Azure Face API 的 Large Face List 是否应该在每次添加新面孔时进行训练？
Should Azure Face API's Large Face List be trained every time a new face is added to it?
我将 Microsoft Cognitive Services Face API 用于人脸识别项目，用户在一段时间内不断添加人脸。以前，面孔存储在 "Face List" 中。我现在要把脸换成 "Large Face List"。但是，它需要一个训练调用，"Face Lists" 不需要。
我找不到任何提到 if
的文档
- 我们必须训练一次？或者
- 每加一张脸就训练一次？
FaceAPI一开始的REST documentation for Face API but it is stated in the actual documentation中并没有说明。
To enable Face search performance for Identification and FindSimilar
in large scale, introduce a Train operation to preprocess the
LargeFaceList and LargePersonGroup. The training time varies from
seconds to about half an hour based on the actual capacity. During the
training period, it's possible to perform Identification and
FindSimilar if a successful training operating was done before. The
drawback is that the new added persons and faces don't appear in the
result until a new post migration to large-scale training is
completed.
这意味着每次添加面孔时都需要对其进行训练，因为 LargeFaceList 用于大规模使用（最多 1,000,000 张面孔），因此，如果您不这样做需要该容量，那么您可能希望使用 FaceList（最多 1,000 张面孔），因为它不需要每次都进行培训。
我将 Microsoft Cognitive Services Face API 用于人脸识别项目，用户在一段时间内不断添加人脸。以前，面孔存储在 "Face List" 中。我现在要把脸换成 "Large Face List"。但是，它需要一个训练调用，"Face Lists" 不需要。
我找不到任何提到 if
的文档- 我们必须训练一次？或者
- 每加一张脸就训练一次？
FaceAPI一开始的REST documentation for Face API but it is stated in the actual documentation中并没有说明。
To enable Face search performance for Identification and FindSimilar in large scale, introduce a Train operation to preprocess the LargeFaceList and LargePersonGroup. The training time varies from seconds to about half an hour based on the actual capacity. During the training period, it's possible to perform Identification and FindSimilar if a successful training operating was done before. The drawback is that the new added persons and faces don't appear in the result until a new post migration to large-scale training is completed.
这意味着每次添加面孔时都需要对其进行训练，因为 LargeFaceList 用于大规模使用（最多 1,000,000 张面孔），因此，如果您不这样做需要该容量，那么您可能希望使用 FaceList（最多 1,000 张面孔），因为它不需要每次都进行培训。