不可JSON序列化

Question

我已经建立了CNN模型，并且能够很好地进行分类。但是我想尝试使用Django在URL中传递图像时对图像的类进行分类。这是我尝试过的几件事。我的apps.py中的预测功能

def prediction(image_loc):
    image_path = 'D:/Discern/'
    image = cv2.imread(os.path.join(image_path,image_loc))
    print("image in matrix is ", image)
    output = image.copy()

    # Pre-Process the image for classification
    image = cv2.resize(image, (96, 96))
    image = image.astype("float") / 255.0
    image = img_to_array(image)
    image = np.expand_dims(image, axis=0)

    # Load the trained convolutional neural network and the label binarizer
    print("[INFO] Loading Model...")
    model_RP = load_model(os.path.join(os.getcwd(), "model\cnn_model_RP.hdf5"))
    lb_path = os.path.join(os.getcwd(),"model\labelbin_RP")
    lb_RP = pickle.loads(open(lb_path, "rb").read())
    print("[INFO] Model Loading Complete.")

    # Classify the input image
    print("[INFO] classifying image...")
    proba = model_RP.predict(image)[0]
    idx = np.argmax(proba)
    label = lb_RP.classes_[idx]

    #we will mark our prediction as "correct" of the input image filename contains the predicted label text 
    #(obviously this makes the assumption that you have named your testing image files this way)

    filename = image_loc[image_loc.rfind(os.path.sep) + 1:]
    correct = "correct" if filename.rfind(label) != -1 else "incorrect"

    # Build the label and draw the label on the image
    label = "{}: {:.2f}% ({})".format(label, proba[idx] * 100, correct)
    output = imutils.resize(output, width=400)
    cv2.putText(output, label, (10, 25),  cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 0, 0), 2)

    # show the output image
    print("[INFO] {}".format(label))
    #plt.imshow(output)
    #plt.show()

    #return(plt.show())
    return(label) #- WORKING

    #return HttpResponse(output, content_type = 'image/png')  
    #resp = HttpResponse("", content_type = 'image/png')
    #resp.write('output')
    #return resp

1. [如果我只返回它可以使用的标签，则下面是我的apps.py中的代码段

    label = "{}: {:.2f}% ({})".format(label, proba[idx] * 100, correct)
    return (label)

2.a这是问题所在。我正在尝试返回带有标签的图像。我不成功。

    label = "{}: {:.2f}% ({})".format(label, proba[idx] * 100, correct)
    output = imutils.resize(output, width=400)
    cv2.putText(output, label, (10, 25),  cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 0, 0), 2) 

    return HttpResponse(output, content_type = 'image/png')

2.b，这是第二种返回图像的方法，不幸的是失败了。

     label = "{}: {:.2f}% ({})".format(label, proba[idx] * 100, correct)
     output = imutils.resize(output, width=400)
     cv2.putText(output, label, (10, 25),  cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 0, 0), 2)      
     resp = HttpResponse("", content_type = 'image/png')
     resp.write('output')
     return resp

3. 这是我的views.py

@api_view(['GET'])  # Decorator
def call_model(request):
    #if request.method == 'GET':

            # sentence is the query we want to get the prediction for
    params =  request.GET.get('image_loc')

            # predict method used to get the prediction
    resp = prediction(image_loc = params)

            # returning JSON response
    return Response(resp) 

曾尝试查看类似的帖子，但它们与文本有关，因此无法解决我的问题。

[有人可以帮忙。

Answer 1

resp似乎是一个HttpResponse对象（不能告诉更多，您没有提供prediction的代码）。

您必须在Response()构造函数中创建可序列化的JSON（通常是字典或列表，仅包含字符串/ int /布尔值）。

（（顺便说一下，DRF的@api_view装饰器已过时，@action在上一个版本中更受欢迎）