63 lines
1.6 KiB
Python
63 lines
1.6 KiB
Python
#!/usr/bin/env python3
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"""
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Run the full LangGraph detection pipeline on a test video.
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Usage:
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python tests/detect/manual/run_graph.py [--job JOB_ID] [--port PORT]
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Opens: http://mpr.local.ar/detection/?job=<JOB_ID>
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"""
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import argparse
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import logging
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import os
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import sys
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parser = argparse.ArgumentParser()
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parser.add_argument("--job", default="graph-test")
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parser.add_argument("--port", type=int, default=6382)
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args = parser.parse_args()
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os.environ["REDIS_URL"] = f"redis://localhost:{args.port}/0"
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logging.basicConfig(level=logging.INFO, format="%(levelname)-7s %(name)s — %(message)s")
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sys.path.insert(0, ".")
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from detect.graph import get_pipeline
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from detect.state import DetectState
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logger = logging.getLogger(__name__)
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VIDEO = "media/out/chunks/95043d50-4df6-4ac8-bbd5-2ba873117c6e/chunk_0000.mp4"
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def main():
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logger.info("Job: %s", args.job)
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logger.info("Open: http://mpr.local.ar/detection/?job=%s", args.job)
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input("\nPress Enter to start...")
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pipeline = get_pipeline()
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initial_state = DetectState(
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video_path=VIDEO,
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job_id=args.job,
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profile_name="soccer_broadcast",
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)
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logger.info("Running pipeline...")
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result = pipeline.invoke(initial_state)
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frames = result.get("frames", [])
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filtered = result.get("filtered_frames", [])
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report = result.get("report")
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logger.info("Frames extracted: %d", len(frames))
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logger.info("Frames after filter: %d", len(filtered))
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if report:
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logger.info("Brands found: %d", len(report.brands))
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logger.info("Done.")
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if __name__ == "__main__":
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main()
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