Question

我正在尝试从Flask应用程序在HTML上打印字典，并且不允许这样做，并抛出以下错误。我能够成功返回字符串（https://github.com/upendrak/Disease_Predictor），但是当我更改代码以返回字典（下面的代码）时，它抛出了错误。我以为这与我不太熟悉的js有关。

这是我得到的错误

TypeError: 'list' object is not callable
The view function did not return a valid response. The return type must be a string, tuple, Response instance, or WSGI callable, but it was a list.

这是我的app.py脚本中的两个相关功能

def model_predict(img_path, model):
    img = image.load_img(img_path, target_size=(224, 224))

    # Preprocessing the image
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = x/255

    predictions = model.predict(x)
    pred_5 = np.argsort(predictions)[0][-5:]
    top_5 = {}
    labels_dict = {'Apple Scab': 0, 'Apple Black rot': 1, 'Apple Cedar rust': 2, 'Apple healthy': 3}
    for i in pred_5:
        rank = predictions[0][i]
        for kee, val in labels_dict.items():
            if i == val:
                top_5[kee] = rank

    sorted_x2 = sorted(top_5.items(), key=operator.itemgetter(1), reverse=True)
    return sorted_x2

@app.route('/predict', methods=['GET', 'POST'])
def upload():
    if request.method == 'POST':
        f = request.files['file']

        # Save the file to ./uploads
        basepath = os.path.dirname(__file__)
        file_path = os.path.join(
            basepath, 'uploads', secure_filename(f.filename))
        f.save(file_path)

        result = model_predict(file_path, model)
        return result

    return None

这是我的js文件-https://github.com/upendrak/Disease_Predictor/blob/master/static/js/main.js

Answer 1

使用[jsonify()][1]传递数据。它将数据序列化为JSON，因此返回JSON响应。不仅仅是返回return result，而是执行return jsonify(result)。

更新代码：

def model_predict(img_path, model):
    img = image.load_img(img_path, target_size=(224, 224))

    # Preprocessing the image
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = x/255

    predictions = model.predict(x)
    pred_5 = np.argsort(predictions)[0][-5:]
    top_5 = {}
    labels_dict = {'Apple Scab': 0, 'Apple Black rot': 1, 'Apple Cedar rust': 2, 'Apple healthy': 3}
    for i in pred_5:
        rank = predictions[0][i]
        for kee, val in labels_dict.items():
            if i == val:
                top_5[kee] = rank

    sorted_x2 = sorted(top_5.items(), key=operator.itemgetter(1), reverse=True)
    return sorted_x2

@app.route('/predict', methods=['GET', 'POST'])
def upload():
    if request.method == 'POST':
        f = request.files['file']

        # Save the file to ./uploads
        basepath = os.path.dirname(__file__)
        file_path = os.path.join(
            basepath, 'uploads', secure_filename(f.filename))
        f.save(file_path)

        result = model_predict(file_path, model)
        return jsonify(result)

    return None

返回字典对象时烧瓶中的响应错误

1 个答案: