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pipeline.py
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pipeline.py
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# -*- coding: utf-8 -*-
"""
Created on Sun Oct 8 21:49:26 2017
@author: yang
"""
import os
import cv2
import utils
import matplotlib.pyplot as plt
import numpy as np
from moviepy.editor import VideoFileClip
import line
def thresholding(img):
#setting all sorts of thresholds
x_thresh = utils.abs_sobel_thresh(img, orient='x', thresh_min=10 ,thresh_max=230)
mag_thresh = utils.mag_thresh(img, sobel_kernel=3, mag_thresh=(30, 150))
dir_thresh = utils.dir_threshold(img, sobel_kernel=3, thresh=(0.7, 1.3))
hls_thresh = utils.hls_select(img, thresh=(180, 255))
lab_thresh = utils.lab_select(img, thresh=(155, 200))
luv_thresh = utils.luv_select(img, thresh=(225, 255))
#Thresholding combination
threshholded = np.zeros_like(x_thresh)
threshholded[((x_thresh == 1) & (mag_thresh == 1)) | ((dir_thresh == 1) & (hls_thresh == 1)) | (lab_thresh == 1) | (luv_thresh == 1)] = 1
return threshholded
def processing(img,object_points,img_points,M,Minv,left_line,right_line):
#camera calibration, image distortion correction
undist = utils.cal_undistort(img,object_points,img_points)
#get the thresholded binary image
thresholded = thresholding(undist)
#perform perspective transform
thresholded_wraped = cv2.warpPerspective(thresholded, M, img.shape[1::-1], flags=cv2.INTER_LINEAR)
#perform detection
if left_line.detected and right_line.detected:
left_fit, right_fit, left_lane_inds, right_lane_inds = utils.find_line_by_previous(thresholded_wraped,left_line.current_fit,right_line.current_fit)
else:
left_fit, right_fit, left_lane_inds, right_lane_inds = utils.find_line(thresholded_wraped)
left_line.update(left_fit)
right_line.update(right_fit)
#draw the detected laneline and the information
area_img = utils.draw_area(undist,thresholded_wraped,Minv,left_fit, right_fit)
curvature,pos_from_center = utils.calculate_curv_and_pos(thresholded_wraped,left_fit, right_fit)
result = utils.draw_values(area_img,curvature,pos_from_center)
return result
#
#
left_line = line.Line()
right_line = line.Line()
cal_imgs = utils.get_images_by_dir('camera_cal')
object_points,img_points = utils.calibrate(cal_imgs,grid=(9,6))
M,Minv = utils.get_M_Minv()
project_outpath = 'vedio_out/project_video_out.mp4'
project_video_clip = VideoFileClip("project_video.mp4")
project_video_out_clip = project_video_clip.fl_image(lambda clip: processing(clip,object_points,img_points,M,Minv,left_line,right_line))
project_video_out_clip.write_videofile(project_outpath, audio=False)
##draw the processed test image
# test_imgs = utils.get_images_by_dir('test_images')
# undistorted = []
# for img in test_imgs:
# img = utils.cal_undistort(img,object_points,img_points)
# undistorted.append(img)
#
# result=[]
# for img in undistorted:
# res = processing(img,object_points,img_points,M,Minv,left_line,right_line)
# result.append(res)
#
# plt.figure(figsize=(20,68))
# for i in range(len(result)):
#
# plt.subplot(len(result),1,i+1)
# plt.title('thresholded_wraped image')
# plt.imshow(result[i][:,:,::-1])