如果测试图像而非视频的话，网上有很多代码都是在terminal里面运行：python yolo_video.py --image, 本人比较懒不喜欢使用命令运行程序，因此对测试程序yolo.video.py做了如下更改。
实验结果发现Keras写的yolo虽然可以出实验结果但是loss接近10左右。实验结果如图：
将yolo_video.py更改为下面的代码直接运行即可，每测试一张显示一张图像，22行的path是测试图像的路径，23行outputdir是要保存测试图像的路径，61行的default=‘True’即可：（使用需要点赞，谢谢！）
import sys
import argparse
from yolo import YOLO, detect_video
from PIL import Image
import glob, os
from skimage import io
from matplotlib import pyplot as plt
import numpy as np
# def detect_img(yolo):
# while True:
# img = input('Input image filename:')
# try:
# image = Image.open(img)
# except:
# print('Open Error! Try again!')
# continue
# else:
# r_image = yolo.detect_image(image)
# r_image.show()
# yolo.close_session()
def detect_img(yolo):path = "D:\\Users\\Experiments\\YOLO3\\keras-yolo3-master\\data\\testimage\\*.jpg"outputdir = "D:\\Users\\Experiments\\YOLO3\\keras-yolo3-master\\data"for jpgfile in glob.glob(path):img = Image.open(jpgfile)img = yolo.detect_image(img)img.save(os.path.join(outputdir, os.path.basename(jpgfile)))img = np.array(img)io.imshow(img)plt.show()yolo.close_session()FLAGS = Noneif __name__ == '__main__':# class YOLO defines the default value, so suppress any default hereparser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)'''Command line options'''parser.add_argument('--model', type=str,help='path to model weight file, default ' + YOLO.get_defaults("model_path"))parser.add_argument('--anchors', type=str,help='path to anchor definitions, default ' + YOLO.get_defaults("anchors_path"))parser.add_argument('--classes', type=str,help='path to class definitions, default ' + YOLO.get_defaults("classes_path"))parser.add_argument('--gpu_num', type=int,help='Number of GPU to use, default ' + str(YOLO.get_defaults("gpu_num")))parser.add_argument('--image', default=True, action="store_true",help='Image detection mode, will ignore all positional arguments')'''Command line positional arguments -- for video detection mode'''parser.add_argument("--input", nargs='?', type=str,required=False,default='./path2your_video',help = "Video input path")parser.add_argument("--output", nargs='?', type=str, default="",help = "[Optional] Video output path")FLAGS = parser.parse_args()if FLAGS.image:"""Image detection mode, disregard any remaining command line arguments"""print("Image detection mode")if "input" in FLAGS:print(" Ignoring remaining command line arguments: " + FLAGS.input + "," + FLAGS.output)detect_img(YOLO(**vars(FLAGS)))elif "input" in FLAGS:detect_video(YOLO(**vars(FLAGS)), FLAGS.input, FLAGS.output)else:print("Must specify at least video_input_path. See usage with --help.")
在改进yolo的过程中遇见的错误记录：
错误一：'NoneType' object has no attribute '_inbound_n’
这个错误是由误用tensorflow中的代码写作方式导致的，不可将TensorFlow代码与keras代码一起使用，
解决方法：检查改进的代码，将TensorFlow写的代码替换成keras.