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Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
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Jael Gu 3 years ago
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README.md

@ -13,35 +13,34 @@ which maintains SOTA deep-learning models and tools in computer vision.
## Code Example
Load an image from path './dog.jpg'
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*:
```python
from towhee import dc
import towhee
dc.glob('./dog.jpg') \
.image_decode.cv2() \
.image_embedding.timm(model_name='resnet50') \
.show()
towhee.glob('./towhee.jpg') \
.image_decode.cv2() \
.image_embedding.timm(model_name='resnet50') \
.show()
```
| [0.052790146, 0.0, 0.0, ...] shape=(2048,) |
<img src="https://towhee.io/image-embedding/timm/src/branch/main/result1.png" alt="result1" style="width:50px;"/>
![result1](result1.png)
*Write a same pipeline with explicit inputs/outputs name specifications:*
```python
from towhee import dc
import towhee
dc.glob['path']('./dog.jpg') \
.image_decode.cv2['path', 'img']() \
.image_embedding.timm['img', 'vec'](model_name='resnet50') \
.select('vec') \
.to_list()
towhee.glob['path']('./dog.jpg') \
.image_decode.cv2['path', 'img']() \
.image_embedding.timm['img', 'vec'](model_name='resnet50') \
.select('img', 'vec') \
.show('img', 'vec')
```
[array([0.05279015, 0. , 0. , ..., 0.00239191, 0.06632169,
0. ], dtype=float32)]
## Factory Constructor

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