| # Prerecorded-video example |
|
|
| This example performs object detection on prerecorded video. Video decoding and |
| resizing complete before detection is timed, and annotated-video rendering runs |
| afterward so neither is included in the reported model performance. |
|
|
| The example writes: |
|
|
| - detections and per-frame timings to `examples/video/output/detections.json`; |
| - an annotated video to `examples/video/output/rendered.mp4`. |
|
|
| ## Usage |
|
|
| Run these commands from the `yolo26-raspberry-pi-5/` runtime directory. |
|
|
| ### Prerequisites |
|
|
| Install the required packages: |
|
|
| ```bash |
| sudo apt update |
| sudo apt install --yes --no-install-recommends \ |
| ca-certificates \ |
| curl \ |
| git \ |
| make \ |
| python3 \ |
| python3-venv \ |
| tar \ |
| gzip |
| ``` |
|
|
| ### Using the sample video |
|
|
| The following command downloads a sample video and the pinned standard YOLO26n |
| checkpoint, converts the model, and runs detection on the first 200 frames: |
|
|
| ```bash |
| make example-video |
| ``` |
|
|
| > The input is MediaPipe's object-detection `test_video.mp4`, Copyright 2019 |
| > The MediaPipe Authors, licensed under Apache-2.0. |
| |
| ### Using your own video and model |
| |
| The video must contain at least 200 decodable frames. Convert your model as |
| described in [Acquiring a model](../../README.md#acquiring-a-model), then run: |
| |
| ```bash |
| make example-video VIDEO=/path/to/video.mp4 |
| ``` |
| |
| To use a converted model outside the default `dist/models/` location, set |
| `MODEL` explicitly: |
| |
| ```bash |
| make example-video \ |
| VIDEO=/path/to/video.mp4 \ |
| MODEL=/path/to/converted-model |
| ``` |
| |
