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The build command was `pip install .`, which is what upstream and the dora docs use because `--uv` rewrites it. Spelling it `uv pip install .` means the dataflow never installs through pip at all, whether or not `--uv` was passed. The cost is that the node then needs a virtualenv to install into, so it must be run with `--uv`; the README says so. The second dataflow is gone. It existed to wire this node into dora-image-view just to see the frames, which pulled another repository over the network and needed a tag there. PREVIEW=true now opens a local window of the frames as they are published, so checking a camera, an encoding or a flip needs this repository alone. It shows the frame after the flip and the resize, so what is on screen is what is sent, and it never opens under CI, where there is no display. That a source node can display its own output overlaps with what a viewer node does. The overlap is the point: the alternative was a second repository in the loop before you can tell whether a camera works.
122 lines
4.1 KiB
Markdown
122 lines
4.1 KiB
Markdown
# dora-webcam
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Dora node that captures frames from a webcam and publishes them as
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`std/media/v1/Image`. A source for a vision pipeline: it takes a tick and produces
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frames.
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Based on [`opencv-video-capture`](https://github.com/dora-rs/dora-hub/tree/main/node-hub/opencv-video-capture)
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from dora-hub, brought up to the dora 1.0 node contract, narrowed to Linux camera
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selection, and changed to publish the typed Arrow image struct rather than a flat
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buffer plus metadata.
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## Usage
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Add to your dataflow:
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```yaml
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nodes:
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- id: camera
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git: ssh://git@gitea.liria.cl:5001/liria/dora-webcam.git
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tag: v0.1.0
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build: uv pip install .
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path: dora-webcam
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inputs:
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tick: dora/timer/millis/33
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outputs:
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- image
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```
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Run the dataflow with `--uv` (`dora run dataflow.yml --uv`): the build command is
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`uv pip install .`, so the node gets its own managed environment and never installs into
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an ambient one.
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### Runnable dataflow
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[`dataflow.yml`](dataflow.yml) is the camera on its own, and is what CI runs:
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```bash
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dora run dataflow.yml --uv
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```
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Nothing consumes the frames, so to actually see them set `PREVIEW`:
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```bash
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PREVIEW=true dora run dataflow.yml --uv
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```
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A window opens showing the frames as they are published. Press `q` to stop. That is
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enough to check a camera, an encoding or a flip without wiring a second node — which is
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why there is one dataflow here rather than one per consumer.
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For a real pipeline, wire `image` into a viewer such as `dora-image-view` from your own
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dataflow.
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## Output
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| Output | Payload | Metadata |
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|---|---|---|
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| `image` | `std/media/v1/Image` struct | none — the struct describes itself |
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The struct carries `width: UInt32`, `height: UInt32`, `encoding: Utf8` and
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`data: LargeBinary`, so a receiver needs nothing from the message metadata. For a
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compressed encoding, `width` and `height` are the image's dimensions, not the length of
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`data`.
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## Inputs
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| Input | Description |
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|---|---|
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| `tick` | Publishes one frame. Wire to `dora/timer/millis/N`; the node stops when it closes. |
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## Environment variables
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| Variable | Default | Meaning |
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| `CAMERA_ID` | unset | Substring of a `/dev/v4l/by-id/` entry. Wins over `CAPTURE_PATH`. |
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| `CAPTURE_PATH` | `0` | Device path (`/dev/video1`) or index. A numeric string is an index. |
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| `IMAGE_WIDTH` | native | Requested capture width; frames are also resized to it. |
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| `IMAGE_HEIGHT` | native | Requested capture height; frames are also resized to it. |
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| `ENCODING` | `bgr8` | One of `bgr8`, `rgb8`, `yuv420`, `jpeg`/`jpg`/`jpe`, `png`, `bmp`, `webp`. |
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| `JPEG_QUALITY` | `95` | Quality 0-100, used only by the JPEG encodings. |
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| `FLIP` | unset | `VERTICAL`, `HORIZONTAL` or `BOTH`. |
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| `PREVIEW` | unset | `true` opens a window of the published frames; `q` stops the node. |
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| `CAPTURE_FRAMES` | `0` | Stop after this many frames. 0 runs until the tick closes. |
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Resizing only happens when both `IMAGE_WIDTH` and `IMAGE_HEIGHT` are set.
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`CAMERA_ID` is worth preferring on a robot: a by-id name is stable across reboots and
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across which USB port the camera is in, and an index is not.
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`CI=true` makes a failed read publish a labelled black frame instead of raising, which
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is what lets the dataflow run on a machine with no camera. It is not a configuration
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knob.
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## Build
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```bash
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uv sync
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```
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Every dependency ships prebuilt wheels for linux-x86_64, linux-aarch64 and macos-arm64,
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so the node installs with no system packages and no compiler.
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**Requirements:** dora 1.0+ (verified with `dora-cli 1.0.1`), Python 3.11+, `uv`, and a
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V4L2 camera. `PREVIEW` also needs a display. On a bare Linux image `opencv-python` needs
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the libGL shared libraries (`libgl1`, `libglib2.0-0`), which it links at import time.
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## Test
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```bash
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uv run pytest
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```
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Unit tests over device resolution, encoding and the image struct; they need neither a
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camera nor a dataflow. The headless `dataflow.yml` run covers the wiring and the event
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loop.
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## Camera selection on other platforms
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Selecting by `CAMERA_ID` reads `/dev/v4l/by-id/`, so it is Linux only. Upstream also
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enumerates cameras through macOS `system_profiler` and Windows PowerShell; that is not
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carried here. `CAPTURE_PATH` works everywhere.
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