This pipeline includes two main operators: [transform image](https://hub.towhee.io/towhee/transform-image-operator-class) (implemented as [towhee/transform-image](https://hub.towhee.io/towhee/transform-image)) and [image embedding](https://hub.towhee.io/towhee/image-embedding-operator-class) (implemented as [towhee/resnet50-image-embedding](https://hub.towhee.io/towhee/resnet50-image-embedding)). The transform image op will first convert the original image into a normalized format, such as with 512x512 resolutions. Then, the normalized image will be encoded via image embedding op, and finally we get a feature vector of the given image.
This pipeline includes two main operators: [transform image](https://hub.towhee.io/towhee/transform-image-operator-class) (implemented as [towhee/transform-image](https://hub.towhee.io/towhee/transform-image)) and [image embedding](https://hub.towhee.io/towhee/image-embedding-operator-class) (implemented as [towhee/resnet50-image-embedding](https://hub.towhee.io/towhee/resnet50-image-embedding)). The transform image operator will first convert the original image into a normalized format, such as with 512x512 resolutions. Then, the normalized image will be encoded via image embedding operator, and finally we get a feature vector of the given image.
> Refer [Towhee architecture](https://github.com/towhee-io/towhee#towhee-architecture) for basic concepts in Towhee: pipeline, operator, dataframe.
