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@ -24,36 +24,26 @@ Read the text 'A teddybear on a skateboard in Times Square.' to generate an text |
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*Write the pipeline in simplified style*: |
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*Write the pipeline in simplified style*: |
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```python |
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```python |
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import towhee |
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towhee.glob('./teddy.jpg') \ |
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.image_decode() \ |
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.image_text_embedding.albef(model_name='albef_4m', modality='image') \ |
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.show() |
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from towhee.dc2 import pipe, ops, DataCollection |
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towhee.dc(["A teddybear on a skateboard in Times Square."]) \ |
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.image_text_embedding.albef(model_name='albef_4m', modality='text') \ |
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.show() |
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``` |
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<img src="./vec1.png" alt="result1" style="height:20px;"/> |
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<img src="./vec2.png" alt="result2" style="height:20px;"/> |
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img_pipe = ( |
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pipe.input('url') |
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.map('url', 'img', ops.image_decode.cv2_rgb()) |
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.map('img', 'vec', ops.image_text_embedding.albef(model_name='albef_4m', modality='image')) |
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.output('img', 'vec') |
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) |
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*Write a same pipeline with explicit inputs/outputs name specifications:* |
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text_pipe = ( |
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pipe.input('text') |
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.map('text', 'vec', ops.image_text_embedding.albef(model_name='albef_4m', modality='text')) |
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.output('text', 'vec') |
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) |
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```python |
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import towhee |
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towhee.glob['path']('./teddy.jpg') \ |
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.image_decode['path', 'img']() \ |
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.image_text_embedding.albef['img', 'vec'](model_name='albef_4m', modality='image') \ |
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.select['img', 'vec']() \ |
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.show() |
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towhee.dc['text'](["A teddybear on a skateboard in Times Square."]) \ |
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.image_text_embedding.albef['text','vec'](model_name='albef_4m', modality='text') \ |
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.select['text', 'vec']() \ |
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.show() |
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DataCollection(img_pipe('./teddy.jpg')).show() |
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DataCollection(text_pipe('A teddybear on a skateboard in Times Square.')).show() |
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``` |
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``` |
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<img src="./tabular1.png" alt="result1" style="height:60px;"/> |
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<img src="./tabular1.png" alt="result1" style="height:60px;"/> |
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<img src="./tabular2.png" alt="result2" style="height:60px;"/> |
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<img src="./tabular2.png" alt="result2" style="height:60px;"/> |
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