JPEGImages/000033.jpg 9,107,499,263,0 421,200,482,226,0 325,188,411,223,0
......
2.准备输入输出数据
YOLO V1...cv.rectangle(img, ptLeftTop, ptRightBottom, point_color, thickness, lineType)
cv.namedWindow("YOLO V1...")
cv.imshow('YOLO V1', img)
while(1):
if (cv.waitKey(0) == 27):
break
cv.destroyAllWindows...from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, InputLayer,...194s 310ms/step - loss: 71.0617 - val_loss: 61.3470
由于缺少预训练的环节,模型的训练效果最终没有达到论文描述的精度,但通过代码实现的过程,对于YOLO V1