New face detection example based on MediaPipe

examples/manifest.yml

@@ -132,3 +132,6 @@ root:
         - name: tracking-hf-opencv
           python: python/tracking_hf_opencv
 
+        - name: human-face-tracking
+          python: python/human_face_tracking
+

examples/python/human_face_tracking/.gitignore

@@ -0,0 +1,2 @@
+dataset/
+model/

examples/python/human_face_tracking/README.md

@@ -0,0 +1,49 @@
+---
+title: Human Face Tracking
+python: https://github.com/rerun-io/rerun/tree/latest/examples/python/human_face_tracking/main.py
+tags: [media-pipe, face-tracking, live, camera, 2d, 3d]
+---
+
+![mp_face example screenshot](https://static.rerun.io/6efefd1de7c63166c4d99956711b6367206d9835_mp_face.png)
+
+Use the [MediaPipe](https://google.github.io/mediapipe/) Face Detector and Landmarker solutions to detect and track a human face in image, videos, and camera stream.
+
+```bash
+pip install -r examples/python/mp_face/requirements.txt
+python examples/python/mp_face/main.py
+```
+
+## Usage
+
+CLI usage help is available using the `--help` option:
+
+```
+$ python examples/python/mp_face/main.py --help
+usage: main.py [-h] [--demo-image] [--image IMAGE] [--video VIDEO] [--camera CAMERA] [--max-frame MAX_FRAME] [--max-dim MAX_DIM] [--num-faces NUM_FACES] [--headless] [--connect] [--serve] [--addr ADDR] [--save SAVE]
+
+Uses the MediaPipe Face Detection to track a human pose in video.
+
+options:
+  -h, --help            show this help message and exit
+  --demo-image          Run on a demo image automatically downloaded
+  --image IMAGE         Run on the provided image
+  --video VIDEO         Run on the provided video file.
+  --camera CAMERA       Run from the camera stream (parameter is the camera ID, usually 0
+  --max-frame MAX_FRAME
+                        Stop after processing this many frames. If not specified, will run until interrupted.
+  --max-dim MAX_DIM     Resize the image such as its maximum dimension is not larger than this value.
+  --num-faces NUM_FACES
+                        Max number of faces detected by the landmark model (temporal smoothing is applied only for a value of 1).
+  --headless            Don't show GUI
+  --connect             Connect to an external viewer
+  --serve               Serve a web viewer (WARNING: experimental feature)
+  --addr ADDR           Connect to this ip:port
+  --save SAVE           Save data to a .rrd file at this path
+```
+
+Here is an overview of the options specific to this example:
+
+- *Running modes*: By default, this example streams images from the default webcam. Another webcam can be used by providing a camera index with the `--camera` option. Alternatively, images can be read from a video file (using `--video PATH`) or a single image file (using `--image PATH`). Also, a demo image with two faces can be automatically downloaded and used with `--demo-image`.
+- *Max face count*: The maximum face detected by MediaPipe Face Landmarker can be set using `--num-faces NUM`. It defaults to 1, in which case the Landmarker applies temporal smoothing. This parameter doesn't affect MediaPipe Face Detector, which always attempts to detect all faces present in the input images.
+- *Image downscaling*: By default, this example logs and runs on the native resolution of the provided images. Input images can be downscaled to a given maximum dimension using `--max-dim DIM`.
+- *Limiting frame count*: When running from a webcam or a video file, this example can be set to stop after a given number of frames using `--max-frame MAX_FRAME`.