一、代码
发个优快云,证明我看过
import cv2 import numpy as np from random import randint animals_net = cv2.ml.ANN_MLP_create() animals_net.setTrainMethod(cv2.ml.ANN_MLP_RPROP | cv2.ml.ANN_MLP_UPDATE_WEIGHTS) animals_net.setActivationFunction(cv2.ml.ANN_MLP_SIGMOID_SYM) animals_net.setLayerSizes(np.array([3, 6, 4])) #[3, 6, 4] animals_net.setTermCriteria(( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )) """Input arrays weight, length, teeth """ """Output arrays dog, eagle, dolphin and dragon """ def dog_sample(): return [randint(10, 20), 1, randint(38, 42)] # 3x1 def dog_class(): return [1, 0