Refactor Jupyter notebooks for marker processing: deleted boom.ipynb and compute_3d_maybe.ipynb, added calculate_box_coord_naive.ipynb, calculate_box_face_coord_naive.ipynb, estimate_extrinstic.ipynb, find_aruco_points_with_image.ipynb, find_aruco_points.py, and find_extrinsic_object.py. Updated .gitignore to include new output files.

find_aruco_points.py

@@ -0,0 +1,83 @@
+import cv2
+from cv2 import aruco
+from datetime import datetime
+from loguru import logger
+from pathlib import Path
+from typing import cast, Final
+import awkward as ak
+from cv2.typing import MatLike
+import numpy as np
+
+NDArray = np.ndarray
+CALIBRATION_PARQUET = Path("output") / "usbcam_cal.parquet"
+# 7x7
+DICTIONARY: Final[int] = aruco.DICT_7X7_1000
+# 400mm
+MARKER_LENGTH: Final[float] = 0.4
+RED = (0, 0, 255)
+GREEN = (0, 255, 0)
+BLUE = (255, 0, 0)
+YELLOW = (0, 255, 255)
+
+
+def gen():
+    API = cv2.CAP_AVFOUNDATION
+    cap = cv2.VideoCapture(0, API)
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            logger.warning("Failed to grab frame")
+            break
+        yield frame
+
+
+def main():
+    aruco_dict = aruco.getPredefinedDictionary(DICTIONARY)
+    cal = ak.from_parquet(CALIBRATION_PARQUET)[0]
+    camera_matrix = cast(MatLike, ak.to_numpy(cal["camera_matrix"]))
+    distortion_coefficients = cast(MatLike, ak.to_numpy(cal["distortion_coefficients"]))
+    detector = aruco.ArucoDetector(
+        dictionary=aruco_dict, detectorParams=aruco.DetectorParameters()
+    )
+
+    for frame in gen():
+        grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        # pylint: disable-next=unpacking-non-sequence
+        markers, ids, rejected = detector.detectMarkers(grey)
+        # `markers` is [N, 1, 4, 2]
+        # `ids` is [N, 1]
+        if ids is not None:
+            markers = np.reshape(markers, (-1, 4, 2))
+            ids = np.reshape(ids, (-1, 1))
+            # logger.info("markers={}, ids={}", np.array(markers).shape, np.array(ids).shape)
+            for m, i in zip(markers, ids):
+                center = np.mean(m, axis=0).astype(int)
+                logger.info("id={}, center={}", i, center)
+                cv2.circle(frame, tuple(center), 5, RED, -1)
+                cv2.putText(
+                    frame,
+                    str(i),
+                    tuple(center),
+                    cv2.FONT_HERSHEY_SIMPLEX,
+                    1,
+                    RED,
+                    2,
+                )
+                # BGR
+                color_map = [RED, GREEN, BLUE, YELLOW]
+                for color, corners in zip(color_map, m):
+                    corners = corners.astype(int)
+                    frame = cv2.circle(frame, corners, 5, color, -1)
+        cv2.imshow("frame", frame)
+        if (k := cv2.waitKey(1)) == ord("q"):
+            logger.info("Exiting")
+            break
+        elif k == ord("s"):
+            now = datetime.now().strftime("%Y%m%d%H%M%S")
+            file_name = f"aruco_{now}.png"
+            logger.info("Saving to {}", file_name)
+            cv2.imwrite(file_name, frame)
+
+
+if __name__ == "__main__":
+    main()