An image embedding pipeline generates a vector given an image. This Pipeline extracts features for image with 'ResNet50' models provided by [Timm](https://github.com/rwightman/pytorch-image-models). Timm is a deep-learning library developed by [Ross Wightman](https://twitter.com/wightmanr), who maintains SOTA deep-learning models and tools in computer vision.
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## Code Example
@ -33,6 +35,8 @@ res = p('https://github.com/towhee-io/towhee/raw/main/towhee_logo.png')
res.get()
```
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## **Configuration**
@ -61,6 +65,8 @@ The flag to control whether to skip image pre-process. The default value is Fals
The number of GPU device, defaults to -1, which means using CPU.
