Samples: Automatic updates to public repository

README.md

@@ -112,8 +112,6 @@ from the camera can be used.
           - [get\_checkerboard\_pose\_from\_zdf](https://github.com/zivid/zivid-python-samples/tree/master/source/applications/advanced/get_checkerboard_pose_from_zdf.py) - Read point cloud data of a Zivid calibration board from a
             ZDF file, estimate the
           - [hand\_eye\_calibration](https://github.com/zivid/zivid-python-samples/tree/master/source/applications/advanced/hand_eye_calibration/hand_eye_calibration.py) - Perform Hand-Eye calibration.
-          - [mask\_point\_cloud](https://github.com/zivid/zivid-python-samples/tree/master/source/applications/advanced/mask_point_cloud.py) - Read point cloud data from a ZDF file, apply a binary
-            mask, and visualize it.
           - [project\_and\_find\_marker](https://github.com/zivid/zivid-python-samples/tree/master/source/applications/advanced/project_and_find_marker.py) - Show a marker using the projector, capture a set of 2D
             images to find the marker coordinates (2D and 3D).
           - [read\_project\_and\_capture\_image](https://github.com/zivid/zivid-python-samples/tree/master/source/applications/advanced/read_project_and_capture_image.py) - Read a 2D image from file and project it using the camera
@@ -205,10 +203,10 @@ Note that Open3D is not available for Python 3.13 and later.
 -----
 
 1.  [Install Zivid
-    Software](https://support.zivid.com/latest//getting-started/software-installation.html).
+    Software](https://support.zivid.com/en/latest//camera/getting-started/software-installation.html).
 
 2.  [Download Zivid Sample
-    Data](https://support.zivid.com/latest//api-reference/samples/sample-data.html).
+    Data](https://support.zivid.com/en/latest//camera/api-reference/samples/sample-data.html).
 
 3.  Check out the Zivid Python samples repository:
 
@@ -252,9 +250,9 @@ Note that Open3D is not available for Python 3.13 and later.
 ## Support
 
 For more information about the Zivid cameras, please visit our
-[Knowledge Base](https://support.zivid.com/latest). If you run into any
-issues please check out
-[Troubleshooting](https://support.zivid.com/latest/support/troubleshooting.html).
+[Knowledge Base](https://support.zivid.com/en/latest). If you run into
+any issues please check out
+[Troubleshooting](https://support.zivid.com/en/latest/camera/support/troubleshooting.html).
 
 ## License
 

modules/zividsamples/color_to_grayscale.py

@@ -21,24 +21,3 @@ def convert_rgba_to_grayscale(rgba_image: np.ndarray) -> np.ndarray:
     if rgba_image.ndim != 3 or rgba_image.shape[2] != 4:
         raise ValueError("Input image must be a RGBA image.")
     return np.dot(rgba_image[..., :3], [0.299, 0.587, 0.114])
-
-
-def convert_bgra_to_grayscale(bgra_image: np.ndarray) -> np.ndarray:
-    """Convert BGRA image to grayscale using the luminance method.
-
-    The luminance method uses the formula:
-    Y = 0.299 * R + 0.587 * G + 0.114 * B
-    where R, G, B are the red, green, and blue channels of the image.
-
-    Args:
-        bgra_image (numpy.ndarray): Input BGRA image.
-
-    Raises:
-        ValueError: If the input image is not a BGRA image.
-
-    Returns:
-        numpy.ndarray: Grayscale image.
-    """
-    if bgra_image.ndim != 3 or bgra_image.shape[2] != 4:
-        raise ValueError("Input image must be a BGRA image.")
-    return np.dot(bgra_image[..., :3], [0.114, 0.587, 0.299])

modules/zividsamples/gui/calibration/pose_pair_selection_widget.py

@@ -175,13 +175,6 @@ def _translation_to_string(self, translation: NDArray[Shape["3"], Float32]) -> s
         return f"{translation[0]:>8.1f}, {translation[1]:>8.1f}, {translation[2]:.1f}"
 
 
-def directory_has_pose_pair_data(directory: Path) -> bool:
-    return (
-        len(list(directory.glob("robot_pose_*.yaml"))) > 0
-        and len(list(directory.glob("calibration_object_pose_*.zdf"))) > 0
-    )
-
-
 class _PosePairLoadWorker(QObject):
     """Loads pose pair data from disk in a background thread."""
 

modules/zividsamples/gui/preparation/warmup_gui.py

@@ -292,16 +292,24 @@ def rate_of_change_data(self) -> NDArray[Shape["N"], Float32]:  # type: ignore
         return self.df["average_rate_of_change"].to_numpy()
 
     def temperature_is_stable(self) -> bool:
+        if not self.has_enough_data_to_analyze():
+            return False
+
+        # Ensure minimum warmup time of 1 minute has passed
         now = self.df["timestamp"].iloc[-1]
+        warmup_start_time = self.df["timestamp"].iloc[0]
+        elapsed_time = now - warmup_start_time
+        if elapsed_time < timedelta(minutes=1):
+            return False
+
         one_minute_ago = now - timedelta(minutes=1)
         last_minute_of_data = self.df[self.df["timestamp"] >= one_minute_ago]
-        max_rate_of_change_in_the_last_minute = last_minute_of_data["average_rate_of_change"].max()
-        if self.has_enough_data_to_analyze():
-            return (
-                self.df["average_rate_of_change"].iloc[-1] is not None
-                and max_rate_of_change_in_the_last_minute <= self.temperature_change_threshold_degrees_per_minute
-            )
-        return False
+        max_rate_of_change_in_the_last_minute = float(last_minute_of_data["average_rate_of_change"].max())
+
+        return (
+            self.df["average_rate_of_change"].iloc[-1] is not None
+            and max_rate_of_change_in_the_last_minute <= self.temperature_change_threshold_degrees_per_minute
+        )
 
     def temperature_is_changing_fast(self) -> bool:
         return self.df["average_rate_of_change"].iloc[-1] > 2 * self.temperature_change_threshold_degrees_per_minute

modules/zividsamples/gui/widgets/image_viewer.py

@@ -1,17 +1,6 @@
-from PyQt5.QtCore import QRectF, QSize, Qt, pyqtSlot
+from PyQt5.QtCore import QRectF, Qt, pyqtSlot
 from PyQt5.QtGui import QImage, QPainter, QPixmap
 from PyQt5.QtWidgets import QDialog, QGraphicsPixmapItem, QGraphicsScene, QGraphicsView, QVBoxLayout
-from zividsamples.gui.qt_application import ZividColors, color_as_qcolor
-
-
-def error_message_pixmap(error_message: str, size: QSize) -> QPixmap:
-    error_pixmap = QPixmap(size)
-    error_pixmap.fill(color_as_qcolor(ZividColors.ITEM_BACKGROUND, 0.5))
-    painter = QPainter(error_pixmap)
-    painter.setPen(color_as_qcolor(ZividColors.PINK, 1))
-    painter.drawText(error_pixmap.rect(), Qt.AlignCenter | Qt.TextWordWrap, error_message)
-    painter.end()
-    return error_pixmap
 
 
 class ImageViewer(QGraphicsView):

modules/zividsamples/gui/widgets/live_2d_widget.py

@@ -61,7 +61,7 @@ def update_exposure_based_on_relative_brightness(self, settings_2d: zivid.Settin
         rgba_with_projector = self.capture_function(settings_2d).image_srgb().copy_data()
         grayscale_with_projector = self.rgb_to_grayscale(rgba_with_projector)
         for acquisition in settings_2d.acquisitions:
-            acquisition.brightness = 0.0
+            acquisition.brightness = 0.1
         rgba_without_projector = self.capture_function(settings_2d).image_srgb().copy_data()
         grayscale_without_projector = self.rgb_to_grayscale(rgba_without_projector)
         grayscale_without_projector[grayscale_without_projector == 0] = np.nan
@@ -82,7 +82,7 @@ def update_exposure_based_on_relative_brightness(self, settings_2d: zivid.Settin
                 else relative_brightness / (exposure_increase / current_exposure_time)
             )
             acquisition.gain = max(1.0, min(acquisition.gain * remaining_relative_brightness, 16.0))
-            acquisition.brightness = 0.0
+            acquisition.brightness = 0.1
         return settings_2d
 
     def update_settings_2d(self, settings_2d: zivid.Settings2D, camera_model: str):

modules/zividsamples/gui/widgets/pose_widget.py

@@ -21,21 +21,6 @@
 from zividsamples.transformation_matrix import TransformationMatrix
 
 
-def wrap_path(path: Path, wrap_length: int) -> str:
-    parts = path.parts  # Get parts of the Path
-    wrapped_lines = []
-    current_line = parts[0]
-    divider = "/" if current_line.endswith(":") else "\\"
-    for part in parts[1:]:
-        if len(f"{current_line}{divider}{part}") > wrap_length:
-            wrapped_lines.append(f"{current_line}{divider}")
-            current_line = part
-        else:
-            current_line = f"{current_line}{divider}{part}"
-    wrapped_lines.append(current_line)
-    return "\n".join(wrapped_lines)
-
-
 class PoseWidgetDisplayMode(Enum):
     OnlyPose = 0
     Basic = 1

modules/zividsamples/gui/wizard/marker_configuration.py

@@ -2,7 +2,7 @@
 from typing import Dict, List, Optional
 
 import numpy as np
-from nptyping import Float32, NDArray, Shape, UInt8
+from nptyping import NDArray, Shape, UInt8
 from PyQt5.QtCore import QRegExp, QSettings
 from PyQt5.QtGui import QImage, QPixmap, QValidator
 from PyQt5.QtWidgets import (
@@ -16,7 +16,6 @@
     QVBoxLayout,
     QWidget,
 )
-from scipy.spatial.transform import Rotation
 from zivid.calibration import MarkerDictionary, MarkerShape
 from zivid.experimental import PixelMapping
 from zividsamples.gui.qt_application import ZividQtApplication
@@ -35,12 +34,6 @@ def generate_marker_dictionary(markers: List[MarkerShape]) -> Dict[str, MarkerSh
     return marker_dict
 
 
-def marker_angle(rotation_matrix: NDArray[Shape["3, 3"], Float32]) -> float:  # type: ignore
-    rotation = Rotation.from_matrix(rotation_matrix)
-    rotvec = rotation.as_rotvec()
-    return np.degrees(np.linalg.norm(rotvec))
-
-
 class TouchMarkerWidget(QWidget):
     marker_id: int = 1
     marker_dictionary: str = MarkerDictionary.aruco4x4_50

source/applications/advanced/stitch_using_robot_mounted_camera.py

@@ -56,6 +56,7 @@ def _options() -> argparse.Namespace:
     parser.add_argument(
         "--full-resolution",
         action="store_true",
+        default=False,
         help="Use full resolution for stitching. If not set, downsampling is applied.",
     )
 
@@ -77,8 +78,8 @@ def _stitch_point_clouds(directory: Path, full_resolution: bool) -> zivid.Unorga
         ValueError: If the number of ZDF files and robot pose files do not match.
 
     """
-    zdf_files = list(directory.rglob("capture_*.zdf"))
-    pose_files = list(directory.rglob("robot_pose_*.yaml"))
+    zdf_files = sorted(list(directory.rglob("capture_*.zdf")))
+    pose_files = sorted(list(directory.rglob("robot_pose_*.yaml")))
 
     if not zdf_files or not pose_files or not (directory / "hand_eye_transform.yaml").exists():
         raise FileNotFoundError("Required files are missing in the directory.")