fix flake8

.travis.yml

@@ -0,0 +1,13 @@
+dist: trusty
+language: python
+
+install:
+ - pip install flake8
+
+python:
+ - "2.7"
+ - "3.5"
+ - "3.6"
+
+script:
+ - flake8

deepim/_init_paths.py

@@ -7,10 +7,12 @@
 import os.path as osp
 import sys
 
+
 def add_path(path):
  if path not in sys.path:
  sys.path.insert(0, path)
 
+
 this_dir = osp.dirname(__file__)
 
 lib_path = osp.join(this_dir, '../lib')

deepim/config/config.py

@@ -14,7 +14,8 @@
 
 config.output_path = ''
 config.symbol = ''
-config.SCALES = [(480, 640)] # first is scale (the shorter side); second is max size
+config.SCALES = [(480, 640)
+ ] # first is scale (the shorter side); second is max size
 
 # default training
 config.default = edict()
@@ -36,11 +37,10 @@
 config.network.STANDARD_FLOW_REP = False
 config.network.TRAIN_ITER = False
 config.network.TRAIN_ITER_SIZE = 1
-config.network.REGRESSOR_NUM = 1 # 1 or num_classes
-config.network.ROT_TYPE = 'QUAT' # 'QUAT', 'EULER'
+config.network.REGRESSOR_NUM = 1  # 1 or num_classes
+config.network.ROT_TYPE = 'QUAT'  # 'QUAT', 'EULER'
 config.network.ROT_COORD = 'CAMERA'
-config.network.TRANS_LOSS_TYPE = 'L2' # 'L1', 'smooth_L1'
-
+config.network.TRANS_LOSS_TYPE = 'L2' # 'L1', 'smooth_L1'
 
 # dataset related params
 config.dataset = edict()
@@ -50,13 +50,15 @@
 config.dataset.root_path = './data'
 config.dataset.test_image_set = 'val_ape'
 config.dataset.model_dir = ''
-config.dataset.model_file = './data/ModelNet/render_v1/models.txt' # optional, if too many classes
-config.dataset.pose_file = './data/ModelNet/render_v1/poses.txt' # optional, if too many classes
+config.dataset.model_file = './data/ModelNet/render_v1/models.txt'  # optional, if too many classes
+config.dataset.pose_file = './data/ModelNet/render_v1/poses.txt'  # optional, if too many classes
 
 config.dataset.DEPTH_FACTOR = 1000
 config.dataset.NORMALIZE_FLOW = 1.0
 config.dataset.NORMALIZE_3D_POINT = 0.1
-config.dataset.INTRINSIC_MATRIX = np.array([[572.4114, 0, 325.2611], [0, 573.57043, 242.04899], [0, 0, 1]])
+config.dataset.INTRINSIC_MATRIX = np.array([[572.4114, 0, 325.2611],
+ [0, 573.57043, 242.04899],
+ [0, 0, 1]])
 config.dataset.ZNEAR = 0.25
 config.dataset.ZFAR = 6.0
 
@@ -80,13 +82,13 @@
 config.TRAIN.RESUME = False
 config.TRAIN.SHUFFLE = True
 config.TRAIN.BATCH_PAIRS = 1
-config.TRAIN.FLOW_WEIGHT_TYPE = 'all' # 'all', 'viz', 'valid'
+config.TRAIN.FLOW_WEIGHT_TYPE = 'all'  # 'all', 'viz', 'valid'
 # config.TRAIN.VISUALIZE = False
 config.TRAIN.TENSORBOARD_LOG = False
-config.TRAIN.INIT_MASK = 'box_gt' # mask_gt, box_gt
+config.TRAIN.INIT_MASK = 'box_gt'  # mask_gt, box_gt
 config.TRAIN.UPDATE_MASK = 'box_gt'
 config.TRAIN.MASK_DILATE = False
-config.TRAIN.REPLACE_OBSERVED_BG_RATIO = 0.0 # replace train images' bg with VOC
+config.TRAIN.REPLACE_OBSERVED_BG_RATIO = 0.0  # replace train images' bg with VOC
 
 config.TEST = edict()
 config.TEST.BATCH_PAIRS = 1
@@ -96,28 +98,29 @@
 config.TEST.INIT_MASK = 'box_rendered'
 config.TEST.UPDATE_MASK = 'box_rendered'
 config.TEST.FAST_TEST = False
-config.TEST.PRECOMPUTED_ICP = False # evaluate with ICP refinement
-config.TEST.BEFORE_ICP = False # evaluate without ICP refinement
+config.TEST.PRECOMPUTED_ICP = False  # evaluate with ICP refinement
+config.TEST.BEFORE_ICP = False  # evaluate without ICP refinement
 
 # for iterative train
-## se3 distance loss
+# se3 distance loss
 config.train_iter = edict()
 config.train_iter.SE3_DIST_LOSS = False
 config.train_iter.LW_ROT = 0.0
 config.train_iter.LW_TRANS = 0.0
-config.train_iter.TRANS_LOSS_TYPE = 'L2' # 'L1', 'smooth_L1'
+config.train_iter.TRANS_LOSS_TYPE = 'L2'  # 'L1', 'smooth_L1'
 config.train_iter.TRANS_SMOOTH_L1_SCALAR = 3.0
-## se3 point matching loss
+# se3 point matching loss
 config.train_iter.SE3_PM_LOSS = False
 config.train_iter.LW_PM = 0.0
 config.train_iter.SE3_PM_LOSS_TYPE = 'L1'
 config.train_iter.SE3_PM_SL1_SCALAR = 1.0
 config.train_iter.NUM_3D_SAMPLE = -1
-## flow loss
+# flow loss
 config.train_iter.LW_FLOW = 0.0
-## segmentation loss
+# segmentation loss
 config.train_iter.LW_MASK = 0.0
 
+
 def update_config(config_file):
  exp_config = None
  with open(config_file) as f:
@@ -134,15 +137,21 @@ def update_config(config_file):
  elif k == 'dataset':
  # make elegant later
  if 'INTRINSIC_MATRIX' in v:
- v['INTRINSIC_MATRIX'] = np.array(v['INTRINSIC_MATRIX']).reshape([3,3]).astype(np.float32)
+ v['INTRINSIC_MATRIX'] = np.array(
+ v['INTRINSIC_MATRIX']).reshape([3, 3]).astype(
+ np.float32)
  if 'trans_means' in v:
- v['trans_means'] = np.array(v['trans_means']).flatten().astype(np.float32)
+ v['trans_means'] = np.array(
+ v['trans_means']).flatten().astype(np.float32)
  if 'trans_stds' in v:
- v['trans_stds'] = np.array(v['trans_stds']).flatten().astype(np.float32)
+ v['trans_stds'] = np.array(
+ v['trans_stds']).flatten().astype(np.float32)
  if 'class_name_file' in v:
  if v['class_name_file'] != '':
  with open(v['class_name_file']) as f:
- v['class_name'] = [line.strip() for line in f.readlines()]
+ v['class_name'] = [
+ line.strip() for line in f.readlines()
+ ]
  for vk, vv in v.items():
  config[k][vk] = vv
  else:
@@ -151,4 +160,5 @@ def update_config(config_file):
  else:
  config[k] = v
  else:
- raise ValueError("key: {} does not exist in config.py".format(k))
+ raise ValueError(
+ "key: {} does not exist in config.py".format(k))