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GuoRentong 3 years ago
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README.md

@ -18,13 +18,13 @@ which maintains SOTA deep-learning models and tools in computer vision.
Load an image from path './towhee.jpg'
and use the pretrained ResNet50 model ('resnet50') to generate an image embedding.
*Write the pipeline in simplified style*:
*Write the pipeline in simplified style:*
```python
import towhee
towhee.glob('./towhee.jpg') \
.image_decode.cv2() \
.image_decode() \
.image_embedding.timm(model_name='resnet50') \
.show()
```
@ -36,9 +36,9 @@ towhee.glob('./towhee.jpg') \
import towhee
towhee.glob['path']('./towhee.jpg') \
.image_decode.cv2['path', 'img']() \
.image_decode['path', 'img']() \
.image_embedding.timm['img', 'vec'](model_name='resnet50') \
.select('img', 'vec') \
.select['img', 'vec']() \
.show()
```
<img src="./result2.png" height="150px"/>
@ -53,18 +53,17 @@ Create the operator via the following factory method
**Parameters:**
***model_name***: *str*
***model_name:*** *str*
The model name in string. The default value is "resnet34".
Refer [Timm Docs](https://fastai.github.io/timmdocs/#List-Models-with-Pretrained-Weights) to get a full list of supported models.
***num_classes***: *int*
***num_classes:*** *int*
The number of classes. The default value is 1000.
It is related to model and dataset.
***skip_preprocess***: *bool*
***skip_preprocess:*** *bool*
The flag to control whether to skip image preprocess.
The default value is False.
@ -78,18 +77,15 @@ In this case, input image data must be prepared in advance in order to properly
An image embedding operator takes a towhee image as input.
It uses the pre-trained model specified by model name to generate an image embedding in ndarray.
**Parameters:**
***img***: *towhee.types.Image (a sub-class of numpy.ndarray)*
***img:*** *towhee.types.Image (a sub-class of numpy.ndarray)*
The decoded image data in numpy.ndarray.
**Returns**:
*numpy.ndarray*
**Returns:** *numpy.ndarray*
The image embedding extracted by model.

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