import tensorflow as tf from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense import pandas as pd import numpy as np import cv2 import os 构建模型 model = Sequential() model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(80, 160, 3))) # (None, 80, 160, 3) model.add(MaxPooling2D((2, 2))) model.add(Conv2D(64, (3, 3), activation='relu')) model.add(MaxPooling2D((2, 2))) model.add(Flatten()) model.add(Dense(64, activation='relu')) model.add(Dense(62, activation='softmax')) # 36表示0-9数字和A-Z(a-z)字母的类别数 model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy']) model.fit(train_data, train_labels, epochs=10, batch_size=32) model.save('captcha_model.h5') 编写使用该模型测试验证码数据准确率的代码
时间: 2024-01-07 18:06:17 浏览: 31
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense
import pandas as pd
import numpy as np
import cv2
import os
# 加载训练数据和标签
train_data = ...
train_labels = ...
# 构建模型
model = Sequential()
model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(80, 160, 3)))
model.add(MaxPooling2D((2, 2)))
model.add(Conv2D(64, (3, 3), activation='relu'))
model.add(MaxPooling2D((2, 2)))
model.add(Flatten())
model.add(Dense(64, activation='relu'))
model.add(Dense(62, activation='softmax'))
# 编译模型
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
# 训练模型
model.fit(train_data, train_labels, epochs=10, batch_size=32)
# 保存模型
model.save('captcha_model.h5')
# 加载测试数据和标签
test_data = ...
test_labels = ...
# 使用模型测试数据准确率
loss, accuracy = model.evaluate(test_data, test_labels)
print('Test accuracy:', accuracy)