首先,你需要确保已经安装 Flask。如果没有安装,可以使用以下命令: pipinstallFlask# 使用 pip 安装 Flask 1. 2. 创建 Flask 应用 创建一个新的 Python 文件,命名为app.py。在文件中导入 Flask,并创建一个简单的应用。 fromflaskimportFlask# 导入 Flask 类app=Flask(__name__)# 创建 Flask 应用实例@app.rou...
Flask Web框架托管的TensorFlow Serving客户端 这是我的的扩展。 它引入了一个托管TensorFlow服务客户端的Flask Web服务器。 它接收REST请求以预测,将其转换为protobufs,然后通过gRPC发送到TensorFlow服务器以通过GAN模型进行预测。 提到的GAN模型是使用技术并以课程中教授的模型为 训练的。 原始的Jupyter Notebook可在...
This repository contains instructions, template source code and examples on how to serve/deploy machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, MLflow and even code on how to deploy your machine learning model as an android app....
from flask import Flask app = Flask(__name__) @app.route('/') def hello(): return 'Hello, World!' if __name__ == '__main__': app.run(host='0.0.0.0', port=8080) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 构建容器镜像:将应用程序代码打包到一个容器镜像中。创建一个 Dockerfil...
app.logger.info(' * Running on http://{}:{}/'.format(host, port)) run_server() 开发者ID:e-yes,项目名称:Flask-aiohttp,代码行数:59,代码来源:__init__.py 示例7: runServer ▲点赞 1▼ defrunServer(self):"""Starts up the server. It (will) support different config options via the ...
Awesome pre-trained models toolkit based on PaddlePaddle.(300+ models including Image, Text, Audio and Video with Easy Inference & Serving deployment) - PaddleHub/paddlehub/serving/app_single.py at 8419f9d526b8eff82b376a59e9cc68c25731c588 · iqy/PaddleH
FLASK_ENV=development or FLASK_DEBUG=1. """debug = get_debug_flag()ifreloadisNone: reload = debugifdebuggerisNone: debugger = debugifeager_loadingisNone: eager_loading =notreload show_server_banner(get_env(), debug, info.app_import_path, eager_loading) ...
1. 编写您的无服务器应用程序代码。Knative Serving 支持多种编程语言和框架,例如Node.js、Python、Go等。根据您选择的语言和框架,编写一个简单的服务。以python为例的一个简单Hello World。 app.py: fromflaskimportFlaskapp=Flask(__name__)@app.route('/')defhello():return'Hello, World!'if__name__=...
In this ESP32 tutorial we will check how to serve JSON content from a Picoweb app. The tests shown here were performed using a DFRobot’s ESP-WROOM-32 device integrated in a ESP32 FireBeetle board. Introduction In this ESP32 tutorial we will check how to
app = Flask(__name__) # Testing URL @app.route('/cls/', methods=['POST']) def textclassification_cls(): sentence = request.get_data() sentence = " ".join(jieba.lcut(sentence)) with open('tokenizer.pickle', 'rb') as handle: ...