Get rid of implementation names (#56)

people_recognition_2d/README.md

@@ -2,21 +2,21 @@
 Node for people recognition in 2D. Defined as a service and not a publisher/subscriber.
 
 ## Custom dependencies
-- [image_recognition_openpose](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_openpose)
-- [image_recognition_openface](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_openpose)
-- [image_recognition_keras](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_keras)
+- [image_recognition_pose_estimation](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_pose_estimation)
+- [image_recognition_face_recognition](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_pose_estimation)
+- [image_recognition_age_gender](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_age_gender)
 - [image_recognition_color_extractor](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_color_extractor)
 - [image_recognition_msgs](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_msgs)
 
 # How To
 ### Start the dependent nodes
 The relative namespaces of the dependent nodes must be as follows so that their advertised services are the same as the values of the [parameters](#parameters) of people recognition node:
 ```
-rosrun image_recognition_openpose openpose_node __ns:=openpose
+rosrun image_recognition_pose_estimation pose_estimation_node __ns:=pose_estimation
 
-rosrun image_recognition_openface face_recognition_node __ns:=face_recognition
+rosrun image_recognition_face_recognition face_recognition_node __ns:=face_recognition
 
-rosrun image_recognition_keras face_properties_node __ns:=face_recognition
+rosrun image_recognition_age_gender face_properties_node __ns:=face_recognition
 
 rosrun image_recognition_color_extractor color_extractor_node
 ```
@@ -30,12 +30,12 @@ This will create a service `detect_people` of type `RecognizePeople2D` and which
 custom message type `people_recognition_msgs/Person2D`
 
 ### Parameters
-| Name                         | Default Value                         |
-|------------------------------|---------------------------------------|
-| `~openpose_srv_name`         | `openpose/recognize`                  |
-| `~openface_srv_name`         | `face_recognition/recognize`          |
-| `~keras_srv_name`            | `face_recognition/get_face_properties`|
-| `~color_extractor_srv_name`  | `extract_color`                       |
+| Name                         | Default Value                          |
+|------------------------------|----------------------------------------|
+| `~pose_estimation_srv_name`  | `pose_estimation/recognize`            |
+| `~face_recognition_srv_name` | `face_recognition/recognize`           |
+| `~face_properties_srv_name`  | `face_recognition/get_face_properties` |
+| `~color_extractor_srv_name`  | `extract_color`                        |
 
 ### Message definition of Person2D
 ```
@@ -67,9 +67,9 @@ roscd people_recognition_2d/scripts
 ```
 
 # Work Flow
-The node first calls the recognize services of the openpose and openface nodes. ROIs of faces are extracted from
-the recognitions returned by OpenPose and are associated with the recognitions returned by OpenFace through the
-face ROIs to create a `Person2D` object. The ROIs of body parts returned by OpenPose are associated with each
-`Person2D` object. Face images are sent to the Keras node and properties (age and gender) are extracted and
+The node first calls the recognize services of the pose_estimation and face_recognition nodes. ROIs of faces are extracted from
+the recognitions returned by pose_estimation and are associated with the recognitions returned by face_recognition through the
+face ROIs to create a `Person2D` object. The ROIs of body parts returned by pose_estimation are associated with each
+`Person2D` object. Face images are sent to the face properties node and properties (age and gender) are extracted and
 assoicated with each 'Person2D' object. The ROIs of the faces are shifted vertically to approximate the ROIs of
 the shirts. These are sent to the color extractor to get the dominant colors.

people_recognition_2d/scripts/get_people_recognition_2d

@@ -10,9 +10,9 @@ from people_recognition_2d import PeopleRecognizer2D
 
 parser = argparse.ArgumentParser(description="Get 2D people recognition")
 parser.add_argument("-v", "--verbose", help="Increase output verbosity", action="store_true")
-parser.add_argument("--openpose_srv_name", default="openpose/recognize")
-parser.add_argument("--openface_srv_name", default="people_recognition/face_recognition/recognize")
-parser.add_argument("--keras_srv_name", default="people_recognition/face_recognition/get_face_properties")
+parser.add_argument("--pose_estimation_srv_name", default="pose_estimation/recognize")
+parser.add_argument("--face_recognition_srv_name", default="people_recognition/face_recognition/recognize")
+parser.add_argument("--face_properties_srv_name", default="people_recognition/face_recognition/get_face_properties")
 parser.add_argument("--color_extractor_srv_name", default="people_recognition/extract_color")
 
 parser.add_argument("--enable-age-gender", action="store_const", default=True, const=True, dest="age_gender")
@@ -36,9 +36,9 @@ args = parser.parse_args(myargv)
 rospy.init_node("get_people_recognition_2d")
 
 recognizer = PeopleRecognizer2D(
-    args.openpose_srv_name,
-    args.openface_srv_name,
-    args.keras_srv_name,
+    args.pose_estimation_srv_name,
+    args.face_recognition_srv_name,
+    args.face_properties_srv_name,
     args.color_extractor_srv_name,
     args.age_gender,
     args.shirt_color,

people_recognition_2d/scripts/people_recognition_2d_node

@@ -11,16 +11,16 @@ from sensor_msgs.msg import Image
 class PeopleRecognition2DNode:
     def __init__(self):
 
-        openpose_srv_name = self._get_param('~openpose_srv_name', "openpose/recognize")
-        openface_srv_name = self._get_param('~openface_srv_name', "face_recognition/recognize")
-        keras_srv_name = self._get_param('~keras_srv_name', "face_recognition/get_face_properties")
+        pose_estimation_srv_name = self._get_param('~pose_estimation_srv_name', "pose_estimation/recognize")
+        face_recognition_srv_name = self._get_param('~face_recognition_srv_name', "face_recognition/recognize")
+        face_properties_srv_name = self._get_param('~face_properties_srv_name', "face_recognition/get_face_properties")
         color_extractor_srv_name = self._get_param('~color_extractor_srv_name', "extract_color")
         enable_age_gender_detection = self._get_param('~enable_age_gender_detection', True)
         enable_shirt_color_extraction = self._get_param('~enable_shirt_color_extraction', True)
 
-        self._people_recognizer = PeopleRecognizer2D(openpose_srv_name,
-                                                     openface_srv_name,
-                                                     keras_srv_name,
+        self._people_recognizer = PeopleRecognizer2D(pose_estimation_srv_name,
+                                                     face_recognition_srv_name,
+                                                     face_properties_srv_name,
                                                      color_extractor_srv_name,
                                                      enable_age_gender_detection,
                                                      enable_shirt_color_extraction,

people_recognition_2d/src/people_recognition_2d/people_recognizer_2d.py

@@ -48,23 +48,22 @@ def _get_service_response(srv, args):
 
 
 class PeopleRecognizer2D(object):
-    def __init__(self, openpose_srv_name, openface_srv_name,
-                 keras_srv_name, color_extractor_srv_name,
+    def __init__(self, pose_estimation_srv_name, face_recognition_srv_name,
+                 face_properties_srv_name, color_extractor_srv_name,
                  enable_age_gender_detection, enable_shirt_color_extraction):
 
-        self._openpose_srv = _get_and_wait_for_service(openpose_srv_name, Recognize)
-        self._openface_srv = _get_and_wait_for_service(openface_srv_name, Recognize)
+        self._pose_estimation_srv = _get_and_wait_for_service(pose_estimation_srv_name, Recognize)
+        self._face_recognition_srv = _get_and_wait_for_service(face_recognition_srv_name, Recognize)
 
         self._enable_age_gender_detection = enable_age_gender_detection
         self._enable_shirt_color_extraction = enable_shirt_color_extraction
 
         if self._enable_age_gender_detection:
-            self._keras_srv = _get_and_wait_for_service(keras_srv_name, GetFaceProperties)
+            self._face_properties_srv = _get_and_wait_for_service(face_properties_srv_name, GetFaceProperties)
 
         if self._enable_shirt_color_extraction:
             self._color_extractor_srv = _get_and_wait_for_service(color_extractor_srv_name, Recognize)
 
-
         self._bridge = CvBridge()
 
         rospy.loginfo("People recognizer 2D initialized")
@@ -80,12 +79,12 @@ def _is_label_recognition(recognition):
         return [r for r in recognitions if _is_label_recognition(r)]
 
     @staticmethod
-    def _get_face_rois_ids_openpose(recognitions):
+    def _get_face_rois_ids_pose_estimation(recognitions):
         """
-        Get ROIs of faces from openpose recognitions using the nose, left ear
+        Get ROIs of faces from pose estimation using the nose, left ear
         and right ear
 
-        :param: recognitions from openpose
+        :param: recognitions from pose estimation
         """
         nose_recognitions = PeopleRecognizer2D._get_recognitions_with_label("Nose", recognitions)
         left_ear_recognitions = PeopleRecognizer2D._get_recognitions_with_label("LEar", recognitions)
@@ -129,23 +128,23 @@ def _get_face_rois_ids_openpose(recognitions):
         return rois, group_ids
 
     @staticmethod
-    def _get_body_parts_openpose(group_id, recognitions):
+    def _get_body_parts_pose_estimation(group_id, recognitions):
         """
         Get a list of all bodyparts associated with a particular group ID
 
         :param: group_id: The group ID of the bodyparts to be fetched
-        :param: recognitions: All bodyparts recieved from openpose
+        :param: recognitions: All bodyparts received from pose estimation
         :return: List of body_parts
         """
         return [r for r in recognitions if r.group_id == group_id]
 
     @staticmethod
     def _get_container_recognition(roi, recognitions, padding_factor=0.1):
         """
-        Associate OpenPose ROI with best OpenPose face ROI
+        Associate pose estimation ROI with best pose estimation face ROI
 
-        :param: roi: openpose face roi
-        :recognitions: openface recognitions
+        :param: roi: pose estimation face roi
+        :param: recognitions: face recognitions
         """
         x = roi.x_offset + .5 * roi.width
         y = roi.y_offset + .5 * roi.height
@@ -244,35 +243,38 @@ def recognize(self, image_msg):
         image_annotations = []
         people = []
 
-        # OpenPose and OpenFace service calls
+        # Pose estimation and face recognition service calls
         rospy.loginfo("Starting pose and face recognition...")
         start_recognize = time.time()
-        openpose_response = _get_service_response(self._openpose_srv, image_msg)
-        openface_response = _get_service_response(self._openface_srv, image_msg)
+        pose_estimation_response = _get_service_response(self._pose_estimation_srv, image_msg)
+        face_recognition_response = _get_service_response(self._face_recognition_srv, image_msg)
         rospy.logdebug("Recognize took %.4f seconds", time.time() - start_recognize)
-        rospy.loginfo("_get_face_rois_ids_openpose...")
+        rospy.loginfo("_get_face_rois_ids_pose_estimation...")
 
-        # Extract face ROIs and their corresponding group ids from recognitions of openpose
-        openpose_face_rois, openpose_face_group_ids = PeopleRecognizer2D._get_face_rois_ids_openpose(
-            openpose_response.recognitions)
+        # Extract face ROIs and their corresponding group ids from recognitions of pose estimation
+        pose_estimation_face_rois, pose_estimation_face_group_ids = PeopleRecognizer2D._get_face_rois_ids_pose_estimation(
+            pose_estimation_response.recognitions
+        )
 
-        body_parts_array = [PeopleRecognizer2D._get_body_parts_openpose(group_id,
-                                                                        openpose_response.recognitions) for group_id in
-                            openpose_face_group_ids]
+        body_parts_array = [
+            PeopleRecognizer2D._get_body_parts_pose_estimation(group_id, pose_estimation_response.recognitions)
+            for group_id in pose_estimation_face_group_ids
+        ]
 
-        face_recognitions = [PeopleRecognizer2D._get_container_recognition(openpose_face_roi,
-                                                                           openface_response.recognitions)
-                             for openpose_face_roi in openpose_face_rois]
+        face_recognitions = [
+            PeopleRecognizer2D._get_container_recognition(pose_estimation_face_roi, face_recognition_response.recognitions)
+            for pose_estimation_face_roi in pose_estimation_face_rois
+        ]
 
         face_labels = [PeopleRecognizer2D._get_best_label(r) for r in face_recognitions]
 
-        # Keras service call
+        # Face properties service call
         if self._enable_age_gender_detection:
             rospy.loginfo("_get_face_properties...")
             face_image_msg_array = [self._bridge.cv2_to_imgmsg(PeopleRecognizer2D._image_from_roi(image, r.roi), "bgr8") for
                                     r in face_recognitions]
-            keras_response = _get_service_response(self._keras_srv, face_image_msg_array)
-            face_properties_array = keras_response.properties_array
+            face_properties_response = _get_service_response(self._face_properties_srv, face_image_msg_array)
+            face_properties_array = face_properties_response.properties_array
         else:
             face_properties_array = [FaceProperties()] * len(face_recognitions)
 

people_recognition_3d/config/config.yaml

@@ -4,7 +4,7 @@ link_threshold: 0.5
 heuristic: "shoulder"
 arm_norm_threshold: 0.5
 neck_norm_threshold: 0.7
-wave_threshold: 0.2
+waving_threshold: 0.2
 vert_threshold: 0.7
 hor_threshold: 0.4
 padding: 5

people_recognition_3d/package.xml

@@ -23,6 +23,8 @@
   <exec_depend>cv_bridge</exec_depend>
   <exec_depend>geometry_msgs</exec_depend>
   <exec_depend>image_geometry</exec_depend>
+  <exec_depend>image_recognition_pose_estimation</exec_depend>
+  <exec_depend>image_recognition_util</exec_depend>
   <exec_depend>message_filters</exec_depend>
   <exec_depend>people_recognition_2d</exec_depend>
   <exec_depend>people_recognition_msgs</exec_depend>

people_recognition_3d/scripts/dummy_people_recognition_3d_node.py

@@ -38,7 +38,7 @@ def _generate_dummy_person3d(self, rgb, depth, cam_info, name=None):
         colors = ['black', 'orange', 'yellow']
         random.shuffle(colors)
         person.shirt_colors = colors
-        person.tags = ['LWave', 'RWave'] + random.choice([[], ["is_pointing"]])
+        person.tags = ['LWaving', 'RWaving'] + random.choice([[], ["is_pointing"]])
         # person.body_parts_pose
         person.position = Point()
         person.face.roi = RegionOfInterest(width=200, height=200)

people_recognition_3d/scripts/people_recognition_3d_node

@@ -24,7 +24,7 @@ class PeopleRecognition3DNode:
         heuristic = self._get_param('~heuristic', 'shoulder')
         arm_norm_threshold = self._get_param('~arm_norm_threshold', 0.5)
         neck_norm_threshold = self._get_param('~neck_norm_threshold', 0.7)
-        wave_threshold = self._get_param('~wave_threshold', 0.2)
+        waving_threshold = self._get_param('~waving_threshold', 0.2)
         vert_threshold = self._get_param('~vert_threshold', 0.7)
         hor_threshold = self._get_param('~hor_threshold', 0.4)
         padding = self._get_param('~padding', 5)
@@ -33,7 +33,7 @@ class PeopleRecognition3DNode:
 
         self._people_recognizer_3d = PeopleRecognizer3D(
             recognize_people_srv_name, probability_threshold, link_threshold,
-            heuristic, arm_norm_threshold, neck_norm_threshold, wave_threshold,
+            heuristic, arm_norm_threshold, neck_norm_threshold, waving_threshold,
             vert_threshold, hor_threshold, padding)
 
         self._markers_pub = rospy.Publisher('~viz',