Files
HSAP/algorithms/lane_ufld/code.embedded.bak/CLRNet-main/main.py
Chengfang Lu e72bc061c5 feat: HSAP platform v2 — modular navigation, quality review, audit log, world model simulation
Major changes:
- New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind
- 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理
- Data catalog with charts (DMS/ADAS/Lane 3-tab view)
- Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance
- Audit enhancements: batch operations, rejection categories, Feishu notifications
- Operation audit log (操作日志)
- World model simulation studio (仿真工坊)
- Dataset version management with snapshots and diff
- ADAS 7-class dataset integration (138K images organized + compressed)
- User management with Feishu integration and pagination
- CRUD/search/filter on all pages, card layout redesign
- PIL-optimized image overlay rendering
- Auto-snapshot on build, in_review workflow stage
- Removed embedded algorithm code (now in workspace)
2026-06-03 11:40:21 +08:00

76 lines
2.1 KiB
Python

import os
import cv2
import torch
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import argparse
import numpy as np
import random
from clrnet.utils.config import Config
from clrnet.engine.runner import Runner
from clrnet.datasets import build_dataloader
def main():
args = parse_args()
os.environ["CUDA_VISIBLE_DEVICES"] = ','.join(
str(gpu) for gpu in args.gpus)
cfg = Config.fromfile(args.config)
cfg.gpus = len(args.gpus)
cfg.load_from = args.load_from
cfg.resume_from = args.resume_from
cfg.finetune_from = args.finetune_from
cfg.view = args.view
cfg.seed = args.seed
cfg.work_dirs = args.work_dirs if args.work_dirs else cfg.work_dirs
cudnn.benchmark = True
runner = Runner(cfg)
if args.validate:
runner.validate()
elif args.test:
runner.test()
else:
runner.train()
def parse_args():
parser = argparse.ArgumentParser(description='Train a detector')
parser.add_argument('config', help='train config file path')
parser.add_argument('--work_dirs',
type=str,
default=None,
help='work dirs')
parser.add_argument('--load_from',
default=None,
help='the checkpoint file to load from')
parser.add_argument('--resume_from',
default=None,
help='the checkpoint file to resume from')
parser.add_argument('--finetune_from',
default=None,
help='the checkpoint file to resume from')
parser.add_argument('--view', action='store_true', help='whether to view')
parser.add_argument(
'--validate',
action='store_true',
help='whether to evaluate the checkpoint during training')
parser.add_argument(
'--test',
action='store_true',
help='whether to test the checkpoint on testing set')
parser.add_argument('--gpus', nargs='+', type=int, default='0')
parser.add_argument('--seed', type=int, default=0, help='random seed')
args = parser.parse_args()
return args
if __name__ == '__main__':
main()