从Gluoncv下载已经训练好的模型进行目标检测

首先从cmd下载

pip install mxnet

pip install gluoncv
将以下代码复制到Pycharm中，

from gluoncv import model_zoo, data, utils
from matplotlib import pyplot as plt
import cv2
net = model_zoo.get_model('yolo3_darknet53_voc', pretrained=True)
#下载预训练好的网络模型
im_fname = ('C:\\Users\\lenovo\\Pictures\\dog.jpg')
 #测试用dog图片

x, img = data.transforms.presets.yolo.load_test(im_fname, short=512)
print('Shape of pre-processed image:', x.shape)

class_IDs, scores, bounding_boxs = net(x)

ax = utils.viz.plot_bbox(img, bounding_boxs[0], scores[0],
                         class_IDs[0], class_names=net.classes)
plt.show()

显示结果如下：