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我正在从用户那里获取上传的图像，然后将其发送到 YOLO 模型，然后该模型返回给我一张图像。

我想将返回的图像存储在我的本地目录中，然后将其显示在用户界面上。

这是views.py接收图像并将其发送到 Yolo 模型的代码，

def predictImage(request):
    # print(request)
    # print(request.POST.dict())
    fileObj = request.FILES['filePath']
    fs = FileSystemStorage()
    filePathName = fs.save(fileObj.name, fileObj)
    filePathName = fs.url(filePathName)
    testimage = '.'+filePathName
    # img = image.load_img(testimage, target_size=(img_height, img_width))
    img = detect_image(testimage)
    filePathName = fs.save(fileObj.name + "_result", img) # -> HERE IS THE ERROR
    filePathName = fs.url(filePathName)

这是 YOLO 模型的函数，它使用 OpenCV 读取图像（图像作为参数发送给函数）然后返回该图像，

import numpy as np
import cv2

def detect_image(img_path):

    confidenceThreshold = 0.5
    NMSThreshold = 0.3

    modelConfiguration = 'cfg/yolov3.cfg'
    modelWeights = 'yolov3.weights'

    labelsPath = 'coco.names'
    labels = open(labelsPath).read().strip().split('\n')

    np.random.seed(10)
    COLORS = np.random.randint(0, 255, size=(len(labels), 3), dtype="uint8")

    net = cv2.dnn.readNetFromDarknet(modelConfiguration, modelWeights)

    image = cv2.imread(img_path)
    (H, W) = image.shape[:2]

    #Determine output layer names
    layerName = net.getLayerNames()
    layerName = [layerName[i - 1] for i in net.getUnconnectedOutLayers()]

    blob = cv2.dnn.blobFromImage(image, 1 / 255.0, (416, 416), swapRB = True, crop = False)
    net.setInput(blob)
    layersOutputs = net.forward(layerName)

    boxes = []
    confidences = []
    classIDs = []

    for output in layersOutputs:
        for detection in output:
            scores = detection[5:]
            classID = np.argmax(scores)
            confidence = scores[classID]
            if confidence > confidenceThreshold:
                box = detection[0:4] * np.array([W, H, W, H])
                (centerX, centerY,  width, height) = box.astype('int')
                x = int(centerX - (width/2))
                y = int(centerY - (height/2))

                boxes.append([x, y, int(width), int(height)])
                confidences.append(float(confidence))
                classIDs.append(classID)

    #Apply Non Maxima Suppression
    detectionNMS = cv2.dnn.NMSBoxes(boxes, confidences, confidenceThreshold, NMSThreshold)

    if(len(detectionNMS) > 0):
        for i in detectionNMS.flatten():
            (x, y) = (boxes[i][0], boxes[i][1])
            (w, h) = (boxes[i][2], boxes[i][3])

            color = [int(c) for c in COLORS[classIDs[i]]]
            cv2.rectangle(image, (x, y), (x + w, y + h), color, 2)
            text = '{}: {:.4f}'.format(labels[classIDs[i]], confidences[i])
            cv2.putText(image, text, (x, y - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
    
    return image 
    
    #cv2.imshow('Image', image)
    #cv2.waitKey(0)

在这条线上，

filePathName = fs.save(fileObj.name + "_result", img)

我收到以下错误，

'numpy.ndarray' object has no attribute 'read'

我不确定如何解决这个问题。我尝试搜索如何存储 OpenCV 修改文件 usnig FileSystemStorage 但没有找到任何帮助。任何人都可以帮我解决这个问题吗？

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1 回答 1

1

您可以使用库的imwrite功能cv2将文件存储在本地目录中，即

在您的情况下，只需执行此操作，

img = detect_image(testimage)
cv2.imwrite(fileObj.name+"_result.jpg", img=img)
于 2022-02-13T16:57:34.897 回答