add seg_id interface for policy update() function

src/active_grasp/active_perception_policy.py

@@ -18,8 +18,8 @@ class ActivePerceptionPolicy(MultiViewPolicy):
     def activate(self, bbox, view_sphere):
         super().activate(bbox, view_sphere)
 
-    def update(self, img, seg, x, q):
+    def update(self, img, seg, target_id, x, q):
-        self.depth_image_to_ap_input(img, seg)
+        self.depth_image_to_ap_input(img, seg, target_id)
         # if len(self.views) > self.max_views or self.best_grasp_prediction_is_stable():
         #     self.done = True
         # else:
@@ -41,7 +41,7 @@ class ActivePerceptionPolicy(MultiViewPolicy):
 
         #     self.x_d = nbv
     
-    def depth_image_to_ap_input(self, depth_img, seg_img):
+    def depth_image_to_ap_input(self, depth_img, seg_img, target_id):
         K = self.intrinsic.K
         depth_shape = depth_img.shape
         seg_shape = seg_img.shape

src/active_grasp/baselines.py

@@ -4,7 +4,7 @@ from .policy import SingleViewPolicy, MultiViewPolicy, compute_error
 
 
 class InitialView(SingleViewPolicy):
-    def update(self, img, x, q):
+    def update(self, img, seg, target_id, x, q):
         self.x_d = x
         super().update(img, x, q)
 
@@ -22,7 +22,7 @@ class TopTrajectory(MultiViewPolicy):
         self.x_d = self.view_sphere.get_view(0.0, 0.0)
         self.done = False if self.solve_cam_ik(self.q0, self.x_d) else True
 
-    def update(self, img, x, q):
+    def update(self, img, seg, target_id, x, q):
         self.integrate(img, x, q)
         linear, _ = compute_error(self.x_d, x)
         if np.linalg.norm(linear) < 0.02:
@@ -33,5 +33,5 @@ class FixedTrajectory(MultiViewPolicy):
     def activate(self, bbox, view_sphere):
         pass
 
-    def update(self, img, x, q):
+    def update(self, img, seg, target_id, x, q):
         pass

src/active_grasp/controller.py

@@ -9,7 +9,7 @@ import trimesh
 
 from .bbox import from_bbox_msg
 from .timer import Timer
-from active_grasp.srv import Reset, ResetRequest
+from active_grasp.srv import *
 from robot_helpers.ros import tf
 from robot_helpers.ros.conversions import *
 from robot_helpers.ros.panda import PandaArmClient, PandaGripperClient
@@ -43,6 +43,7 @@ class GraspController:
         self.switch_controller = rospy.ServiceProxy(
             "controller_manager/switch_controller", SwitchController
         )
+        self.get_target_id = rospy.ServiceProxy("get_target_seg_id", TargetID)
 
     def init_robot_connection(self):
         self.arm = PandaArmClient()
@@ -108,7 +109,8 @@ class GraspController:
         r = rospy.Rate(self.policy_rate)
         while not self.policy.done:
             depth_img, seg_image, pose, q = self.get_state()
-            self.policy.update(depth_img, seg_image, pose, q)
+            target_seg_id = self.get_target_id(TargetIDRequest())
+            self.policy.update(depth_img, seg_image, target_seg_id, pose, q)
             r.sleep()
         rospy.sleep(0.2)  # Wait for a zero command to be sent to the robot.
         self.policy.deactivate()

src/active_grasp/nbv.py

@@ -84,7 +84,7 @@ class NextBestView(MultiViewPolicy):
     def activate(self, bbox, view_sphere):
         super().activate(bbox, view_sphere)
 
-    def update(self, img, seg, x, q):
+    def update(self, img, seg, target_id, x, q):
         if len(self.views) > self.max_views or self.best_grasp_prediction_is_stable():
             self.done = True
         else:

src/active_grasp/policy.py

@@ -75,7 +75,7 @@ class Policy:
         rospy.sleep(1.0)  # Wait for tf tree to be updated
         self.vis.roi(self.task_frame, 0.3)
 
-    def update(self, img, seg, x, q):
+    def update(self, img, seg, target_id, x, q):
         raise NotImplementedError
 
     def filter_grasps(self, out, q):
@@ -106,7 +106,7 @@ def select_best_grasp(grasps, qualities):
 
 
 class SingleViewPolicy(Policy):
-    def update(self, img, seg, x, q):
+    def update(self, img, seg, target_id, x, q):
         linear, _ = compute_error(self.x_d, x)
         if np.linalg.norm(linear) < 0.02:
             self.views.append(x)