github-actions[bot]
54e6124925
version: sunnypilot v2026.001.000 (dev) date: 2026-05-07T23:07:19 master commit: c28eb958740187620f2282023b8f1997cf90f583
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
"""
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Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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This file is part of sunnypilot and is licensed under the MIT License.
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See the LICENSE.md file in the root directory for more details.
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"""
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import os
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import tomllib
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from difflib import SequenceMatcher
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from opendbc.car import structs
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from openpilot.common.basedir import BASEDIR
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TORQUE_NN_MODEL_PATH = os.path.join(BASEDIR, "sunnypilot", "neural_network_data", "neural_network_lateral_control")
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TORQUE_NN_MODEL_SUBSTITUTE_PATH = os.path.join(BASEDIR, "opendbc", "car", "torque_data/substitute.toml")
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MOCK_MODEL_PATH = os.path.join(TORQUE_NN_MODEL_PATH, "MOCK.json")
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def similarity(s1: str, s2: str) -> float:
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return SequenceMatcher(None, s1, s2).ratio()
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def get_nn_model_path(CP: structs.CarParams) -> tuple[str, str, bool]:
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car_fingerprint = CP.carFingerprint
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eps_fw = str(next((fw.fwVersion for fw in CP.carFw if fw.ecu == "eps"), ""))
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def check_nn_path(_nn_candidate):
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_model_path = None
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_max_similarity = -1.0
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for f in os.listdir(TORQUE_NN_MODEL_PATH):
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if f.endswith(".json"):
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model = os.path.splitext(f)[0]
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similarity_score = similarity(model, _nn_candidate)
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if similarity_score > _max_similarity:
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_max_similarity = similarity_score
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_model_path = os.path.join(TORQUE_NN_MODEL_PATH, f)
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return _model_path, _max_similarity
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if len(eps_fw) > 3:
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eps_fw = eps_fw.replace("\\", "")
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nn_candidate = f"{car_fingerprint} {eps_fw}"
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else:
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nn_candidate = car_fingerprint
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model_path, max_similarity = check_nn_path(nn_candidate)
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exact_match = max_similarity >= 0.99
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if car_fingerprint not in model_path or 0.0 <= max_similarity < 0.9:
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nn_candidate = car_fingerprint
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model_path, max_similarity = check_nn_path(nn_candidate)
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exact_match = max_similarity >= 0.99
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if 0.0 <= max_similarity < 0.9:
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with open(TORQUE_NN_MODEL_SUBSTITUTE_PATH, 'rb') as f:
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sub = tomllib.load(f)
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sub_candidate = sub.get(car_fingerprint, car_fingerprint)
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for candidate in [car_fingerprint, sub_candidate]:
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model_path, max_similarity = check_nn_path(candidate)
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exact_match = False
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if CP.steerControlType == structs.CarParams.SteerControlType.angle:
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model_path = MOCK_MODEL_PATH
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model_name = os.path.splitext(os.path.basename(model_path))[0]
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return model_path, model_name, exact_match
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