96 lines
2.2 KiB
Markdown
96 lines
2.2 KiB
Markdown
# Dora Node for plotting data with OpenCV
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This node is used to plot a text and a list of bbox on a base image (ideal for object detection).
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# YAML
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```yaml
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- id: dora-image-viewer
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build: pip install ../../dora_image_viewer
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path: dora_image_viewer/dora_image_viewer/main.py
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inputs:
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# image: Arrow array of size 1 containing the base image
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# bbox: Arrow array of bbox
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# text: Arrow array of size 1 containing the text to be plotted
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env:
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PLOT_WIDTH: 640 # optional, default is image input width
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PLOT_HEIGHT: 480 # optional, default is image input height
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```
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# Inputs
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- `image`: Arrow array containing the base image
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```python
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## Image data
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image_data: UInt8Array # Example: pa.array(img.ravel())
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metadata = {
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"width": 640,
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"height": 480,
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"shape": [480, 640, 3], # optional alternative to width/height
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"encoding": str, # bgr8, rgb8
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}
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## Example
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node.send_output(
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image_data, {"width": 640, "height": 480, "encoding": "bgr8"}
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)
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## Decoding
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storage = event["value"]
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metadata = event["metadata"]
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encoding = metadata["encoding"]
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width = metadata.get("width")
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height = metadata.get("height")
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shape = metadata.get("shape")
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if encoding == "bgr8":
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channels = 3
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storage_type = np.uint8
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frame = (
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storage.to_numpy()
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.astype(storage_type)
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.reshape((height, width, channels))
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)
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```
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- `bbox`: an arrow array containing the bounding boxes, confidence scores, and class names of the detected objects
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```Python
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bbox: {
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"bbox": np.array, # flattened array of bounding boxes
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"conf": np.array, # flat array of confidence scores
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"labels": np.array, # flat array of class names
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}
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encoded_bbox = pa.array([bbox], {"format": "xyxy"})
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decoded_bbox = {
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"bbox": encoded_bbox[0]["bbox"].values.to_numpy().reshape(-1, 4),
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"conf": encoded_bbox[0]["conf"].values.to_numpy(),
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"labels": encoded_bbox[0]["labels"].values.to_numpy(zero_copy_only=False),
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}
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```
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- `text`: Arrow array containing the text to be plotted
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```python
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text: str
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encoded_text = pa.array([text])
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decoded_text = encoded_text[0].as_py()
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```
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## Example
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Check example at [examples/python-dataflow](examples/python-dataflow)
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## License
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This project is licensed under Apache-2.0. Check out [NOTICE.md](../../NOTICE.md) for more information.
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