107 lines
4.6 KiB
Python
Executable File
107 lines
4.6 KiB
Python
Executable File
#!/usr/bin/python
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"""
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Created on Sat Aug 10 18:21:47 2013
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@author: Christian Forster
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"""
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import os
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import yaml
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import rospkg
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import argparse
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import time
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import vikit_py.cpu_info as cpu_info
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import vikit_py.ros_node as ros_node
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import evaluate
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import shutil
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def run_experiment(dataset, params):
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# load dataset parameters
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params['dataset_directory'] = os.path.join(os.environ['SVO_DATASET_DIR'], dataset)
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if not os.path.exists(params['dataset_directory']):
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raise Exception("Provided dataset folder does not exist.")
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dataset_params_file = os.path.join(params['dataset_directory'], 'dataset_params.yaml')
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dataset_params = yaml.load(open(dataset_params_file,'r'))
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# load algorithm parameters
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algo_params_file = os.path.join(rospkg.RosPack().get_path('svo_ros'),
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'param', params['param_settings']+'.yaml')
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algo_params = yaml.load(open(algo_params_file,'r'))
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# combine all parameters
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if 'rig_size' not in dataset_params or dataset_params['rig_size'] == 1:
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params = dict(params.items() + algo_params.items() + dataset_params['cam0'].items())
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else:
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params = dict(params.items() + algo_params.items() + dataset_params.items())
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if 'dataset_is_blender' in dataset_params:
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params['dataset_is_blender'] = dataset_params['dataset_is_blender']
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params['dataset_first_frame'] = dataset_params['dataset_first_frame']
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# dump experiment params to file and copy the other parameter files:
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params_dump_file = os.path.join(params['trace_dir'],'params.yaml')
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with open(params_dump_file,'w') as outfile:
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outfile.write(yaml.dump(params, default_flow_style=False))
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shutil.copyfile(dataset_params_file,
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os.path.join(params['trace_dir'], 'dataset_params.yaml'))
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# copy the groundtruth trajectory to the trace dir for later evaluation
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if params['dataset_is_blender']:
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shutil.copyfile(os.path.join(params['dataset_directory'], 'trajectory.txt'),
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os.path.join(params['trace_dir'], 'groundtruth_matched.txt'))
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else:
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shutil.copyfile(os.path.join(params['dataset_directory'], 'groundtruth_matched.txt'),
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os.path.join(params['trace_dir'], 'groundtruth_matched.txt'))
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# execute ros node
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node = ros_node.RosNode(args.version, args.executable)
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node.run(params)
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if __name__=="__main__":
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# parse command line
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parser = argparse.ArgumentParser(description='''
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Runs SVO with the dataset and parameters specified in the provided experiment file.
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''')
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parser.add_argument('experiment_file', help='experiment file in svo_analysis/experiments folder')
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parser.add_argument('--evaluate', help='evaluate tracefile after running SVO', action='store_true')
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parser.add_argument('--version', help='version of svo to evaluate', default='svo_ros')
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parser.add_argument('--executable', help='the executable to be called', default='benchmark')
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args = parser.parse_args()
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# load experiment parameters
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args.experiment_file = args.experiment_file.replace('.yaml','')
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experiment_params_file = os.path.join(rospkg.RosPack().get_path('svo_analysis'),
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'experiments', args.experiment_file+'.yaml')
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if os.path.exists(experiment_params_file):
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experiment_params = yaml.load(open(experiment_params_file, 'r'))
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else:
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print('experiment file does not exist. run with default setttings')
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experiment_params = dict({'experiment_label':'default','param_settings':'vo_fast',
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'datasets':list([args.experiment_file])})
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params = dict()
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params['experiment_label'] = experiment_params['experiment_label']
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params['param_settings'] = experiment_params['param_settings']
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params['time'] = time.strftime("%Y%m%d_%H%M", time.localtime())
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params['platform'] = cpu_info.get_cpu_info()
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params['trace_name'] = 'trace'
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trace_dirs = list()
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for dataset in experiment_params['datasets']:
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params['experiment_name'] = params['time']+'_'+args.version+'_'+args.experiment_file+'_'+dataset
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params['trace_dir'] = os.path.join(rospkg.RosPack().get_path('svo_analysis'),
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'results', params['experiment_name'])
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if not os.path.exists(params['trace_dir']):
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os.makedirs(params['trace_dir'])
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trace_dirs.append(params['trace_dir'])
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run_experiment(dataset, params)
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# TODO: check if it is a synthetic dataset
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for trace in trace_dirs:
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evaluate.evaluate_dataset(trace)
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