From b3bf21ff6c8513c628a95ddb27684c5ee1ab7556 Mon Sep 17 00:00:00 2001 From: shiyu22 Date: Fri, 24 Dec 2021 16:52:25 +0800 Subject: [PATCH] Update Signed-off-by: shiyu22 --- README.md | 11 ++++++----- readme_res/pipeline.png | Bin 270232 -> 220098 bytes 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 76b518a..510e108 100644 --- a/README.md +++ b/README.md @@ -4,15 +4,15 @@ Authors: derekdqc ## Overview -The pipeline is used to **extract the feature vector of a given image**. It first normalizes the image and then uses Resnet50 model to generate the vector. +The pipeline is used to **extract the feature vector of a given image**. It uses Resnet50 model to generate the vector. ## Interface **Input Arguments:** - img_path: - - the input image to be encoded - - supported types: `str` (path of the image) + - path to the input image + - supported types: `str` **Pipeline Output:** @@ -38,12 +38,13 @@ $ pip3 install towhee >>> from towhee import pipeline >>> embedding_pipeline = pipeline('towhee/image-embedding-resnet50') ->>> embedding = embedding_pipeline('path/to/your/image') +>>> embedding = embedding_pipeline('path/to/your/image') #such as './readme_res/pipeline.png' ``` ## How it works -This pipeline includes two main operators: [transform image](https://hub.towhee.io/towhee/transform-image-operator-template) (implemented as [towhee/transform-image](https://hub.towhee.io/towhee/transform-image)) and [image embedding](https://hub.towhee.io/towhee/image-embedding-operator-template) (implemented as [towhee/resnet-image-embedding](https://hub.towhee.io/towhee/resnet-image-embedding)). The transform image operator will first convert the original image into a normalized format, such as with 512x512 resolutions. Then, the normalized image will be encoded via image embedding operator, and finally we get a feature vector of the given image. +This pipeline includes one operator: [image embedding](https://hub.towhee.io/towhee/image-embedding-operator-template) (implemented as [towhee/resnet-image-embedding](https://hub.towhee.io/towhee/resnet-image-embedding)). The image will be encoded via image embedding operator, then we can get a feature vector of the given image. + > Refer [Towhee architecture](https://github.com/towhee-io/towhee#towhee-architecture) for basic concepts in Towhee: pipeline, operator, dataframe. diff --git a/readme_res/pipeline.png b/readme_res/pipeline.png index 5dbc0d7597856b52b01361d08d56fd613c2f7295..5d6f7625ce088f51019221351f51ea38cfb95c60 100644 GIT binary patch literal 220098 zcmeFYgMVF3)HWP8Y8u-%n#N9JH)`ypv2EKn8aB3V+qP{d-^s1s&-1a8^2o}ly_yPp0*846>FUrtMOjxrCe%Dhc8C_1}T&^uCan&(h@%gEUFpd#QtiP$T4b+Z0m{i2dH6&1aD z&aSe$r{YY@&rVGm0Kw_WWvSH<6p5LX)M)MVl9w~mjBajA*@e1LBI0jCs45(yooSE> z(LT6Zw%Gd9!_I%78InC%pnA8b9%Eiu$U>)PSb!Qnc<5@>)kSCr_jF3KBp~4BQPxg-A_@&PtLGzzB2R}c^wSp z(8Vxcv{mPEZhctV)mSk`y=^w!-kZztUD_Brr*TA1_tb0;A@?NwxlisC%N!h3DeUy~ z>o*y4Tw^RsJcZywzM9O&Z!f<%enCxh9)ea_ffk;o}Qk@soJzabc-M?!a1yF!WmJBmrLUB?Gq z-3rxmzxnL>@1}6}=p26P-5ZvOtdglDqcDA)xto`k!j@!K36@0lM$0aoP;>z-?Hn8Y 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