From 14ccc47f153c70f451688e70e533117f211d83da Mon Sep 17 00:00:00 2001 From: wxywb Date: Fri, 22 Jul 2022 17:36:47 +0800 Subject: [PATCH] update the readme. Signed-off-by: wxywb --- README.md | 110 ++++++++++++++++++++++++++++++++++++++++++++++++++- tabular1.png | Bin 0 -> 122681 bytes tabular2.png | Bin 0 -> 16750 bytes vec1.png | Bin 0 -> 10656 bytes vec2.png | Bin 0 -> 10212 bytes 5 files changed, 109 insertions(+), 1 deletion(-) create mode 100644 tabular1.png create mode 100644 tabular2.png create mode 100644 vec1.png create mode 100644 vec2.png diff --git a/README.md b/README.md index cb0b00f..0d5a3e3 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,110 @@ -# slip +# Image-Text Retrieval Embdding with SLIP + +*author: David Wang* + + +
+ + + +## Description + +This operator extracts features for image or text with [SLIP](https://arxiv.org/abs/2112.12750), a multi-task learning framework for combining self-supervised learning and CLIP pre-training. This is an adaptation from [facebookresearch/SLIP](https://github.com/facebookresearch/SLIP). + + +
+ + +## Code Example + +Load an image from path './teddy.jpg' to generate an image embedding. + +Read the text 'A teddybear on a skateboard in Times Square.' to generate an text embedding. + + *Write the pipeline in simplified style*: + +```python +import towhee + +towhee.glob('./moon.jpeg') \ + .image_decode() \ + .image_text_embedding.slip(model_name='slip_vit_small', modality='image') \ + .show() + +towhee.dc(['moon in the night.']) \ + .image_text_embedding.slip(model_name='slip_vit_small', modality='text') \ + .show() +``` +result1 +result2 + +*Write a same pipeline with explicit inputs/outputs name specifications:* + +```python +import towhee + +towhee.glob['path']('./moon.jpeg') \ + .image_decode['path', 'img']() \ + .image_text_embedding.slip['img', 'vec'](model_name='slip_vit_small', modality='image') \ + .select['img', 'vec']() \ + .show() + +towhee.dc['text'](['moon in the night.']) \ + .image_text_embedding.slip['text','vec'](model_name= 'slip_vit_small', modality='text') \ + .select['text', 'vec']() \ + .show() +``` +result1 +result2 + + +
+ + + +## Factory Constructor + +Create the operator via the following factory method + +***slip(model_name, modality)*** + +**Parameters:** + +​ ***model_name:*** *str* + +​ The model name of SLIP. Supported model names: +- slip_vit_small +- slip_vit_base +- slip_vit_large + + +​ ***modality:*** *str* + +​ Which modality(*image* or *text*) is used to generate the embedding. + +
+ + + +## Interface + +An image-text embedding operator takes a [towhee image](link/to/towhee/image/api/doc) or string as input and generate an embedding in ndarray. + + +**Parameters:** + +​ ***data:*** *towhee.types.Image (a sub-class of numpy.ndarray)* or *str* + +​ The data (image or text based on specified modality) to generate embedding. + + + +**Returns:** *numpy.ndarray* + +​ The data embedding extracted by model. + + + + + diff --git a/tabular1.png b/tabular1.png new file mode 100644 index 0000000000000000000000000000000000000000..a7480e57d14f0d4953658ed6b03ad2fb4cd50ce4 GIT binary patch literal 122681 zcmeFZXIxXw7B@-RSe2<8#h=@BMl|y!mC5oxS(WthHv%f3*o=y4va&$yvzp@bE6)(NMjQ zhex=Bhll@^^a60DnZBP8_@Zp5qN008MTJY(#p$Wt^Cx(Cg0a??mb4nz1v{*)EG;{_ zuU#c~@wguv8hPK+x2>^FHFl#yIVUxYiZ>utQB zyd$NZFs$MD(0kEQoFd1QzA^rd$w$hpGrSk~U6l052nnqTVv5Wl_wgQ8;*IgBDXQa- zNhq$rB=x!&noMNHiC0KQ=5pan3EmjNcjmCGihFcirUGPlK1psQ!On# zA>f=8j|iUyj~F<^2M&3B)_OBX$PHFO9YC$yz%(2wOdNdh|pX>fn6d4;~0A3!FMUd1=K3b$IUR 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