "will be used instead."
)
b_dict["b_id"] = l_b_id
else:
Logger.error(
"Building discarded:",
"Invalid building id", b_id,
"and no valid legacy id is present"
)
return False
return True
示例8: __test_img
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def __test_img(self, image_path, save_path):
if self.configer.get('dataset') == 'cityscape':
self.__test_cityscape_img(image_path, save_path)
elif self.configer.get('dataset') == 'laneline':
self.__test_laneline_img(image_path, save_path)
else:
Log.error('Dataset: {} is not valid.'.format(self.configer.get('dataset')))
exit(1)
示例9: get_relation_loss
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def get_relation_loss(self, key):
if key == 'embedding_loss':
return EmbeddingLoss(num_keypoints=self.configer.get('data', 'num_keypoints'),
l_vec=self.configer.get('capsule', 'l_vec'))
else:
Log.error('Relation loss: {} is not valid.'.format(key))
exit(1)
示例10: select_seg_model
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def select_seg_model(self):
key = self.configer.get('method')
if key == 'fcn_segmentor':
if self.configer.get('phase') == 'train':
return FCNSegmentor(self.configer)
else:
return FCNSegmentorTest(self.configer)
else:
Log.error('Seg Model: {} is not valid.'.format(key))
示例11: create_submission
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def create_submission(self, test_dir=None):
base_dir = os.path.join(self.configer.get('project_dir'),
'val/results/pose', self.configer.get('dataset'), 'submission')
if not os.path.exists(base_dir):
os.makedirs(base_dir)
if self.configer.get('dataset') == 'coco':
self.__create_coco_submission(test_dir)
else:
Log.error('Dataset: {} is not valid.'.format(self.configer.get('dataset')))
exit(1)
示例12: TestLogger
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
class TestLogger(unittest.TestCase):
def setUp(self):
self.logger = Logger().getLogger(__name__)
def test_log(self):
self.logger.debug("debug")
self.logger.info("info")
self.logger.warn("warn")
self.logger.error("error")
self.logger.critical("critical")
示例13: UtLogger
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
class UtLogger(unittest.TestCase):
def setUp(self):
self.logger = Logger().getLogger("test.utils.UtLogger")
def testLogger(self):
self.logger.debug("1")
self.logger.info("2")
self.logger.warn("3")
self.logger.error("4")
self.logger.critical("5")
示例14: __train
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def __train(self):
"""
Train function of every epoch during train phase.
"""
self.seg_net.train()
start_time = time.time()
# data_tuple: (inputs, heatmap, maskmap, tagmap, num_objects)
for i, data_tuple in enumerate(self.train_loader):
self.data_time.update(time.time() - start_time)
# Change the data type.
if len(data_tuple) < 2:
Log.error('Train Loader Error!')
exit(0)
inputs = Variable(data_tuple[0].cuda(async=True))
targets = Variable(data_tuple[1].cuda(async=True))
# Forward pass.
outputs = self.seg_net(inputs)
# Compute the loss of the train batch & backward.
loss_pixel = self.pixel_loss(outputs, targets)
loss = loss_pixel
self.train_losses.update(loss.data[0], inputs.size(0))
self.optimizer.zero_grad()
loss.backward()
self.optimizer.step()
# Update the vars of the train phase.
self.batch_time.update(time.time() - start_time)
start_time = time.time()
self.iters += 1
# Print the log info & reset the states.
if self.iters % self.configer.get('solver', 'display_iter') == 0:
Log.info('Train Iteration: {0}\t'
'Time {batch_time.sum:.3f}s / {1}iters, ({batch_time.avg:.3f})\t'
'Data load {data_time.sum:.3f}s / {1}iters, ({data_time.avg:3f})\n'
'Learning rate = {2}\n'
'Loss = {loss.val:.8f} (ave = {loss.avg:.8f})\n'.format(
self.iters, self.configer.get('solver', 'display_iter'),
self.lr, batch_time=self.batch_time,
data_time=self.data_time, loss=self.train_losses))
self.batch_time.reset()
self.data_time.reset()
self.train_losses.reset()
# Check to val the current model.
if self.val_loader is not None and \
self.iters % self.configer.get('solver', 'test_interval') == 0:
self.__val()
self.optimizer, self.lr = self.module_utilizer.update_optimizer(self.seg_net, self.iters)
示例15: get_seg_loss
# 需要导入模块: from utils.logger import Logger [as 别名]
# 或者: from utils.logger.Logger import error [as 别名]
def get_seg_loss(self, key):
if key == 'cross_entropy_loss':
return CrossEntropyLoss()
elif key == 'embedding_loss':
return EmbeddingLoss(self.configer.get('num_classes'))
elif key == 'iou_loss':
return IOULoss(self.configer.get('num_classes'))
elif key == 'focal_loss':
return FocalLoss(self.configer.get('focal', 'y'))
else:
Log.error('Segmentation Loss: {} is not valid.'.format(key))
exit(1)