Tusimple 数据集可视化_tusimple 数据可视化

import os
import cv2
import numpy as np
import json
from time import sleep
 
# tusimple 数据集地址
basedir = r'F:\data\tusimple'
 
 
def get_laneData(filepath, y_samples, gt_lanes):
    img = None
    imgLable = None
    if os.path.exists(filepath) and gt_lanes:
        img = cv2.imread(filepath)  # 读取图片
        # 获取点
        labelPos = [[(x, y) for (x, y) in zip(lane, y_samples) if x >= 0]
                    for lane in gt_lanes]
        labelPos = [lane for lane in labelPos if len(lane) > 0]
 
        # 绘制点
        imgLable = img.copy()
        for lpos in labelPos:
            for point in lpos:
                cv2.circle(imgLable, point, 2, (0, 0, 255), 2)
    # 对没有车道线的图片仅读取图片
    elif os.path.exists(filepath):
        img = cv2.imread(filepath)
        imgLable = None
    else:
        print("no image")
    return img, imgLable
 
 
text_path = r'test_label.json'
for line in open(os.path.join(basedir, text_path)):
    # 读取数据
    data = json.loads(line)
    y_samples = data['h_samples']
    gt_lanes = data['lanes']
    path = data['raw_file']
    # 获取img以及绘制的imglabel
    img, imglabel = get_laneData(os.path.join(
        basedir, path.strip('\n')), y_samples, gt_lanes)
 
    # 均存在
    if img.any() and imglabel is not None:
        imglabel = cv2.resize(imglabel, (1024, 512))
        cv2.imshow('dsh', imglabel)
        sleep(0.1)
    # 无线
    elif img.any() is not None:
        cv2.imshow('dsh', img)
        sleep(0.1)
    # 退出判断
    if cv2.waitKey(1) & 0xFF == ord('q'):  # 按q退出
        cv2.waitKey(0)
 
cv2.destroyAllWindows()