更新手眼标定文件

mycobot_280/mycobot_280/camera_calibration/camera_calibration.py

@@ -4,11 +4,23 @@
 import numpy as np
 import json
 import time
+import os
 from scipy.linalg import svd
 from pymycobot import *
+from marker_utils import *
+import shutil
+import glob
 
 
-mc = MyCobot("/dev/ttyUSB0")  # 设置端口
+ports = glob.glob('/dev/ttyUSB*') + glob.glob('/dev/ttyACM*')
+print(ports)
+if ports:
+    arm_port = ports[0]
+else:
+    raise Exception("No MyCobot device found")
+
+
+mc = MyCobot(port=arm_port)  # 设置端口
 
 np.set_printoptions(suppress=True, formatter={'float_kind': '{:.2f}'.format})
 
@@ -29,13 +41,23 @@ def __init__(self, camera_id, marker_size, mtx, dist):
 
         # Initialize EyesInHand_matrix to None or load from a document if available
         self.EyesInHand_matrix = None
+        file_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+        self.matrix_file_path = os.path.join(file_dir, "config","EyesInHand_matrix.json")
+
         self.load_matrix()
 
     def save_matrix(self, filename="EyesInHand_matrix.json"):
         # Save the EyesInHand_matrix to a JSON file
         if self.EyesInHand_matrix is not None:
             with open(filename, 'w') as f:
                 json.dump(self.EyesInHand_matrix.tolist(), f)
+
+            try:
+                # 复制文件到目标路径
+                shutil.copy(filename, self.matrix_file_path)
+                print(f"File copied to {self.matrix_file_path}")
+            except IOError as e:
+                print(f"Failed to copy file: {e}")
 
     def load_matrix(self, filename="EyesInHand_matrix.json"):
         # Load the EyesInHand_matrix from a JSON file, if it exists

mycobot_280/mycobot_280/camera_calibration/marker_utils.py

@@ -0,0 +1,59 @@
+import cv2
+import numpy as np
+import typing as T
+from numpy.typing import NDArray, ArrayLike
+
+
+class MarkerInfo(T.TypedDict):
+    corners: np.ndarray
+    tvec: np.ndarray
+    rvec: np.ndarray
+    num_id: int
+
+
+def solve_marker_pnp(corners: NDArray, marker_size: int, mtx: NDArray, dist: NDArray):
+    """
+    This will estimate the rvec and tvec for each of the marker corners detected by:
+       corners, ids, rejectedImgPoints = detector.detectMarkers(image)
+    corners - is an array of detected corners for each detected marker in the image
+    marker_size - is the size of the detected markers
+    mtx - is the camera matrix
+    distortion - is the camera distortion matrix
+    RETURN list of rvecs, tvecs, and trash (so that it corresponds to the old estimatePoseSingleMarkers())
+    """
+    marker_points = np.array(
+        [
+            [-marker_size / 2, marker_size / 2, 0],
+            [marker_size / 2, marker_size / 2, 0],
+            [marker_size / 2, -marker_size / 2, 0],
+            [-marker_size / 2, -marker_size / 2, 0],
+        ],
+        dtype=np.float32,
+    )
+    rvecs = []
+    tvecs = []
+    for corner in corners:
+        retval, rvec, tvec = cv2.solvePnP(
+            marker_points,
+            corner,
+            mtx,
+            dist,
+            flags=cv2.SOLVEPNP_IPPE_SQUARE,
+        )
+        if retval:
+            rvecs.append(rvec)
+            tvecs.append(tvec)
+
+    rvecs = np.array(rvecs)  # type: ignore
+    tvecs = np.array(tvecs)  # type: ignore
+    (rvecs - tvecs).any()  # type: ignore
+    return rvecs, tvecs
+
+
+def draw_marker(frame: np.ndarray, corners, tvecs, rvecs, ids, mtx, dist) -> None:
+    # cv2.aruco.drawDetectedMarkers(frame, corners, None, borderColor=(0, 255, 0))
+    cv2.aruco.drawDetectedMarkers(frame, corners, ids, borderColor=(0, 200, 200))
+    for i in range(len(ids)):
+        corner, tvec, rvec, marker_id = corners[i], tvecs[i], rvecs[i], ids[i]
+        cv2.drawFrameAxes(frame, mtx, dist, rvec, tvec, 60, 2)
+