add compute_plane_normal
modified: src/maintain/scripts/test.py
This commit is contained in:
@@ -14,8 +14,7 @@ import rospkg
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# import open3d as o3d
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# import open3d as o3d
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# from open3d_ros_helper import open3d_ros_helper as orh
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# from open3d_ros_helper import open3d_ros_helper as orh
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import os
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import math
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import sys
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from rostopic import get_topic_type
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from rostopic import get_topic_type
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from detection_msgs.msg import BoundingBox, BoundingBoxes
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from detection_msgs.msg import BoundingBox, BoundingBoxes
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@@ -24,11 +23,49 @@ annulus_width = 10
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# 2d to 3d
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# 2d to 3d
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def computer_2d_3d(x, y, depth_roi, color_intrinsics):
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def computer_2d_3d(x, y, depth_roi, color_intrinsics):
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pz = np.mean(depth_roi) * 0.001
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pz = depth_roi[int(y), int(x)] / 1000.0
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px = (x - color_intrinsics[2]) * pz / color_intrinsics[0]
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px = (x - color_intrinsics[2]) * pz / color_intrinsics[0]
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py = (y - color_intrinsics[5]) * pz / color_intrinsics[4]
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py = (y - color_intrinsics[5]) * pz / color_intrinsics[4]
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return px, py, pz
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return px, py, pz
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def compute_plane_normal(box, depth, color_intrinsics):
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# 计算相机内参
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fx = color_intrinsics[0]
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fy = color_intrinsics[4]
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cx = color_intrinsics[2]
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cy = color_intrinsics[5]
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# 计算矩形中心点坐标
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x_center = (box[0] + box[2]) / 2
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y_center = (box[1] + box[3]) / 2
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z = depth[int(y_center), int(x_center)]
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x = (x_center - cx) * z / fx
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y = (y_center - cy) * z / fy
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# 计算四个顶点坐标
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x1 = (box[0] - cx) * z / fx
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y1 = (box[1] - cy) * z / fy
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x2 = (box[2] - cx) * z / fx
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y2 = (box[1] - cy) * z / fy
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x3 = (box[2] - cx) * z / fx
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y3 = (box[3] - cy) * z / fy
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x4 = (box[0] - cx) * z / fx
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y4 = (box[3] - cy) * z / fy
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# 计算矩形边缘向量
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v1 = np.array([x2 - x1, y2 - y1, depth[int(box[1]), int(box[0])] - z])
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v2 = np.array([x3 - x2, y3 - y2, depth[int(box[1]), int(box[2])] - z])
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v3 = np.array([x4 - x3, y4 - y3, depth[int(box[3]), int(box[2])] - z])
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v4 = np.array([x1 - x4, y1 - y4, depth[int(box[3]), int(box[0])] - z])
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# 计算平面法向量
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normal = np.cross(v1, v2)
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normal += np.cross(v2, v3)
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normal += np.cross(v3, v4)
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normal += np.cross(v4, v1)
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normal /= np.linalg.norm(normal)
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# 将法向量转换为四元数表示
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theta = math.acos(normal[2])
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sin_theta_2 = math.sin(theta/2)
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quaternion = [math.cos(theta/2), sin_theta_2 * normal[0], sin_theta_2 * normal[1], sin_theta_2 * normal[2]]
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return quaternion
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def compute_normal_vector(p1, p2, p3, p4):
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def compute_normal_vector(p1, p2, p3, p4):
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# Compute two vectors in the plane
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# Compute two vectors in the plane
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v1 = np.array(p2) - np.array(p1)
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v1 = np.array(p2) - np.array(p1)
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@@ -42,7 +79,10 @@ def compute_normal_vector(p1, p2, p3, p4):
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n = -n
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n = -n
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# Normalize the normal vector to obtain a unit vector
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# Normalize the normal vector to obtain a unit vector
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n = n / np.linalg.norm(n)
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n = n / np.linalg.norm(n)
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return n
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theta = math.acos(n[2])
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sin_theta_2 = math.sin(theta/2)
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quaternion = [math.cos(theta/2), sin_theta_2 * n[0], sin_theta_2 * n[1], sin_theta_2 * n[2]]
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return quaternion
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def filter_quaternion(quat, quat_prev, alpha):
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def filter_quaternion(quat, quat_prev, alpha):
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if quat_prev is None:
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if quat_prev is None:
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@@ -69,20 +109,22 @@ def box_callback(box, depth, color_info):
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# print(screw_x,screw_y)
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# print(screw_x,screw_y)
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depth_array = np.array(depth_image, dtype=np.float32)
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depth_array = np.array(depth_image, dtype=np.float32)
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depth_roi = depth_array[boundingBox.ymin:boundingBox.ymax, boundingBox.xmin:boundingBox.xmax]
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# depth_roi = depth_array[boundingBox.ymin:boundingBox.ymax, boundingBox.xmin:boundingBox.xmax]
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x, y, z = computer_2d_3d(screw_x, screw_y, depth_roi, color_intrinsics)
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x, y, z = computer_2d_3d(screw_x, screw_y, depth_array, color_intrinsics)
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# rospy.loginfo("screw pose: x: %f, y: %f, z: %f", x, y, z)
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# rospy.loginfo("screw pose: x: %f, y: %f, z: %f", x, y, z)
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# calculate normal direction of screw area
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# calculate normal direction of screw area
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p1x, p1y, p1z = computer_2d_3d(boundingBox.xmin-annulus_width, boundingBox.ymin-annulus_width, depth_roi, color_intrinsics)
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box = [boundingBox.ymin - annulus_width, boundingBox.xmin - annulus_width, boundingBox.ymax + annulus_width, boundingBox.xmax + annulus_width]
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p2x, p2y, p2z = computer_2d_3d(boundingBox.xmax+annulus_width, boundingBox.ymin-annulus_width, depth_roi, color_intrinsics)
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# p1x, p1y, p1z = computer_2d_3d(boundingBox.xmin-annulus_width, boundingBox.ymin-annulus_width, depth_array, color_intrinsics)
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p3x, p3y, p3z = computer_2d_3d(boundingBox.xmax+annulus_width, boundingBox.ymax+annulus_width, depth_roi, color_intrinsics)
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# p2x, p2y, p2z = computer_2d_3d(boundingBox.xmax+annulus_width, boundingBox.ymin-annulus_width, depth_array, color_intrinsics)
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p4x, p4y, p4z = computer_2d_3d(boundingBox.xmin-annulus_width, boundingBox.ymax+annulus_width, depth_roi, color_intrinsics)
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# p3x, p3y, p3z = computer_2d_3d(boundingBox.xmax+annulus_width, boundingBox.ymax+annulus_width, depth_array, color_intrinsics)
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p1 = [p1x, p1y, p1z]
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# p4x, p4y, p4z = computer_2d_3d(boundingBox.xmin-annulus_width, boundingBox.ymax+annulus_width, depth_array, color_intrinsics)
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p2 = [p2x, p2y, p2z]
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# p1 = [p1x, p1y, p1z]
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p3 = [p3x, p3y, p3z]
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# p2 = [p2x, p2y, p2z]
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p4 = [p4x, p4y, p4z]
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# p3 = [p3x, p3y, p3z]
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normal = compute_normal_vector(p1, p2, p3, p4)
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# p4 = [p4x, p4y, p4z]
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# normal_q = compute_normal_vector(p1, p2, p3, p4)
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normal_q = compute_plane_normal(box, depth_array, color_intrinsics)
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# annulus_roi = depth_array[boundingBox.ymin-annulus_width:boundingBox.ymax+annulus_width, boundingBox.xmin-annulus_width:boundingBox.xmax+annulus_width]
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# annulus_roi = depth_array[boundingBox.ymin-annulus_width:boundingBox.ymax+annulus_width, boundingBox.xmin-annulus_width:boundingBox.xmax+annulus_width]
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# normal = calculate_image_edge_plane_normal(annulus_roi)
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# normal = calculate_image_edge_plane_normal(annulus_roi)
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@@ -91,14 +133,14 @@ def box_callback(box, depth, color_info):
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# normal vector to quaternion
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# normal vector to quaternion
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screw_quat = tf.transformations.quaternion_from_euler(0, 0, 0)
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screw_quat = tf.transformations.quaternion_from_euler(0, 0, 0)
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screw_quat[0] = normal[0]
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screw_quat[0] = normal_q[0]
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screw_quat[1] = normal[1]
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screw_quat[1] = normal_q[1]
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screw_quat[2] = normal[2]
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screw_quat[2] = normal_q[2]
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screw_quat[3] = 0
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screw_quat[3] = normal_q[3]
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# quaternion to euler
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# quaternion to euler
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screw_euler = tf.transformations.euler_from_quaternion(screw_quat)
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screw_euler = tf.transformations.euler_from_quaternion(screw_quat)
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screw_quat = tf.transformations.quaternion_from_euler(screw_euler[0], screw_euler[1], 0)
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screw_quat_zero_z = tf.transformations.quaternion_from_euler(screw_euler[0], screw_euler[1], 0)
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# Apply low-pass filter to screw quaternion
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# Apply low-pass filter to screw quaternion
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