The repository, the Python package, the entrypoint and the manifest name all now agree. `plot` was carried over from the upstream opencv-plot node and no longer described anything here, so the module, the class and the environment variables follow the node: dora_plot/ -> dora_image_view/ dora_plot/plot.py -> dora_image_view/view.py Plot -> View PLOT_WIDTH/HEIGHT -> VIEW_WIDTH/HEIGHT --plot-width/-height -> --view-width/-height Breaking for anyone wiring `path: dora-plot` or setting PLOT_WIDTH; nothing is tagged yet.
dora-image-view
Dora node that overlays bounding boxes, labels and text on an image input and displays it in an OpenCV window. A display sink for debugging a vision pipeline: it produces no outputs.
Based on opencv-plot
from dora-hub, brought up to the dora 1.0 node contract and packaged with uv.
Usage
Add to your dataflow:
nodes:
- id: view
git: ssh://git@gitea.liria.cl:5001/liria/dora-image-view.git
tag: v0.1.0
build: pip install .
path: dora-image-view
inputs:
image: camera/image
bbox: detector/bbox
text: detector/text
Run the dataflow with --uv (dora run dataflow.yml --uv) so the node gets its own
managed environment.
Wire image from any node publishing one of the encodings below, and bbox from any
detector publishing the struct below. Both inputs are optional: an image alone is a
plain viewer.
Runnable example
dataflow.yml is self-contained. examples/source.py
is a synthetic source node that emits an animated frame, the box around the square
moving in it, and a caption — the three inputs this node draws — so the example needs
no camera, no detector and no network:
dora run dataflow.yml --uv
A window opens with a square bouncing across a gradient, boxed and labelled. Press q
to quit.
It builds both nodes from this checkout (path: + build:) rather than from a tag,
which is what lets dora validate pick up the manifest described below.
Set SOURCE_FRAMES to stop the source after a fixed number of frames instead of running
until you quit; that plus CI=true is how the same dataflow runs headless as a test:
CI=true SOURCE_FRAMES=30 dora run dataflow.yml --uv
SOURCE_WIDTH and SOURCE_HEIGHT (default 640x480) set the frame size.
Node manifest
dora-node.yml declares the node's inputs with type URNs. No source
package is shared between node repositories, so it is the only contract a consumer has,
and it is what makes a wiring mistake fail at build time instead of at runtime. The
example source has a manifest of its own, so dora validate checks the two against
each other:
$ dora validate dataflow.yml
node "source": injected 2 contract type(s) from .../examples/dora-node.yml
node "view": injected 2 contract type(s) from .../dora-node.yml
All type annotations OK.
image is std/core/v1/UInt8 and text is std/core/v1/String; the payloads are raw
buffers described by their metadata, so the URN names the element type rather than a
struct. bbox is deliberately left untyped — senders disagree on whether its numeric
fields are 32- or 64-bit, and the node reads either.
Behavior
The node keeps a current frame, bbox set and text string. Each input updates its slice of that state:
- An
imageevent decodes the frame and immediately redraws: it draws every stored bbox (green rectangle pluslabel, conftext), draws the stored text at the top left, resizes toVIEW_WIDTHxVIEW_HEIGHTif both are set, and shows it in a window titledDora Node: dora-image-view. Pressqin the window to quit. - A
bboxortextevent only updates stored state; it is drawn on the nextimageredraw.
Setting CI=true suppresses the display: the node still decodes every input but opens
no window. That is what makes it safe to run in a pipeline test.
Inputs
| Input | Payload | Metadata |
|---|---|---|
image |
Flat UInt8 array |
width, height, encoding |
bbox |
Arrow struct array, element [0] with fields bbox, conf, labels |
format |
text |
Arrow array of size 1 | — |
Supported encoding values: bgr8, rgb8, jpeg/jpg/jpe/bmp/webp/png
(encoded byte stream), yuv420, avif. width and height are only needed by the raw
encodings — the rest carry their own dimensions. An unsupported encoding raises.
Supported format values: xyxy and xywh (centre-based, converted to xyxy).
node.send_output("image", pa.array(frame.ravel()),
{"width": 640, "height": 480, "encoding": "bgr8"})
node.send_output("bbox", pa.array([{
"bbox": np.array([...]), # flattened, four values per box
"conf": np.array([...]),
"labels": np.array([...]),
}]), {"format": "xyxy"})
node.send_output("text", pa.array(["hello"]))
Outputs
None — it is a display sink.
Environment variables
| Variable | Default | Meaning |
|---|---|---|
VIEW_WIDTH |
image width | Resize the displayed frame to this width, in pixels. |
VIEW_HEIGHT |
image height | Resize the displayed frame to this height, in pixels. |
Resizing only happens when both are set. Both are also available as --view-width and
--view-height; the environment variable wins when both are given.
CI=true suppresses the display window; it is not a configuration knob.
Build
uv sync
Every dependency ships prebuilt wheels for linux-x86_64, linux-aarch64 and macos-arm64,
so the node installs with no system packages and no compiler on any of them — including
AVIF support, which comes from pillow-avif-plugin rather than OpenCV.
Requirements: dora 1.0+ (verified with dora-cli 1.0.1), Python 3.11+, uv, and a
display to show the window on (or CI=true to run without one). On a bare Linux image
opencv-python also needs the libGL shared libraries (libgl1, libglib2.0-0), which
it links at import time.
Test
uv run pytest
Unit tests over decoding, the bbox format conversion and the headless draw path; they need neither a camera, a dataflow nor a display. The headless dataflow run above covers the rest — the manifest, the wiring and the event loop.