Check format by flake and isort (HiroIshida#31)

* Fix format according to flake and isort

* Check format in ci

.flake8

@@ -0,0 +1,8 @@
+[flake8]
+ignore = 
+    I, H # follow isort 
+    E501  # max length should be checked by black
+    E203  # https://github.com/psf/black/issues/315
+    W503  # https://github.com/psf/black/issues/52
+    E402  # because we can't avoid sys.path.append stuff
+    A, B, C, CNL, D, Q  # external plugins if installed

.github/workflows/peripheral.yml

@@ -16,11 +16,16 @@ jobs:
           uses: actions/checkout@v2
         - name: pip install formatters and mypy
           run: |
-              pip3 install mypy
+              pip3 install mypy flake8 isort
 
         - name: check by mypy
           run: |
               pip3 install -r requirements.txt
               pip3 install numpy==1.23  # to enable numpy's type checking
               mypy --version
               mypy .
+
+        - name: check by isrot and flake8
+          run: |
+              python3 -m isort example/ test/ node_script/
+              python3 -m flake8 example/ test/ node_script/

.isort.cfg

@@ -0,0 +1,2 @@
+[settings]
+profile = black

example/client.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
 import argparse
-import cv_bridge
+
 import cv2
+import matplotlib.pyplot as plt
 import rospy
 from cv_bridge import CvBridge
-from sensor_msgs.msg import Image
+
 from detic_ros.srv import DeticSeg
-import matplotlib.pyplot as plt
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()

example/masked_image_publisher.py

@@ -1,11 +1,13 @@
 #!/usr/bin/env python3
 import copy
+
+import message_filters
 import numpy as np
 import rospy
-import message_filters
+from cv_bridge import CvBridge
 from sensor_msgs.msg import Image
+
 from detic_ros.msg import SegmentationInfo
-from cv_bridge import CvBridge
 
 
 class SampleNode:
@@ -46,7 +48,7 @@ def callback(self, msg_image, msg_info: SegmentationInfo):
         img = bridge.imgmsg_to_cv2(msg_image, desired_encoding='passthrough')
 
         # Add 1 to label_index to account for the background
-        mask_indexes = np.where(img==label_index+1)
+        mask_indexes = np.where(img == label_index + 1)
 
         masked_img = copy.deepcopy(img)
         masked_img[mask_indexes] = 0  # filled by black
@@ -55,7 +57,7 @@ def callback(self, msg_image, msg_info: SegmentationInfo):
         self.pub.publish(msg_out)
 
 
-if __name__=='__main__':
+if __name__ == '__main__':
     import sys
     argv = [x for x in sys.argv if not x.startswith('_')]  # remove roslaunch args
     if len(argv) == 1:
@@ -70,5 +72,3 @@ def callback(self, msg_image, msg_info: SegmentationInfo):
     SampleNode(mask_class_name=class_name)
     rospy.spin()
     pass
-
-

node_script/batch_processor.py

@@ -2,18 +2,14 @@
 import argparse
 import os
 import pickle
-from numpy import inf
 from typing import List, Optional
 
 import rosbag
-import rospy
+import tqdm
 from cv_bridge import CvBridge
-from sensor_msgs.msg import Image
-from detic_ros.msg import SegmentationInfo
 from moviepy.editor import ImageSequenceClip
-import tqdm
-
 from node_config import NodeConfig
+from sensor_msgs.msg import Image
 from wrapper import DeticWrapper
 
 
@@ -78,7 +74,7 @@ def dump_result_as_rosbag(input_bagfile_name, results, output_file_name):
     bag_out.close()
 
 
-if __name__=='__main__':
+if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('input', type=str, help='input file path')
     parser.add_argument('-model', type=str, default='swin', help='model type')
@@ -129,7 +125,10 @@ def dump_result_as_rosbag(input_bagfile_name, results, output_file_name):
 
     # dump debug gif image
     bridge = CvBridge()
-    convert = lambda msg: bridge.imgmsg_to_cv2(msg, desired_encoding='passthrough')
+
+    def convert(msg):
+        bridge.imgmsg_to_cv2(msg, desired_encoding='passthrough')
+
     debug_images = [result[1] for result in results]
     images = list(map(convert, debug_images))
     clip = ImageSequenceClip(images, fps=20)

node_script/node.py

@@ -2,15 +2,15 @@
 from typing import Optional
 
 import rospy
-from rospy import Subscriber, Publisher
-from sensor_msgs.msg import Image
-from detic_ros.msg import SegmentationInfo
-from detic_ros.srv import DeticSeg, DeticSegRequest, DeticSegResponse
 from jsk_recognition_msgs.msg import LabelArray, VectorArray
-
 from node_config import NodeConfig
+from rospy import Publisher, Subscriber
+from sensor_msgs.msg import Image
 from wrapper import DeticWrapper
 
+from detic_ros.msg import SegmentationInfo
+from detic_ros.srv import DeticSeg, DeticSegRequest, DeticSegResponse
+
 
 class DeticRosNode:
     detic_wrapper: DeticWrapper
@@ -22,7 +22,7 @@ class DeticRosNode:
     pub_labels: Publisher
     pub_score: Publisher
 
-    def __init__(self, node_config: Optional[NodeConfig]=None):
+    def __init__(self, node_config: Optional[NodeConfig] = None):
         if node_config is None:
             node_config = NodeConfig.from_rosparam()
 
@@ -90,7 +90,7 @@ def callback_srv(self, req: DeticSegRequest) -> DeticSegResponse:
         return resp
 
 
-if __name__=='__main__':
+if __name__ == '__main__':
     rospy.init_node('detic_node', anonymous=True)
     node = DeticRosNode()
     rospy.spin()

node_script/node_config.py

@@ -1,16 +1,16 @@
 import os
 import sys
 from dataclasses import dataclass
-import rospy
-import rospkg
 
+import rospkg
+import rospy
 import torch
 
 # Dirty but no way, because CenterNet2 is not package oriented
 sys.path.insert(0, os.path.join(sys.path[0], 'third_party/CenterNet2/'))
 
-from detectron2.config import get_cfg
 from centernet.config import add_centernet_config
+from detectron2.config import get_cfg
 from detic.config import add_detic_config
 
 
@@ -36,7 +36,8 @@ class NodeConfig:
     }
 
     @classmethod
-    def from_args(cls, 
+    def from_args(
+            cls,
             model_type: str = 'swin',
             enable_pubsub: bool = True,
             out_debug_img: bool = True,
@@ -46,8 +47,7 @@ def from_args(cls,
             confidence_threshold: float = 0.5,
             device_name: str = 'auto',
             vocabulary: str = 'lvis',
-            custom_vocabulary: str = '',
-            ):
+            custom_vocabulary: str = ''):
 
         if device_name == 'auto':
             device_name = 'cuda' if torch.cuda.is_available() else 'cpu'
@@ -67,33 +67,32 @@ def from_args(cls,
             model_name + '.pth')
 
         return cls(
-                enable_pubsub,
-                out_debug_img,
-                out_debug_segimg,
-                verbose,
-                use_jsk_msgs,
-                vocabulary,
-                custom_vocabulary,
-                default_detic_config_path,
-                default_model_weights_path,
-                confidence_threshold,
-                device_name)
+            enable_pubsub,
+            out_debug_img,
+            out_debug_segimg,
+            verbose,
+            use_jsk_msgs,
+            vocabulary,
+            custom_vocabulary,
+            default_detic_config_path,
+            default_model_weights_path,
+            confidence_threshold,
+            device_name)
 
     @classmethod
     def from_rosparam(cls):
 
         return cls.from_args(
-                rospy.get_param('~model_type', 'swin'),
-                rospy.get_param('~enable_pubsub', True),
-                rospy.get_param('~out_debug_img', True),
-                rospy.get_param('~out_debug_segimg', False),
-                rospy.get_param('~verbose', True),
-                rospy.get_param('~use_jsk_msgs', False),
-                rospy.get_param('~confidence_threshold', 0.5),
-                rospy.get_param('~device', 'auto'),
-                rospy.get_param('~vocabulary', 'lvis'),
-                rospy.get_param('~custom_vocabulary', ''),
-                )
+            rospy.get_param('~model_type', 'swin'),
+            rospy.get_param('~enable_pubsub', True),
+            rospy.get_param('~out_debug_img', True),
+            rospy.get_param('~out_debug_segimg', False),
+            rospy.get_param('~verbose', True),
+            rospy.get_param('~use_jsk_msgs', False),
+            rospy.get_param('~confidence_threshold', 0.5),
+            rospy.get_param('~device', 'auto'),
+            rospy.get_param('~vocabulary', 'lvis'),
+            rospy.get_param('~custom_vocabulary', ''))
 
     def to_detectron_config(self):
         cfg = get_cfg()
@@ -107,13 +106,13 @@ def to_detectron_config(self):
         cfg.merge_from_list(['MODEL.WEIGHTS', self.model_weights_path])
 
         # Similar to https://github.com/facebookresearch/Detic/demo.py
-        cfg.MODEL.ROI_BOX_HEAD.ZEROSHOT_WEIGHT_PATH = 'rand' # load later
+        cfg.MODEL.ROI_BOX_HEAD.ZEROSHOT_WEIGHT_PATH = 'rand'  # load later
         cfg.MODEL.ROI_HEADS.ONE_CLASS_PER_PROPOSAL = True
 
         # Maybe should edit detic_configs/Base-C2_L_R5021k_640b64_4x.yaml
         pack_path = rospkg.RosPack().get_path('detic_ros')
         cfg.MODEL.ROI_BOX_HEAD.CAT_FREQ_PATH = os.path.join(
-                pack_path, 'datasets/metadata/lvis_v1_train_cat_info.json')
+            pack_path, 'datasets/metadata/lvis_v1_train_cat_info.json')
 
         cfg.freeze()
         return cfg

node_script/wrapper.py

@@ -1,21 +1,20 @@
 import os
-from typing import Optional, Tuple, List
+from typing import List, Optional, Tuple
 
-import rospy
+import detic
+import numpy as np
 import rospkg
-from cv_bridge import CvBridge
-from sensor_msgs.msg import Image
-from std_msgs.msg import Header
-from detic_ros.msg import SegmentationInfo
-
+import rospy
 import torch
-import numpy as np
-
-import detic
+from cv_bridge import CvBridge
+from detectron2.utils.visualizer import VisImage
 from detic.predictor import VisualizationDemo
 from jsk_recognition_msgs.msg import Label, LabelArray, VectorArray
-from detectron2.utils.visualizer import VisImage
 from node_config import NodeConfig
+from sensor_msgs.msg import Image
+from std_msgs.msg import Header
+
+from detic_ros.msg import SegmentationInfo
 
 
 class DeticWrapper:
@@ -26,8 +25,9 @@ class DeticWrapper:
     header: Optional[Header]
     data: Optional[np.ndarray]
 
-    class DummyArgs: 
+    class DummyArgs:
         vocabulary: str
+
         def __init__(self, vocabulary, custom_vocabulary):
             assert vocabulary in ['lvis', 'openimages', 'objects365', 'coco', 'custom']
             self.vocabulary = vocabulary
@@ -45,14 +45,13 @@ def __init__(self, node_config: NodeConfig):
         self.header = None
         self.data = None
 
-
     @staticmethod
     def _adhoc_hack_metadata_path():
         # because original BUILDIN_CLASSIFIER is somehow posi-dep
         rospack = rospkg.RosPack()
         pack_path = rospack.get_path('detic_ros')
         path_dict = detic.predictor.BUILDIN_CLASSIFIER
-        for key in  path_dict.keys():
+        for key in path_dict.keys():
             path_dict[key] = os.path.join(pack_path, path_dict[key])
 
     def inference_step(self, msg: Image) -> Tuple[Image, List[int], List[float], Optional[VisImage]]:
@@ -123,7 +122,7 @@ def get_segmentation_info(self, seg_img: Image,
 
     def get_label_array(self, detected_classes: List[int]) -> LabelArray:
         # Label 0 is reserved for the background
-        labels = [Label(id=i+1, name=self.class_names[i]) for i in detected_classes]
+        labels = [Label(id=i + 1, name=self.class_names[i]) for i in detected_classes]
         lab_arr = LabelArray(header=self.header,
                              labels=labels)
         return lab_arr

test/test_batch_processor.py

@@ -1,10 +1,11 @@
 #!/usr/bin/env python3
 import os
+import pickle
 import unittest
 
-import pickle
-import rostest, rospy
 import rospkg
+import rospy
+import rostest
 
 
 class TestNode(unittest.TestCase):
@@ -19,15 +20,15 @@ def test_pkl_dump(self):
 
         pkl_path = os.path.join(pkg_path, 'test', 'data', 'desk_segmented.pkl')
         with open(pkl_path, 'rb') as f:
-            obj = pickle.load(f)
+            pickle.load(f)
 
     def test_rosbag_dump(self):
         pkg_path = rospkg.RosPack().get_path('detic_ros')
         bag_path = os.path.join(pkg_path, 'test', 'data', 'desk.bag')
         ret = os.system('rosrun detic_ros batch_processor.py {} -n 1 -format bag'.format(bag_path))
         assert ret == 0
 
-        outbag_path = os.path.join(pkg_path, 'test', 'data', 'desk_segmented.bag')
+        os.path.join(pkg_path, 'test', 'data', 'desk_segmented.bag')
 
 
 if __name__ == '__main__':