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我有一个像这样运行的python脚本：

python age_detect.py --image images/name.jpg --face face_detector --age age_detector

我还有一个 Django 应用程序，它是上传表单，您可以在其中上传照片，我只需要在上传图像后，我可以使用上传的图像运行脚本并将其显示在应用程序中。

我的意见.py：

 from django.shortcuts import render
 from .forms import ImageForm


def image_upload_view(request):
    if request.method == 'POST':
        form = ImageForm(request.POST, request.FILES)
        if form.is_valid():
            form.save()
            img_obj = form.instance
            return render(request, 'upload.html', {'form': form, 'img_obj': img_obj})
    else:
        form = ImageForm()
    return render(request, 'upload.html', {'form': form})

你们能帮我解答我的问题吗？

脚本.py

import numpy as np
import argparse
import cv2
import os



ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True, help="Path to input image")
ap.add_argument("-f", "--face", required=True, help="Path to face detector model directory")
ap.add_argument("-a", "--age", required=True, help="Path to age detector model directory")
ap.add_argument("-c", "--confidence", type=float, default=0.5, help="Minimum probability to filter weak detections")
args = vars(ap.parse_args())
AGE_BUCKETS = ["(0-2)", "(4-6)", "(8-12)", "(15-20)", "(25-32)", "(38-43)", "(48-53)", "(60-100)"]
prototxtPath = os.path.sep.join([args["face"], "deploy.prototxt"])
weightsPath = os.path.sep.join([args["face"], "res10_300x300_ssd_iter_140000.caffemodel"])
faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
prototxtPath = os.path.sep.join([args["age"], "age_deploy.prototxt"])
weightsPath = os.path.sep.join([args["age"], "age_net.caffemodel"])
ageNet = cv2.dnn.readNet(prototxtPath, weightsPath)
image = cv2.imread(args["image"])
(h, w) = image.shape[:2]
blob = cv2.dnn.blobFromImage(image, 1.0, (300, 300), (104.0, 177.0, 123.0))
faceNet.setInput(blob)
detections = faceNet.forward()


for i in range(0, detections.shape[2]):
    confidence = detections[0, 0, i, 2]
    if confidence > args["confidence"]:
        box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
        (startX, startY, endX, endY) = box.astype("int")
        face = image[startY:endY, startX:endX]
        faceBlob = cv2.dnn.blobFromImage(face, 1.0, (227, 227), (78.4263377603, 87.7689143744, 114.895847746),
                                         swapRB=False)
        ageNet.setInput(faceBlob)
        preds = ageNet.forward()
        i = preds[0].argmax()
        age = AGE_BUCKETS[i]
        ageConfidence = preds[0][i]
        text = "{}: {:.2f}%".format(age, ageConfidence * 100)
        print("[INFO] {}".format(text))
        y = startY - 10 if startY - 10 > 10 else startY + 10
        cv2.rectangle(image, (startX, startY), (endX, endY), (0, 0, 255), 2)
        cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)


cv2.imwrite("C:/Users/root/PycharmProjects/agedetection/deeplearning/images/kanat_mod.jpg", image)
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