cesar
43cb1ff01c
A display sink that overlays bounding boxes and text on an image input and shows it in an OpenCV window. Based on opencv-plot from dora-hub, brought up to the dora 1.0 node contract and packaged with uv. Python rather than Rust: the opencv Rust crate generates its bindings from the OpenCV headers on the build machine, so it needs libopencv-dev and libclang-dev per machine and per architecture and does not cross-compile. Every dependency here ships prebuilt wheels for linux-x86_64, linux-aarch64 and macos-arm64. Covers every encoding the upstream node did — bgr8, rgb8, jpeg/jpg/jpe/bmp/ webp/png, yuv420 and avif — plus both bbox formats, the text overlay, PLOT_WIDTH/PLOT_HEIGHT and headless operation under CI=true.
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
"""Parsing of the `bbox` input: an Arrow struct carrying boxes and labels."""
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import numpy as np
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from opencv_plot.plot import Bboxes
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def parse(value, bbox_format: str) -> Bboxes:
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"""Read a `bbox` payload. `bbox_format` is the `format` metadata parameter."""
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fields = value[0]
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corners = _flat(fields, "bbox").reshape(-1, 4)
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if bbox_format == "xyxy":
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pass
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elif bbox_format == "xywh":
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# xywh is centre-based: x and y are the box centre, not a corner.
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x, y, w, h = corners.T
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corners = np.stack([x - w / 2, y - h / 2, x + w / 2, y + h / 2], axis=1)
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else:
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raise RuntimeError(f"unsupported bbox format: {bbox_format}")
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return Bboxes(
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corners=corners,
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conf=_flat(fields, "conf"),
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labels=_flat(fields, "labels", numeric=False),
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)
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def _flat(fields, name: str, numeric: bool = True) -> np.ndarray:
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"""Read a struct field as a flat numpy array.
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Senders wrap each field in a single-element list -- that is what
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`pa.array([{...}])` produces from numpy arrays -- so unwrap it when present.
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"""
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column = fields[name]
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column = getattr(column, "values", column)
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return column.to_numpy(zero_copy_only=False) if not numeric else column.to_numpy()
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