chore: import upstream snapshot with attribution

2026-07-13 13:05:14 +08:00
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+<!--[metadata]
+title = "Live camera edge detection"
+tags = ["2D", "Canny", "Live", "OpenCV"]
+thumbnail = "https://static.rerun.io/live-camera-edge-detection/f747bcf9ff3039c895f0bf0290e2dea0a72631ea/480w.png"
+thumbnail_dimensions = [480, 480]
+-->
+
+Visualize the [OpenCV Canny Edge Detection](https://docs.opencv.org/4.x/da/d22/tutorial_py_canny.html) results from a live camera stream.
+
+<picture>
+  <source media="(max-width: 480px)" srcset="https://static.rerun.io/live_camera_edge_detection/bf877bffd225f6c62cae3b87eecbc8e247abb202/480w.png">
+  <source media="(max-width: 768px)" srcset="https://static.rerun.io/live_camera_edge_detection/bf877bffd225f6c62cae3b87eecbc8e247abb202/768w.png">
+  <source media="(max-width: 1024px)" srcset="https://static.rerun.io/live_camera_edge_detection/bf877bffd225f6c62cae3b87eecbc8e247abb202/1024w.png">
+  <source media="(max-width: 1200px)" srcset="https://static.rerun.io/live_camera_edge_detection/bf877bffd225f6c62cae3b87eecbc8e247abb202/1200w.png">
+  <img src="https://static.rerun.io/live_camera_edge_detection/bf877bffd225f6c62cae3b87eecbc8e247abb202/full.png" alt="Live Camera Edge Detection example screenshot">
+</picture>
+
+## Used Rerun types
+[`Image`](https://www.rerun.io/docs/reference/types/archetypes/image)
+
+## Background
+In this example, the results of the [OpenCV Canny Edge Detection](https://docs.opencv.org/4.x/da/d22/tutorial_py_canny.html) algorithm are visualized.
+Canny Edge Detection is a popular edge detection algorithm, and can efficiently extract important structural information from visual objects while notably reducing the computational load.
+The process in this example involves converting the input image to RGB, then to grayscale, and finally applying the Canny Edge Detector for precise edge detection.
+
+## Logging and visualizing with Rerun
+
+The visualization in this example were created with the following Rerun code:
+### RGB image
+
+The original image is read and logged in RGB format under the entity "image/rgb".
+```python
+# Log the original image
+rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+rr.log("image/rgb", rr.Image(rgb))
+```
+
+### Grayscale image
+
+The input image is converted from BGR color space to grayscale, and the resulting grayscale image is logged under the entity "image/gray".
+```python
+# Convert to grayscale
+gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+rr.log("image/gray", rr.Image(gray))
+```
+
+### Canny edge detection image
+
+The Canny edge detector is applied to the grayscale image, and the resulting edge-detected image is logged under the entity "image/canny".
+```python
+# Run the canny edge detector
+canny = cv2.Canny(gray, 50, 200)
+rr.log("image/canny", rr.Image(canny))
+```
+
+
+## Run the code
+To run this example, make sure you have the Rerun repository checked out and the latest SDK installed:
+```bash
+pip install --upgrade rerun-sdk  # install the latest Rerun SDK
+git clone git@github.com:rerun-io/rerun.git  # Clone the repository
+cd rerun
+git checkout latest  # Check out the commit matching the latest SDK release
+```
+Install the necessary libraries specified in the requirements file:
+```bash
+pip install -e examples/python/live_camera_edge_detection
+```
+To experiment with the provided example, simply execute the main Python script:
+```bash
+python -m live_camera_edge_detection # run the example
+```
+If you wish to customize it, explore additional features, or save it use the CLI with the `--help` option for guidance:
+```bash
+python -m live_camera_edge_detection --help
+```