Python my_mobilenet_v3示例

示例#1

import tensorflow as tf
from flask import Flask
from flask import jsonify
from flask import request, render_template

import os,sys
from cfg import settings

# 导入模型
from models import my_mobilenet_v3
app = Flask(__name__)

os.chdir(os.path.dirname(sys.argv[0]))
#加载模型
model=my_mobilenet_v3()
# 加载训练好的参数
if os.path.exists(settings.MODEL_PATH + '.index'):
    print('-------------load the model-----------------')
    model.load_weights(settings.MODEL_PATH)

@app.route('/', methods=['GET'])
#首页，vue入口
def index():
    """
    首页，vue入口
    """
    return render_template('index.html')

@app.route('/api/v1/dogs_classify/', methods=['POST'])
#宠物狗图片分类接口

示例#2

# -*- coding: utf-8 -*-
# @Time : 2020/12/20
# @Author : Barbra
# @File : train.py
# @Software : PyCharm
# @Desc : 训练

import os
import tensorflow as tf
import models
import settings
from matplotlib import pyplot as plt
from data import train_db, test_db

# 从models文件中导入模型
model = models.my_mobilenet_v3()
model.summary()

exponential_decay = tf.keras.optimizers.schedules.ExponentialDecay(
    initial_learning_rate=0.1, decay_steps=1, decay_rate=0.99)

# 配置优化器、损失函数、以及监控指标
model.compile(tf.keras.optimizers.Adam(exponential_decay),
              loss=tf.keras.losses.categorical_crossentropy,
              metrics=['accuracy'])

# 在每个epoch结束后尝试保存模型参数，设置断点续训
if os.path.exists(settings.MODEL_PATH + '.index'):
    print('-------------load the model-----------------')
    model.load_weights(settings.MODEL_PATH)