| #!/usr/bin/env python3 | |
| # SPDX-License-Identifier: Apache-2.0 | |
| """Build (and optionally send) a ``POST /predict`` request for bevformer-p150. Standard library only. | |
| # the shipped sample: six cameras + the calibration preset listed by /info | |
| S=code/tt_bevformer/samples/synthetic_6cam | |
| python3 code/tt_bevformer/server/client.py --image CAM_FRONT=$S/CAM_FRONT.png --image CAM_FRONT_RIGHT=$S/CAM_FRONT_RIGHT.png \ | |
| --image CAM_FRONT_LEFT=$S/CAM_FRONT_LEFT.png --image CAM_BACK=$S/CAM_BACK.png \ | |
| --image CAM_BACK_LEFT=$S/CAM_BACK_LEFT.png --image CAM_BACK_RIGHT=$S/CAM_BACK_RIGHT.png \ | |
| --calib-preset synthetic_6cam --out req.json | |
| curl -s localhost:20000/predict -H 'Content-Type: application/json' -d @req.json | |
| # or send it directly and print the response: add --url http://127.0.0.1:20000 (no --out) | |
| The implementation is the vendored ``ttaw/server/client.py`` (C08); this file runs it from the model repository | |
| with any Python 3.9+, without numpy and without installing the package. In Python, use | |
| ``tt_bevformer.ttaw.server.client`` (``build_request``, ``post``, ``wait_ready``, ...). | |
| """ | |
| import runpy | |
| from pathlib import Path | |
| if __name__ == "__main__": | |
| runpy.run_path(str(Path(__file__).resolve().parents[1] / "ttaw" / "server" / "client.py"), run_name="__main__") | |