Initial commit

arm_plane_calib/predict_plane_cmd.py

@@ -0,0 +1,152 @@
+#!/usr/bin/env python3
+import yaml
+import cv2
+import numpy as np
+
+import rclpy
+from rclpy.node import Node
+from sensor_msgs.msg import Image, CameraInfo
+from cv_bridge import CvBridge
+
+
+def features(x, y):
+    return np.array([1.0, x, y, x * x, x * y, y * y], dtype=np.float64)
+
+
+class PlaneCmdPredictor(Node):
+    def __init__(self):
+        super().__init__('plane_cmd_predictor')
+
+        self.declare_parameter('color_topic', '/camera/color/image_raw')
+        self.declare_parameter('depth_topic', '/camera/depth/image_raw')
+        self.declare_parameter('camera_info_topic', '/camera/depth/camera_info')
+        self.declare_parameter('model_path', 'model.yaml')
+        self.declare_parameter('depth_scale', 0.001)
+
+        self.color_topic = self.get_parameter('color_topic').value
+        self.depth_topic = self.get_parameter('depth_topic').value
+        self.camera_info_topic = self.get_parameter('camera_info_topic').value
+        self.model_path = self.get_parameter('model_path').value
+        self.depth_scale = float(self.get_parameter('depth_scale').value)
+
+        with open(self.model_path, 'r', encoding='utf-8') as f:
+            model = yaml.safe_load(f)
+
+        self.W = np.array(model['weights'], dtype=np.float64)   # [6, cmd_dim]
+        self.bridge = CvBridge()
+        self.color_img = None
+        self.depth_img = None
+        self.K = None
+
+        # 你的模型输出顺序固定为：6号、5号、4号、3号
+        self.model_servo_order = [6, 5, 4, 3]
+
+        # 你想打印成：3号、4号、5号、6号
+        self.print_servo_order = [3, 4, 5, 6]
+
+        # 当前只处理 3/4/5/6 号舵机，范围都一致
+        self.servo_min = 125
+        self.servo_max = 875
+
+        self.create_subscription(Image, self.color_topic, self.on_color, 10)
+        self.create_subscription(Image, self.depth_topic, self.on_depth, 10)
+        self.create_subscription(CameraInfo, self.camera_info_topic, self.on_info, 10)
+
+        self.window_name = 'predict_plane_cmd'
+        cv2.namedWindow(self.window_name, cv2.WINDOW_NORMAL)
+        cv2.setMouseCallback(self.window_name, self.on_mouse)
+
+    def on_color(self, msg):
+        self.color_img = self.bridge.imgmsg_to_cv2(msg, desired_encoding='bgr8')
+
+    def on_depth(self, msg):
+        self.depth_img = self.bridge.imgmsg_to_cv2(msg, desired_encoding='passthrough')
+
+    def on_info(self, msg):
+        self.K = np.array(msg.k, dtype=np.float64).reshape(3, 3)
+
+    def pixel_to_xyz(self, u, v):
+        if self.depth_img is None or self.K is None:
+            return None
+
+        h, w = self.depth_img.shape[:2]
+        if not (0 <= u < w and 0 <= v < h):
+            return None
+
+        patch = self.depth_img[max(0, v - 2):min(h, v + 3), max(0, u - 2):min(w, u + 3)].astype(np.float32)
+        valid = patch[patch > 0]
+        if valid.size == 0:
+            return None
+
+        z = np.median(valid) * self.depth_scale
+        fx = self.K[0, 0]
+        fy = self.K[1, 1]
+        cx = self.K[0, 2]
+        cy = self.K[1, 2]
+
+        x = (u - cx) * z / fx
+        y = (v - cy) * z / fy
+        return float(x), float(y), float(z)
+
+    def clamp_servo(self, value):
+        value = int(round(value))
+        if value < self.servo_min:
+            value = self.servo_min
+        if value > self.servo_max:
+            value = self.servo_max
+        return value
+
+    def on_mouse(self, event, x, y, flags, param):
+        if event != cv2.EVENT_LBUTTONDOWN:
+            return
+
+        xyz = self.pixel_to_xyz(x, y)
+        if xyz is None:
+            print('[WARN] 无有效深度')
+            return
+
+        X, Y, Z = xyz
+
+        # 模型输出顺序：6,5,4,3
+        cmd_raw = features(X, Y) @ self.W
+        cmd_raw = cmd_raw.tolist()
+
+        # 先取整并限幅
+        cmd_int = [self.clamp_servo(v) for v in cmd_raw]
+
+        # 转成 {舵机ID: 值}
+        servo_map = {}
+        for sid, val in zip(self.model_servo_order, cmd_int):
+            servo_map[sid] = val
+
+        # 按你希望的顺序打印：3,4,5,6
+        ordered_pairs = [(sid, servo_map[sid]) for sid in self.print_servo_order]
+
+        print(f'\n点击像素: ({x}, {y})')
+        print(f'相机坐标: X={X:.4f}, Y={Y:.4f}, Z={Z:.4f}')
+        print('预测机械臂命令向量(按模型顺序 6,5,4,3):',
+              ', '.join([str(servo_map[sid]) for sid in self.model_servo_order]))
+        print('舵机列表:', ','.join([f'{sid}:{val}' for sid, val in ordered_pairs]))
+
+    def spin_loop(self):
+        while rclpy.ok():
+            rclpy.spin_once(self, timeout_sec=0.03)
+            if self.color_img is not None:
+                cv2.imshow(self.window_name, self.color_img)
+            if (cv2.waitKey(1) & 0xFF) == ord('q'):
+                break
+        cv2.destroyAllWindows()
+
+
+def main():
+    rclpy.init()
+    node = PlaneCmdPredictor()
+    try:
+        node.spin_loop()
+    finally:
+        node.destroy_node()
+        rclpy.shutdown()
+
+
+if __name__ == '__main__':
+    main()