python中url变换

Question

如何将下面静态的url修改成动态的url（url是后端将数据库的内容与我的接口做链接，数据库给什么url我的接口就自动变换成什么url），同时要将处理完的代码返还给后端。

import os
import random
import time
import cv2
import onnxruntime
from opt_einsum.backends import torch
from tool import *
from flask import Flask, request, jsonify
import numpy as np
from urllib.request import urlopen

app = Flask(__name__)

def onnx_load(w):
    cuda = torch.cuda.is_available()
    providers = ['CUDAExecutionProvider', 'CPUExecutionProvider'] if cuda else ['CPUExecutionProvider']
    session = onnxruntime.InferenceSession(w, providers=providers)
    output_names = [x.name for x in session.get_outputs()]
    return session, output_names

def calculate_height(bbox):
    height = bbox[3] - bbox[1]
    return height

def annotate_image(image, boxes, labels):
    for box, label in zip(boxes, labels):
        x1, y1, x2, y2 = [int(coord) for coord in box]
        cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.putText(image, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
    return image

def url_to_image(url):
    try:
        resp = urlopen(url)
        image = np.asarray(bytearray(resp.read()), dtype="uint8")
        image = cv2.imdecode(image, cv2.IMREAD_COLOR)
        return image
    except Exception as e:
        print(f"从URL {url} 获取图像时出错：{e}")
        return None

@app.route('/process_image', methods=['POST'])
def process_image():
    data = request.get_json()
    w = data['model_path']
    image_url = 'https://hoire.oss-cn-shenzhen.aliyuncs.com/313254_638567497450816069.jpg'
    imgsz = [640, 640]

    session, output_names = onnx_load(w)
    device = torch.device('cuda:0')

    im0 = url_to_image(image_url)
    if im0 is None:
        return jsonify({"error": f"Unable to load image from URL: {image_url}"}), 400

    im, org_data = data_process_cv2(im0, imgsz)
    start_time = time.time()
    y = session.run(output_names, {session.get_inputs()[0].name: im})
    pred = torch.from_numpy(y[0]).to(device)
    pred = non_max_suppression(pred, conf_thres=0.25, iou_thres=0.45, max_det=1000)
    spend_time_ms = (time.time() - start_time) * 1000

    res_img = post_process_yolov5(pred[0], org_data)
    boxes = []
    labels = []
    person_heights = []
    bicycle_heights = []

    if pred[0] is not None and isinstance(pred[0], torch.Tensor):
        for det in pred[0]:
            if det is not None and len(det) >= 4:
                box = det[:4].tolist()
                boxes.append(box)
                height = calculate_height(box)
                class_id = int(det[5].item()) if len(det) > 5 else -1
                label = 'person' if class_id == 1 else 'bicycle' if class_id == 0 else 'unknown'
                labels.append(f'{label}: {height:.2f}')

                if label == 'person':
                    person_heights.append(height)
                elif label == 'bicycle':
                    bicycle_heights.append(height)
    else:
        return jsonify({"error": "pred[0] is either None or not a Tensor."}), 400

    res_img = annotate_image(res_img, boxes, labels)
    save_dir = 'D:/sansheng/zg/jiekou/image/train'
    os.makedirs(save_dir, exist_ok=True)
    res_img_name = f"res_{os.path.basename(image_url)}"
    res_img_path = os.path.join(save_dir, res_img_name)
    cv2.imwrite(res_img_path, res_img)

    response = {
        "spend_time_ms": spend_time_ms,
        "annotated_image_path": res_img_path,
        "average_person_height": sum(person_heights) / len(person_heights) if person_heights else None,
        "average_bicycle_height": sum(bicycle_heights) / len(bicycle_heights) if bicycle_heights else None,
    }

    return jsonify(response), 200

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

 

import requests

# 定义接口的URL
url = 'http://192.168.0.75:5000/process_image'
data = {
    'model_path': 'best.onnx',  # 指定要使用的ONNX模型文件路径
    # 'image_url': 'https://hoire.oss-cn-shenzhen.aliyuncs.com/313254_638567497450816069.jpg'  # 要处理的图像文件路径
}

# 发送POST请求到接口，并传递数据
response = requests.post(url, json=data)

# 检查请求是否成功
if response.status_code == 200:
    result = response.json()
    print(f"输出处理时间: {result['spend_time_ms']} ms")
    print(f"输出保存的标注图像路径: {result['annotated_image_path']}")
    if result['average_person_height']:
        print(f"玉米的平均高度: {result['average_person_height']:.2f}")
    if result['average_bicycle_height']:
        print(f"竹竿的平均高度: {result['average_bicycle_height']:.2f}")
    # 计算株高并保留两位小数
    zhugao = round((result['average_person_height'] / result['average_bicycle_height']) * 370, 2)
    print(f"株高: {zhugao}")
else:
    print(f"Error: {response.json()['error']}")

Answer 1

以下内容由AIGC及阿里嘎多学长共同生成、有用望采纳：

---

您的代码实现思路是正确的。下面是根据您提供的代码和需求，对您的代码进行的一些修改和补充，以实现动态URL的修改和结果的返回。

1. 修改静态URL为动态URL：
   • 在process_image函数中，从POST请求的数据中获取image_url，如果请求中没有提供，则使用默认URL。

@app.route('/process_image', methods=['POST'])
def process_image():
    data = request.get_json()
    w = data['model_path']
    image_url = data.get('image_url', 'https://hoire.oss-cn-shenzhen.aliyuncs.com/313254_638567497450816069.jpg')  # 使用POST请求中的URL或默认URL
    # ... 其他代码保持不变

1. 处理完图像后将结果返还给后端：

   • 您的代码已经实现了这一功能，通过jsonify(response)将处理结果以JSON格式返回。

2. 发送POST请求并接收响应：

   • 您的客户端代码已经正确地实现了发送POST请求并接收响应的功能。

3. 检查响应并处理结果：

   • 您的客户端代码已经正确地实现了检查响应状态码，并根据状态码打印相关信息或错误。

以下是整合后的完整process_image函数示例：

@app.route('/process_image', methods=['POST'])
def process_image():
    data = request.get_json()
    w = data['model_path']
    image_url = data.get('image_url', 'https://hoire.oss-cn-shenzhen.aliyuncs.com/313254_638567497450816069.jpg')  # 默认URL

    # ... 省略其他函数定义和处理逻辑

    # 处理图像的逻辑
    # ...

    # 构造响应数据
    response = {
        "spend_time_ms": spend_time_ms,
        "annotated_image_path": res_img_path,
        "average_person_height": sum(person_heights) / len(person_heights) if person_heights else None,
        "average_bicycle_height": sum(bicycle_heights) / len(bicycle_heights) if bicycle_heights else None,
    }

    # 返回JSON格式的响应
    return jsonify(response), 200

确保您的客户端代码已经包含了发送POST请求和接收响应的逻辑，如下所示：

import requests

# 定义接口的URL
url = 'http://192.168.0.75:5000/process_image'
data = {
    'model_path': 'best.onnx',  # 指定要使用的ONNX模型文件路径
    'image_url': '动态获取的URL',  # 从数据库或其他来源动态获取的URL
}

# 发送POST请求到接口，并传递数据
response = requests.post(url, json=data)

# 检查请求是否成功
if response.status_code == 200:
    result = response.json()
    # 打印输出处理时间、标注图像路径等信息
    # ...
else:
    print(f"Error: {response.json()['error']}")

这样，您的接口就可以根据后端提供的数据库内容动态地变换URL，并且在处理完图像后将结果以JSON格式返还给后端。