80 lines
2.5 KiB
Python
Executable File
80 lines
2.5 KiB
Python
Executable File
#!/usr/bin/env python3
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import argparse
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import time
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import os
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from tqdm import tqdm
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from cereal.messaging import PubMaster, recv_one, sub_sock
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from cereal.services import service_list
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from tools.lib.logreader import LogReader
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from xx.chffr.lib.route import Route, RouteSegment
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from tools.lib.route_framereader import RouteFrameReader
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from common.column_store import save_dict_as_column_store
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from xx.pipeline.lib.log_time_series import append_dict
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from selfdrive.test.process_replay.compare_logs import save_log
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Run visiond on segment")
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parser.add_argument("segment_name", help="The segment to run")
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parser.add_argument("output_path", help="The output file")
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args = parser.parse_args()
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segment = RouteSegment.from_canonical_name(args.segment_name)
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route = Route(segment._name._route_name)
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frame_id_lookup = {}
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frame_reader = RouteFrameReader(route.camera_paths(), None, frame_id_lookup, readahead=True)
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msgs = list(LogReader(segment.log_path))
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pm = PubMaster(['liveCalibration', 'frame'])
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model_sock = sub_sock('model')
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# Read encodeIdx
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for msg in msgs:
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if msg.which() == 'encodeIdx':
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frame_id_lookup[msg.encodeIdx.frameId] = (msg.encodeIdx.segmentNum, msg.encodeIdx.segmentId)
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# Send some livecalibration messages to initalize visiond
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for msg in msgs:
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if msg.which() == 'liveCalibration':
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pm.send('liveCalibration', msg.as_builder())
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time.sleep(1.0)
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values = {}
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out_msgs = []
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for msg in tqdm(msgs):
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w = msg.which()
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if w == 'liveCalibration':
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pm.send(w, msg.as_builder())
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if w == 'frame':
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msg = msg.as_builder()
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frame_id = msg.frame.frameId
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img = frame_reader.get(frame_id, pix_fmt="rgb24")[:,:,::-1]
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msg.frame.image = img.flatten().tobytes()
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pm.send(w, msg)
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model = recv_one(model_sock)
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model = model.as_builder()
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model.logMonoTime = 0
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model = model.as_reader()
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out_msgs.append(model)
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save_log(args.output_path, out_msgs)
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# tm = model.logMonoTime / 1.0e9
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# model = model.model
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# append_dict("model/data/path", tm, model.path.to_dict(), values)
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# append_dict("model/data/left_lane", tm, model.leftLane.to_dict(), values)
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# append_dict("model/data/right_lane", tm, model.rightLane.to_dict(), values)
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# append_dict("model/data/lead", tm, model.lead.to_dict(), values)
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# save_dict_as_column_store(values, os.path.join(args.output_path, "LiveVisionD", args.segment_name))
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