lane-detect-pi.py 文件源码

def project_on_road(self, image_input):
        image = image_input[self.remove_pixels:, :]
        image = self.trans_per(image)
        self.im_shape = image.shape
        self.get_fit(image)

        if self.detected_first & self.detected:
            # create fill image
            temp_filler = np.zeros((self.remove_pixels,self.im_shape[1])).astype(np.uint8)
            filler = np.dstack((temp_filler,temp_filler,temp_filler))

            # create an image to draw the lines on
            warp_zero = np.zeros_like(image).astype(np.uint8)
            color_warp = np.dstack((warp_zero, warp_zero, warp_zero))

            ploty = np.linspace(0, image_input.shape[0]-1, image_input.shape[0] )
            left_fitx = self.best_fit_l[0]*ploty**2 + self.best_fit_l[1]*ploty + self.best_fit_l[2]
            right_fitx = self.best_fit_r[0]*ploty**2 + self.best_fit_r[1]*ploty + self.best_fit_r[2]

            # recast the x and y points into usable format for cv2.fillPoly()
            pts_left = np.array([np.transpose(np.vstack([left_fitx, ploty]))])
            pts_right = np.array([np.flipud(np.transpose(np.vstack([right_fitx, ploty])))])
            pts = np.hstack((pts_left, pts_right))

            # draw the lane onto the warped blank image
            cv2.fillPoly(color_warp, np.int_([pts]), (0,255, 0))

            # warp the blank back to original image space using inverse perspective matrix (Minv)
            newwarp = cv2.warpPerspective(color_warp, self.Minv, color_warp.shape[-2:None:-1])
            left_right = cv2.warpPerspective(self.left_right, self.Minv, color_warp.shape[-2:None:-1])
            # combine the result with the original image
            left_right_fill = np.vstack((filler,left_right)) 
            result = cv2.addWeighted(left_right_fill,1, image_input, 1, 0)
            result = cv2.addWeighted(result, 1, np.vstack((filler,newwarp)), 0.3, 0)


            # get curvature and offset
            self.calculate_curvature_offset()

            # plot text on resulting image
            img_text = "radius of curvature: " + str(round((self.left_curverad + self.right_curverad)/2,2)) + ' (m)'

            if self.offset< 0:
                img_text2 = "vehicle is: " + str(round(np.abs(self.offset),2)) + ' (m) left of center'
            else:
                img_text2 = "vehicle is: " + str(round(np.abs(self.offset),2)) + ' (m) right of center'

            result2 = cv2.resize(result, (0,0), fx=self.enlarge, fy=self.enlarge)

            cv2.putText(result2,img_text, (15,15), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255,255,255),1)
            cv2.putText(result2,img_text2,(15,40), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255,255,255),1)

            return result2

        # if lanes were not detected output source image
        else:
            return cv2.resize(image_input,(0,0), fx=self.enlarge, fy=self.enlarge)