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This of Model Builder comes with bug fixes and two exciting new features:
此的Model Builder带有错误修复和两个令人兴奋的新功能:
We showed off this feature in .NET Conf to classify the weather in images as either sunny, cloudy, or rainy, and now you can locally train image classification models in Model Builder with your own images!
我们在.NET Conf中展示了此功能,可以将图像中的天气分类为晴天,阴天或下雨,现在您可以在Model Builder中使用自己的图像在本地训练图像分类模型!
For example, say you have a dataset of images of dogs and cats, and you want to use those images to train an ML.NET model that classifies new images as «dog» or «cat.»
例如,假设您有一个猫和狗的图像数据集,并且想要使用这些图像来训练ML.NET模型,该模型将新图像分类为“狗”或“猫”。
Your dataset must contain a parent folder with labelled subfolders for each category (e.g. a folder called Animals that contains two sub-folders: one named Dog, which contains training images of dogs, and one named Cat, which contains training images of cats):
您的数据集必须包含一个父文件夹,该文件夹的每个类别都带有标记的子文件夹(例如,名为Animals的文件夹包含两个子文件夹:一个名为Dog的文件夹,其中包含狗的训练图像;一个名为Cat的文件夹,其中包含猫的训练图像):
You can use the Next Steps code and projects generated by Model Builder to easily consume the trained image classification model in your end-user application, just like with text scenarios.
您可以使用“模型开发器”生成的“下一步”代码和项目来轻松使用最终用户应用程序中经过训练的图像分类模型,就像使用文本方案一样。
After training a model in Model Builder, you can use the model to make predictions on sample input right in the UI for both text and image scenarios.
在“模型构建器”中训练了模型之后,您可以使用模型在UI中针对文本和图像场景对样本输入进行预测。
For instance, for the dog vs. cat image classification example, you could input an image and see the results in the Evaluate step of Model Builder:
例如,对于狗与猫的图像分类示例,您可以输入图像并在“模型构建器”的“评估”步骤中查看结果:
If you have a text scenario, like price prediction for taxi fare, you can also input sample data in the Try your model section:
如果您有文字场景,例如出租车价格预测,也可以在“ 尝试您的模型”部分中输入示例数据:
If you run into any issues, feel that something is missing, or really love something about ML.NET Model Builder, let us know by creating an issue in our .
如果遇到任何问题,觉得缺少某些东西,或者真的很喜欢ML.NET Model Builder,请在创建一个问题,让我们知道。
Model Builder is still in Preview, and your feedback is super important in driving the direction we take with this tool!
模型构建器仍处于预览状态,您的反馈对于推动我们使用此工具的发展方向至关重要!
You can download ML.NET Model Builder in the (or in the Extensions menu of Visual Studio).
您可以在 (或Visual Studio的“扩展”菜单)中下载ML.NET Model Builder。
Learn more in the or get started with this .
在了解更多信息,或开始学习本 。
Not currently using Visual Studio? Try out the (image classification not yet implemented).
当前不使用Visual Studio吗? 试用 (尚未实现图像分类)。
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