![Adeeb Shihadeh](/assets/img/avatar_default.png)
* start cleanup * fan speed * cleanup dm * fix cereal * hwType -> pandaType * update refs * update refs * bump cereal * freeSpacePercent * cereal master
31 lines
1.1 KiB
Python
Executable file
31 lines
1.1 KiB
Python
Executable file
#!/usr/bin/env python3
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import os
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import numpy as np
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from tools.lib.logreader import LogReader
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from tools.lib.framereader import FrameReader
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from tools.lib.cache import cache_path_for_file_path
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from selfdrive.test.process_replay.camera_replay import camera_replay
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if __name__ == "__main__":
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lr = LogReader(os.path.expanduser('~/rlog.bz2'))
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fr = FrameReader(os.path.expanduser('~/fcamera.hevc'))
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desire = np.load(os.path.expanduser('~/desire.npy'))
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calib = np.load(os.path.expanduser('~/calib.npy'))
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try:
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msgs = camera_replay(list(lr), fr, desire=desire, calib=calib)
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finally:
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cache_path = cache_path_for_file_path(os.path.expanduser('~/fcamera.hevc'))
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if os.path.isfile(cache_path):
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os.remove(cache_path)
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output_size = len(np.frombuffer(msgs[0].model.rawPredictions, dtype=np.float32))
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output_data = np.zeros((len(msgs), output_size), dtype=np.float32)
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for i, msg in enumerate(msgs):
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output_data[i] = np.frombuffer(msg.model.rawPredictions, dtype=np.float32)
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np.save(os.path.expanduser('~/modeldata.npy'), output_data)
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print("Finished replay")
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