Question

[Serializable]
    public class MyAwaitableImage : AwaitableAttachment
    {
        // Mandatory: you should have this ctor as it is used by the recognizer
        public MyAwaitableImage(Attachment source) : base(source) { }

        // Mandatory: you should have this serialization ctor as well & call base
        protected MyAwaitableImage(SerializationInfo info, StreamingContext context) : base(info, context) { }

        // Optional: here you can check for content-type for ex 'image/png' or other..
        public override async Task<ValidateResult> ValidateAsync<T>(IField<T> field, T state)
        {
            var result = await base.ValidateAsync(field, state);

            if (result.IsValid)
            {
                var isValidForMe = this.Attachment.ContentType.ToLowerInvariant().Contains("image/png");

                if (!isValidForMe)
                {
                    result.IsValid = false;
                    result.Feedback = $"Hey, dude! Provide a proper 'image/png' attachment, not any file on your computer like '{this.Attachment.Name}'!";
                }
            }

            return result;
        }

        // Optional: here you can provide additional or override custom help text completely..
        public override string ProvideHelp<T>(IField<T> field)
        {
            var help = base.ProvideHelp(field);

            help += $"{Environment.NewLine}- Only 'image/png' can be attached to this field.";

            return help;
        }

        // Optional: here you can define your custom logic to get the attachment data or add custom logic to check it, etc..
        protected override async Task<Stream> ResolveFromSourceAsync(Attachment source)
        {
            var result = await base.ResolveFromSourceAsync(source);

            // You can apply custom logic to result or avoid calling base and resolve it yourself
            // For ex. if you plan to use your instance several times you can return a MemoryStream instead

            return result;
        }
    }
// here is the form that the Bot takes to the user
    [Serializable]
    public class VehicleForm
    {
        [Prompt("What's your name?")]
        public string Name { get; set; }

        [Prompt("Upload your image")]
        public MyAwaitableImage Image;

我正在bot框架中创建一个表单，我想实现图像识别API并使用它来验证用户上传的图像。如果该图像不是人的图像，则机器人将拒绝并要求该人提供有效的图像。请我需要帮助

Answer 1

我想实现图像识别API，并使用它来验证用户上传的图像。如果该图像不是人的图像，则机器人将拒绝并要求该人提供有效的图像。

Computer Vision API可以帮助分析图像，您可以使用验证方法执行图像分析。以下示例代码对我有用，您可以参考它。

public override async Task<ValidateResult> ValidateAsync<T>(IField<T> field, T state)
{
    var result = await base.ValidateAsync(field, state);

    if (result.IsValid)
    {
        var isValidForMe = this.Attachment.ContentType.ToLowerInvariant().Contains("image/png");

        if (!isValidForMe)
        {
            result.IsValid = false;
            result.Feedback = $"Hey, dude! Provide a proper 'image/png' attachment, not any file on your computer like '{this.Attachment.Name}'!";
        }
        else
        {
            var url = this.Attachment.ContentUrl;

            HttpClient httpClient = new HttpClient();
            Stream filestrem = await httpClient.GetStreamAsync(url);
            httpClient.Dispose();

            byte[] ImageAsByteArray = null;

            using (MemoryStream ms = new MemoryStream())
            {
                int count = 0;
                do
                {
                    byte[] buf = new byte[1024];
                    count = filestrem.Read(buf, 0, 1024);
                    ms.Write(buf, 0, count);
                } while (filestrem.CanRead && count > 0);
                ImageAsByteArray = ms.ToArray();
            }

            HttpClient client = new HttpClient();

            // Request headers.
            client.DefaultRequestHeaders.Add(
                "Ocp-Apim-Subscription-Key", "{Subscription_Key_here}");

            // Request parameters. A third optional parameter is "details".
            string requestParameters =
                "visualFeatures=Categories";

            // Assemble the URI for the REST API Call.
            string uri = "https://westcentralus.api.cognitive.microsoft.com/vision/v2.0/analyze?" + requestParameters;

            HttpResponseMessage response;


            using (ByteArrayContent content = new ByteArrayContent(ImageAsByteArray))
            {
                // This example uses content type "application/octet-stream".
                // The other content types you can use are "application/json"
                // and "multipart/form-data".
                content.Headers.ContentType =
                    new MediaTypeHeaderValue("application/octet-stream");

                // Make the REST API call.
                response = await client.PostAsync(uri, content);
            }

            // Get the JSON response.
            string contentString = await response.Content.ReadAsStringAsync();

            var rs = Newtonsoft.Json.Linq.JToken.Parse(contentString);


            if (rs.HasValues)
            {
                string val = ((Newtonsoft.Json.Linq.JValue)((Newtonsoft.Json.Linq.JProperty)((Newtonsoft.Json.Linq.JContainer)((Newtonsoft.Json.Linq.JContainer)((Newtonsoft.Json.Linq.JContainer)((Newtonsoft.Json.Linq.JContainer)rs).First).First).First).First).Value).Value.ToString();

                if (val!= "people_")
                {
                    result.IsValid = false;
                    result.Feedback = $"The image '{this.Attachment.Name}' is not a person's image!";
                }
            }

        }
    }

    return result;
}

测试结果：

注意：

您还可以查看以下文档，以了解如何使用Computer Vision API /客户端库分析图像。

更新：

请我需要机器人能够描述图像内容（description），而不仅仅是进行验证。

您可以在querystring参数中包含“描述”以返回图像内容的描述。有关更多信息，您可以阅读"Computer Vision API" documentation。

string requestParameters = "visualFeatures=Categories,Description";

如何在Bot框架中将图像识别集成到formFlow

1 个答案: