# 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`](https://github.com/dora-rs/dora-hub/tree/main/node-hub/opencv-plot) from dora-hub, brought up to the dora 1.0 node contract and packaged with `uv`. ## Usage Add to your dataflow: ```yaml 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`](dataflow.yml) is self-contained. [`examples/source.py`](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: ```bash 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: ```bash 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`](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 **`image`** event decodes the frame and immediately redraws: it draws every stored bbox (green rectangle plus `label, conf` text), draws the stored text at the top left, resizes to `VIEW_WIDTH`x`VIEW_HEIGHT` if both are set, and shows it in a window titled `Dora Node: dora-image-view`. Press `q` in the window to quit. - A **`bbox`** or **`text`** event only updates stored state; it is drawn on the next `image` redraw. 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`). ```python 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 ```bash 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 ```bash 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.