如何使用 Flask 将 json 字符串传递给 url

Question

我确实使用 Pytorch 创建了一个机器学习模型，我想将其用作使用 Flask 的网络服务。问题是我不明白如何将 json-String 传递给 url。下面是我编写的代码，用于对我的模型和 Flask 进行一些试验：

from modelLoader import Model
from imageLoader import Img
import os
from flask import Flask, jsonify, request

app = Flask(__name__)
classes = ["dummy-image", "product-image"]
model_path = os.path.join("data", "models", "model1709", "model1709")
image_path = os.path.join("data", "images", "dummy_images")
m1 = Model(model_path, classes, "cpu")

@app.route('/predict', methods=['POST', 'GET'])
def predict():
    # case for handle json
    input_data = request.get_json()['url']
    if isinstance(input_data, list):
        for elem in input_data:
            img_elem = Img(url=elem)
            res = img_elem.get_prediction(m1)
        return jsonify({"type": "bulk_upload"})
    img_inpdata = Img(url=input_data)
    res, info = img_inpdata.get_prediction(m1)
    return jsonify({input_data: res, "info": str(info)})


if __name__ == '__main__':
    app.run(debug=True)

这将是我想使用此代码发出的请求：

POST http://192.168.178.13:5000/predict HTTP/1.1
Content-Type: application/json
Accept: application/json

{
    "url" : "https://socialistmodernism.com/wp-content/uploads/2017/07/placeholder-image.png"
}

通过将此 json 字符串传递给应用程序，我如何才能准确预测 json 字符串中的图像？

为了完整起见，这里有两个类模型和 imageLoader：

from torch import argmax, device, load, nn

class Model:
    def __init__(self, path, class_list=None, dvc=None):
        if class_list is None:
            class_list = [0, 1]
        if dvc is None:
            dvc = 'cpu'
        self.class_list = class_list 
        self.model = load(path, map_location=device(dvc))
        num_ftrs = self.model.fc.in_features                  
        self.model.fc = nn.Linear(num_ftrs, len(class_list))  
        self.model.eval()

import torchvision.transforms as transforms
import io
from PIL import Image
from torch import argmax, device, load, nn
import requests

class Img:
    def __init__(self, url=None, image=None, image_bytes=None):
        if url:
            img = Image.open(requests.get(url, stream=True).raw)
            img_byte_arr = io.BytesIO()
            img.save(img_byte_arr, format=img.format)
            self.image_bytes = img_byte_arr.getvalue()
        elif image:
            f = image.read()
            self.image_bytes = bytearray(f)
        elif image_bytes:
            self.image_bytes = image_bytes

    def transform_image(self):
        data_transforms = transforms.Compose([transforms.Resize((224, 224)),
                                              transforms.CenterCrop(
                                                  224), transforms.ToTensor(),
                                              transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224,
                                                                                           0.225])])
        image = Image.open(io.BytesIO(self.image_bytes)).convert('RGB')
        return data_transforms(image).unsqueeze(0)

    def get_prediction(self, model):
        tensor = self.transform_image()
        output = (model.model(tensor))
        sm = nn.Softmax(output)
        best = output.argmax().item()
        return model.class_list[best], sm

Answer 1

您不能直接从浏览器 URL 框执行 POST 请求。有很多应用程序可以测试您的 API，我最喜欢的是 postman。也可以使用curl命令工具。

如果只想使用浏览器 URL 框，请考虑使用 GET 请求。 GET请求的格式为?parameter1=value1¶meter2=value2。您可以使用请求模块访问 flask 中的参数值。例如，如果您的服务位于 http://192.168.178.13:5000/predict. You can send it as http://192.168.178.13:5000/predict?url=your-url。你可以在烧瓶中获取它作为

from flask import request
my_url = request.args.get("url")

如何使用 Flask 将 json 字符串传递给 url

how to pass a json String to a url using Flask

python

json

flask

jsonify