add utils for changing configs from args

README.md

@@ -59,7 +59,7 @@ Please refer to [`cruw-devit`](https://github.com/yizhou-wang/cruw-devkit) repos
 ```commandline
 git clone https://github.com/yizhou-wang/cruw-devkit.git
 cd cruw-devkit
-pip install -e .
+pip install .
 cd ..
 ```
 

rodnet/utils/load_configs.py

@@ -20,11 +20,103 @@ def load_configs_from_file(config_path):
     return cfg_dict
 
 
+def parse_cfgs(parser):
+    # dataset_cfg
+    parser.add_argument('--data_root', type=str,
+                        help='directory to the dataset (will overwrite data_root in config file)')
+
+    # model_cfg
+    parser.add_argument('--model_type', type=str, help='model type')
+    parser.add_argument('--model_name', type=str, help='model name or exp name')
+    parser.add_argument('--max_dets', type=int, help='max detection per frome')
+    parser.add_argument('--peak_thres', type=float, help='peak threshold')
+    parser.add_argument('--ols_thres', type=float, help='OLS thres')
+    parser.add_argument('--stacked_num', type=int, help='number of stack for HG')
+    parser.add_argument('--mnet_cfg', type=tuple, help='MNet configuration')
+    parser.add_argument('--dcn', type=bool, help='whether use TDC')
+
+    # train_cfg
+    parser.add_argument('--n_epoch', type=int, help='number of training epochs')
+    parser.add_argument('--batch_size', type=int, help='batch size')
+    parser.add_argument('--lr', type=float, help='learning rate')
+    parser.add_argument('--lr_step', type=int, help='step for learning rate decreasing')
+    parser.add_argument('--win_size', type=int, help='window size for RF images')
+    parser.add_argument('--train_step', type=int, help='training step within RF snippets')
+    parser.add_argument('--train_stride', type=int, help='training stride between RF snippets')
+    parser.add_argument('--log_step', type=int, help='step for printing out log info')
+    parser.add_argument('--save_step', type=int, help='step for saving checkpoints')
+
+    # test_cfg
+    parser.add_argument('--test_step', type=int, help='testing step within RF snippets')
+    parser.add_argument('--test_stride', type=int, help='testing stride between RF snippets')
+    parser.add_argument('--rr_min', type=float, help='range of range min value')
+    parser.add_argument('--rr_max', type=float, help='range of range max value')
+    parser.add_argument('--ra_min', type=float, help='range of angle min value')
+    parser.add_argument('--ra_max', type=float, help='range of angle max value')
+
+    return parser
+
+
 def update_config_dict(config_dict, args):
+    # dataset_cfg
+    if hasattr(args, 'data_root') and args.data_root is not None:
         data_root_old = config_dict['dataset_cfg']['base_root']
         config_dict['dataset_cfg']['base_root'] = args.data_root
         config_dict['dataset_cfg']['data_root'] = config_dict['dataset_cfg']['data_root'].replace(data_root_old,
                                                                                                   args.data_root)
         config_dict['dataset_cfg']['anno_root'] = config_dict['dataset_cfg']['anno_root'].replace(data_root_old,
                                                                                                   args.data_root)
+
+    # model_cfg
+    if hasattr(args, 'model_type') and args.model_type is not None:
+        config_dict['model_cfg']['type'] = args.model_type
+    if hasattr(args, 'model_name') and args.model_name is not None:
+        config_dict['model_cfg']['name'] = args.model_name
+    if hasattr(args, 'max_dets') and args.max_dets is not None:
+        config_dict['model_cfg']['max_dets'] = args.max_dets
+    if hasattr(args, 'peak_thres') and args.peak_thres is not None:
+        config_dict['model_cfg']['peak_thres'] = args.peak_thres
+    if hasattr(args, 'ols_thres') and args.ols_thres is not None:
+        config_dict['model_cfg']['ols_thres'] = args.ols_thres
+    if hasattr(args, 'stacked_num') and args.stacked_num is not None:
+        config_dict['model_cfg']['stacked_num'] = args.stacked_num
+    if hasattr(args, 'mnet_cfg') and args.mnet_cfg is not None:
+        config_dict['model_cfg']['mnet_cfg'] = args.mnet_cfg
+    if hasattr(args, 'dcn') and args.dcn is not None:
+        config_dict['model_cfg']['dcn'] = args.dcn
+
+    # train_cfg
+    if hasattr(args, 'n_epoch') and args.n_epoch is not None:
+        config_dict['train_cfg']['n_epoch'] = args.n_epoch
+    if hasattr(args, 'batch_size') and args.batch_size is not None:
+        config_dict['train_cfg']['batch_size'] = args.batch_size
+    if hasattr(args, 'lr') and args.lr is not None:
+        config_dict['train_cfg']['lr'] = args.lr
+    if hasattr(args, 'lr_step') and args.lr_step is not None:
+        config_dict['train_cfg']['lr_step'] = args.lr_step
+    if hasattr(args, 'win_size') and args.win_size is not None:
+        config_dict['train_cfg']['win_size'] = args.win_size
+    if hasattr(args, 'train_step') and args.train_step is not None:
+        config_dict['train_cfg']['train_step'] = args.train_step
+    if hasattr(args, 'train_stride') and args.train_stride is not None:
+        config_dict['train_cfg']['train_stride'] = args.train_stride
+    if hasattr(args, 'log_step') and args.log_step is not None:
+        config_dict['train_cfg']['log_step'] = args.log_step
+    if hasattr(args, 'save_step') and args.save_step is not None:
+        config_dict['train_cfg']['save_step'] = args.save_step
+
+    # test_cfg
+    if hasattr(args, 'test_step') and args.test_step is not None:
+        config_dict['test_cfg']['test_step'] = args.test_step
+    if hasattr(args, 'test_stride') and args.test_stride is not None:
+        config_dict['test_cfg']['test_stride'] = args.test_stride
+    if hasattr(args, 'rr_min') and args.rr_min is not None:
+        config_dict['test_cfg']['rr_min'] = args.rr_min
+    if hasattr(args, 'rr_max') and args.rr_max is not None:
+        config_dict['test_cfg']['rr_max'] = args.rr_max
+    if hasattr(args, 'ra_min') and args.ra_min is not None:
+        config_dict['test_cfg']['ra_min'] = args.ra_min
+    if hasattr(args, 'ra_max') and args.ra_max is not None:
+        config_dict['test_cfg']['ra_max'] = args.ra_max
+
     return config_dict

tools/test.py

 import os
 import time
 import argparse
-import numpy as np
 
 import torch
 from torch.utils.data import DataLoader
@@ -15,7 +14,7 @@ from rodnet.core.post_processing import write_dets_results, write_dets_results_s
 from rodnet.core.post_processing import ConfmapStack
 from rodnet.core.radar_processing import chirp_amp
 from rodnet.utils.visualization import visualize_test_img, visualize_test_img_wo_gt
-from rodnet.utils.load_configs import load_configs_from_file
+from rodnet.utils.load_configs import load_configs_from_file, parse_cfgs, update_config_dict
 from rodnet.utils.solve_dir import create_random_model_name
 
 """
@@ -27,6 +26,7 @@ Example:
 
 def parse_args():
     parser = argparse.ArgumentParser(description='Test RODNet.')
+
     parser.add_argument('--config', type=str, help='choose rodnet model configurations')
     parser.add_argument('--sensor_config', type=str, default='sensor_config_rod2021')
     parser.add_argument('--data_dir', type=str, default='./data/', help='directory to the prepared data')
@@ -35,6 +35,8 @@ def parse_args():
     parser.add_argument('--use_noise_channel', action="store_true", help="use noise channel or not")
     parser.add_argument('--demo', action="store_true", help='False: test with GT, True: demo without GT')
     parser.add_argument('--symbol', action="store_true", help='use symbol or text+score')
+
+    parser = parse_cfgs(parser)
     args = parser.parse_args()
     return args
 
@@ -44,6 +46,8 @@ if __name__ == "__main__":
     sybl = args.symbol
 
     config_dict = load_configs_from_file(args.config)
+    config_dict = update_config_dict(config_dict, args)  # update configs by args
+
     dataset = CRUW(data_root=config_dict['dataset_cfg']['base_root'], sensor_config_name=args.sensor_config)
     radar_configs = dataset.sensor_cfg.radar_cfg
     range_grid = dataset.range_grid

tools/train.py

@@ -18,12 +18,13 @@ from rodnet.datasets.CRDataLoader import CRDataLoader
 from rodnet.datasets.collate_functions import cr_collate
 from rodnet.core.radar_processing import chirp_amp
 from rodnet.utils.solve_dir import create_dir_for_new_model
-from rodnet.utils.load_configs import load_configs_from_file, update_config_dict
+from rodnet.utils.load_configs import load_configs_from_file, parse_cfgs, update_config_dict
 from rodnet.utils.visualization import visualize_train_img
 
 
 def parse_args():
     parser = argparse.ArgumentParser(description='Train RODNet.')
+
     parser.add_argument('--config', type=str, help='configuration file path')
     parser.add_argument('--sensor_config', type=str, default='sensor_config_rod2021')
     parser.add_argument('--data_dir', type=str, default='./data/', help='directory to the prepared data')
@@ -31,6 +32,8 @@ def parse_args():
     parser.add_argument('--resume_from', type=str, default=None, help='path to the trained model')
     parser.add_argument('--save_memory', action="store_true", help="use customized dataloader to save memory")
     parser.add_argument('--use_noise_channel', action="store_true", help="use noise channel or not")
+
+    parser = parse_cfgs(parser)
     args = parser.parse_args()
     return args
 
@@ -38,6 +41,8 @@ def parse_args():
 if __name__ == "__main__":
     args = parse_args()
     config_dict = load_configs_from_file(args.config)
+    config_dict = update_config_dict(config_dict, args)  # update configs by args
+
     # dataset = CRUW(data_root=config_dict['dataset_cfg']['base_root'])
     dataset = CRUW(data_root=config_dict['dataset_cfg']['base_root'], sensor_config_name=args.sensor_config)
     radar_configs = dataset.sensor_cfg.radar_cfg