Flask学习笔记(二):基于Flask框架上传图片到服务器端并原名保存

1.什么是Flask

• Flask是一个基于python开发并依赖于 jinja2 模板和 werkzeug WSGI 服务器的一个微型框架。
• 而werkzeug本质上是一个 socket 服务端，用于接收浏览器发送过来的请求，并进行预处理，然后再触发flask，这个时候我们就通过flask给我们提供的功能去对浏览器发送的请求做一个处理，当要处理的文件相对比较复杂时，则需要通过jinja2模板来处理，也就是我们常说的 渲染 ，之后再把处理过的数据返回给浏览器

学习链接：

2.通过Flask上传图片到服务器端(以原名保存)

server.py

from flask import request
from flask import Flask
import json
import numpy as np

import cv2
import base64
from gevent.pywsgi import WSGIServer

app = Flask(__name__)

# 定义路由
@app.route("/photo", methods=['POST'])
def get_frame():
    # 接收图片
    # upload_file = json.loads(request.json)
    # print(upload_file['file'])
    # upload_file=request.form['file']
    filename=request.get_json()
    print(filename)
    # print(type(filename)=='str')

    if (isinstance(filename,str)):
        filname1=json.loads(filename)
        tmp=filname1['file']
        name=filname1['name']
        img = base64.b64decode(str(tmp))
        image_data = np.fromstring(img, np.uint8)
        image_data = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
        cv2.imwrite('F:/pycharm/feature_match/face_result/{}'.format(name), image_data)
    else:
        tmp=filename['file']
        img = base64.b64decode(str(tmp))
        image_data = np.fromstring(img, np.uint8)
        image_data = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
        cv2.imwrite('F:/pycharm/feature_match/face_result/1.jpg', image_data)
    # fff=json.load(filename)
    # print(upload_file)
    # img=cv2.imread(tmp)
    # cv2.imwrite("222.jpg",img)
    # print(className,prob)
    json_info = json.dumps(dic, ensure_ascii=False)
    return json_info

if __name__ == "__main__":
    dic = {}
    app.run(host='10.16.55.26',port=9000)
    ## Serve the app with gevent
    # http_server = WSGIServer(('0.0.0.1',5000),app)
    # http_server.serve_forever()

        

          
        
        
        

          

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client.py

import requests
import base64,glob
import json,cv2,os
import numpy as np
# API地址
url = "http://10.16.55.26:9000/photo"

# opencv读取出来的图片相当于numpy数组
def cv2_to_base64(image):
    image1 = cv2.imencode('.jpg', image)[1]
    image_code = str(base64.b64encode(image1))[2:-1]
    return image_code

def base64_to_cv2(image_code):
    #解码
    img_data=base64.b64decode(image_code)
    #转为numpy
    img_array=np.fromstring(img_data,np.uint8)
    #转成opencv可用格式
    img=cv2.imdecode(img_array,cv2.COLOR_RGB2BGR)
    return img
# with open(r'D:\pycharm\car_fee_system\images\result\2.jpg', 'rb') as f:
#     img = base64.b64encode(f.read()).decode()
path=r'D:\pycharm\car_fee_system\images\result/'
images_paths = glob.glob(os.path.join(path + '*.jpg')) #*.jpg中的*，表示能匹配多个字符
for images_path in images_paths:
    a,b= os.path.splitext(os.path.split(images_path)[1])
    name=str(a)+str(b)
    print(name)
    image=cv2.imread(images_path)
    image_code=cv2_to_base64(image)
    image = []
    image.append(image_code)
    # 拼接参数
    files = {'file': image,'name': name}
    fff=json.dumps(files, ensure_ascii=False)
    # 发送post请求到服务器端json.dumps(files, ensure_ascii=False)
    # r = requests.post(url, json=json.dumps(files, ensure_ascii=False))
    r = requests.post(url, json=fff)
    print(r.status_code)
    print(r.content)
    print(type(json.dumps(files, ensure_ascii=False)))

        

          
        
        
        

          

          AI 代码解读
        
      
      

client_camera.py

import requests
import base64,glob
import json,cv2,os
import numpy as np
# API地址
url = "http://10.16.55.26:9000/photo"

# opencv读取出来的图片相当于numpy数组
def cv2_to_base64(image):
    image1 = cv2.imencode('.jpg', image)[1]
    image_code = str(base64.b64encode(image1))[2:-1]
    return image_code

def base64_to_cv2(image_code):
    #解码
    img_data=base64.b64decode(image_code)
    #转为numpy
    img_array=np.fromstring(img_data,np.uint8)
    #转成opencv可用格式
    img=cv2.imdecode(img_array,cv2.COLOR_RGB2BGR)
    return img
# with open(r'D:\pycharm\car_fee_system\images\result\2.jpg', 'rb') as f:
#     img = base64.b64encode(f.read()).decode()
# frame 就是每一帧图像，是个三维矩阵
# 参数是0,表示打开笔记本的内置摄像头,参数是视频文件路径则打开视频
capture = cv2.VideoCapture(0)
ret, frame = capture.read()
a='cemare1'
b=1
while ret:
    b+=1
    if b%5==0:
        ret, frame = capture.read()
        name=str(a)+'-'+str(b)
        image_code=cv2_to_base64(frame)
        image = []
        image.append(image_code)
        # 拼接参数
        files = {'file': image,'name': name}
        fff=json.dumps(files, ensure_ascii=False)
        # 发送post请求到服务器端json.dumps(files, ensure_ascii=False)
        # r = requests.post(url, json=json.dumps(files, ensure_ascii=False))
        r = requests.post(url, json=fff)
        print('200为成功 500为失败',r.status_code)
        print('正在上传第{}张图片，图片名为{}'.format(b,name))
    # print(r.content)
    # print(type(json.dumps(files, ensure_ascii=False)))

        

          
        
        
        

          

          AI 代码解读