@ -41,11 +41,11 @@ You can get the required python package by [requirements.txt](./requirements.txt
### How it works
### How it works
The towhee/resnet50_image_embedding Operator implements the function of image embedding, which can add to the pipeline, for example, it's the key Operator within [image_embedding_resnet50](https://hub.towhee.io/towhee/image-embedding-resnet50) pipeline, and it is the red box in the picture below.
The `towhee/resnet50-image-embedding` Operator implements the function of image embedding, which can add to the pipeline, for example, it's the key Operator named embedding_model within [image_embedding_resnet50](https://hub.towhee.io/towhee/image-embedding-resnet50) pipeline, and it is the red box in the picture below.


When using this Operator to write Pipline's Yaml file, you need to declare the following content according to the interface of resnet50_image_embedding class:
When using this Operator to write Pipline's Yaml file, you need to declare the following content according to the interface of Resnet50ImageEmbedding class:
```yaml
```yaml
operators:
operators:
@ -100,7 +100,7 @@ Here is the main file structure of the `resnet50-image-embedding` Operator. If y
│ ├── requirements.txt #The python dependency package for the pytorch model.
│ ├── requirements.txt #The python dependency package for the pytorch model.
│ └── model.py #The code of the pytorch model, including the initialization model and prediction.
│ └── model.py #The code of the pytorch model, including the initialization model and prediction.
├── test_data/ #The directory of test data, including test.jpg
├── test_data/ #The directory of test data, including test.jpg
└── test_resnet50_image_embedding.py #The unittest file of the Operator.
└── test_resnet50_image_embedding.py #The unittest file of this Operator.