147 lines
6.3 KiB
Python
Executable File
147 lines
6.3 KiB
Python
Executable File
#!/usr/bin/python
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import os
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import sys
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import time
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import rospkg
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import numpy as np
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import matplotlib.pyplot as plt
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import yaml
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import argparse
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import svo_analysis.analyse_depth as analyse_depth
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from matplotlib import rc
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# tell matplotlib to use latex font
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rc('font',**{'family':'serif','serif':['Cardo']})
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rc('text', usetex=True)
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from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
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from mpl_toolkits.axes_grid1.inset_locator import mark_inset
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def plot_trajectory(ax, filename, label, color, linewidth):
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file = open(filename)
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data = file.read()
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lines = data.replace(","," ").replace("\t"," ").split("\n")
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trajectory = np.array([[v.strip() for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"], dtype=np.float64)
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ax.plot(trajectory[:,1], trajectory[:,2], label=label, color=color, linewidth=linewidth)
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def save_figure(fig, name, directory):
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fig.tight_layout()
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fig.savefig(os.path.join(directory, name+'.pdf'), bbox_inches="tight")
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def distances_along_trajectory(traj):
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keys = traj.keys()
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keys.sort()
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motion = [ominus(traj[keys[i+1]],traj[keys[i]]) for i in range(len(keys)-1)]
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distances = [0]
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sum = 0
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for t in motion:
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sum += compute_distance(t)
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distances.append(sum)
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return distances
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def compare_results(comp_params, results_dir, comparison_dir):
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print('run comparison: '+comp_params['comparison_name'])
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line_styles = ['-','--',':']
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line_colors = ['b','g','r','m','c']
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# -------------------------------------------------------------------------
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# plot trajectory:
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fig = plt.figure(figsize=(6,2))
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ax = fig.add_subplot(111, xlabel='x [m]', ylabel='y [m]')
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for exp_set in comp_params['experiment_sets']:
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print('processing experiment set: ' + exp_set['label'])
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for i, exp in enumerate(exp_set['experiments']):
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data = np.loadtxt(os.path.join(results_dir, exp, 'traj_estimate.txt'))
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if i == 0:
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base_plot, = ax.plot(data[:,1], data[:,2], label=exp_set['label'], linestyle=line_styles[np.mod(i, len(line_styles))])
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else:
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ax.plot(data[:,1], data[:,2], color=base_plot.get_color(), linestyle= line_styles[np.mod(i, len(line_styles))])
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ax.legend(loc='upper left', ncol=3)
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save_figure(fig, 'trajectory', comparison_dir)
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# -------------------------------------------------------------------------
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# plot translation error:
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fig = plt.figure(figsize=(6,2))
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ax = fig.add_subplot(111, xlabel='distance [m]', ylabel='translation drift [mm]')
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for exp_set in comp_params['experiment_sets']:
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print('processing experiment set: ' + exp_set['label'])
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for i, exp in enumerate(exp_set['experiments']):
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gt = np.loadtxt(os.path.join(results_dir, exp, 'groundtruth_matched.txt'))
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distances = np.diff(gt[:,1:4],axis=0)
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distances = np.sqrt(np.sum(np.multiply(distances,distances),1))
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distances = np.cumsum(distances)
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distances = np.concatenate(([0], distances))
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data = np.loadtxt(os.path.join(results_dir, exp, 'translation_error.txt'))
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e = np.sqrt(np.sum(np.multiply(data[:,1:4],data[:,1:4]),1))
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if np.shape(e)[0] > np.shape(distances)[0]:
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print('WARNING: estimate has more measurement than groundtruth: '
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+str(np.shape(e)[0]-np.shape(distances)[0]))
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e = e[0:np.shape(distances)[0]]
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distances = distances[0:np.shape(e)[0]]
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print '--'
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print np.shape(e)
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print np.shape(distances)
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if i == 0:
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base_plot, = ax.plot(distances, e*1000, label=exp_set['label'], linestyle= line_styles[np.mod(i, len(line_styles))])
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else:
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ax.plot(distances, e*1000, color=base_plot.get_color(), linestyle= line_styles[np.mod(i, len(line_styles))])
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ax.legend(loc='upper left', ncol=3)
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save_figure(fig, 'translation_error', comparison_dir)
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# -------------------------------------------------------------------------
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# plot depth estimation error:
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fig = plt.figure(figsize=(6,5))
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ax = fig.add_subplot(111, xlabel='Error [m]', ylabel='Precision [\%]')
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for k, exp_set in enumerate(comp_params['experiment_sets']):
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print('plot depth error for experiment: ' + exp_set['label'])
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for i, exp in enumerate(exp_set['experiments']):
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D = np.loadtxt(os.path.join(results_dir, exp, 'depth_error.txt'), delimiter=' ')
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D = D[np.logical_and(D[:,0] > 1, D[:,0] < D[-1,0]/4),:]
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errors = np.abs(D[:,1])
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if i == 0:
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base_plot = analyse_depth.precision_plot(ax, errors, 0.05, line_colors[k], line_styles[np.mod(i, len(line_styles))])
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else:
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base_plot = analyse_depth.precision_plot(ax, errors, 0.05, base_plot.get_color(), line_styles[np.mod(i, len(line_styles))])
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save_figure(fig, 'depth_error', comparison_dir)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Compare results of a VO pipeline.')
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parser.add_argument('comparison_file', help='A YAML file that contains the details of the comparison')
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args = parser.parse_args()
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# load comparison file
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args.experiment_file = args.comparison_file.replace('.yaml','')
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comparison_params_file = os.path.join(rospkg.RosPack().get_path('svo_analysis'),
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'comparisons', args.comparison_file+'.yaml')
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if os.path.exists(comparison_params_file):
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comp_params = yaml.load(open(comparison_params_file, 'r'))
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else:
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raise Exception("Provided comparison file does not exist.")
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# create folder for comparison results
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comparison_dir = os.path.join(rospkg.RosPack().get_path('svo_analysis'),
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'comparisons', comp_params['comparison_name'])
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if not os.path.exists(comparison_dir):
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os.makedirs(comparison_dir)
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# folder where the results of previous experiments are saved
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results_dir = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 'results')
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# run comparison
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compare_results(comp_params, results_dir, comparison_dir)
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