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line.py
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line.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Oct 10 19:38:04 2017
@author: yang
"""
import numpy as np
# Define a class to receive the characteristics of each line detection
class Line():
def __init__(self):
# was the line detected in the last iteration?
self.detected = False
# x values of the last n fits of the line
self.recent_fitted = [np.array([False])]
#average x values of the fitted line over the last n iterations
self.bestx = None
#polynomial coefficients averaged over the last n iterations
self.best_fit = None
#polynomial coefficients for the most recent fit
self.current_fit = [np.array([False])]
#radius of curvature of the line in some units
self.radius_of_curvature = None
#distance in meters of vehicle center from the line
self.line_base_pos = None
#difference in fit coefficients between last and new fits
self.diffs = np.array([0,0,0], dtype='float')
#x values for detected line pixels
self.allx = None
#y values for detected line pixels
self.ally = None
def check_detected(self):
if (self.diffs[0] < 0.01 and self.diffs[1] < 10.0 and self.diffs[2] < 1000.) and len(self.recent_fitted) > 0:
return True
else:
return False
def update(self,fit):
if fit is not None:
if self.best_fit is not None:
self.diffs = abs(fit - self.best_fit)
if self.check_detected():
self.detected =True
if len(self.recent_fitted)>10:
self.recent_fitted = self.recent_fitted[1:]
self.recent_fitted.append(fit)
else:
self.recent_fitted.append(fit)
self.best_fit = np.average(self.recent_fitted, axis=0)
self.current_fit = fit
else:
self.detected = False
else:
self.best_fit = fit
self.current_fit = fit
self.detected=True
self.recent_fitted.append(fit)