From c8e40df76169421873ed4fa13be644b171d1cdd9 Mon Sep 17 00:00:00 2001 From: wxywb Date: Wed, 6 Apr 2022 16:07:37 +0800 Subject: [PATCH] fix display issue. Signed-off-by: wxywb --- README.md | 18 +++++++++--------- result1.png | Bin 14047 -> 15629 bytes result2.png | Bin 119295 -> 126300 bytes retinaface.py | 11 +++++++---- 4 files changed, 16 insertions(+), 13 deletions(-) diff --git a/README.md b/README.md index 5876f78..3adedf6 100644 --- a/README.md +++ b/README.md @@ -6,12 +6,11 @@ ## Desription -This operator detects faces in the images by using [RetinaFace](https://arxiv.org/abs/1905.00641) Detector. It will return the bounding box positions and the confidence scores of detected faces. This repo is a adapataion from [repo](https://github.com/biubug6/Pytorch_Retinaface). +This operator detects faces in the images by using [RetinaFace](https://arxiv.org/abs/1905.00641) Detector. It will return the bounding box positions and the confidence scores of detected faces. This repo is an adaptaion from [biubug6/Pytorch_Retinaface](https://github.com/biubug6/Pytorch_Retinaface). ## Code Example -Load an image from path './dog.jpg' -and use the pretrained RetinaFace to generate face bounding boxes. +Load an image from path './turing.png' and use the pretrained RetinaFace model to generate face bounding boxes and confidence scores. *Write the pipeline in simplified style*: @@ -34,7 +33,8 @@ import towhee towhee.glob['path']('turing.png') \ .image_decode.cv2['path', 'img']() \ .face_detection.retinaface['img', ('bbox','score')]() \ - .select('img', 'bbox', 'score').show() + .select('img', 'bbox', 'score') \ + .show() ``` result2 @@ -43,15 +43,15 @@ towhee.glob['path']('turing.png') \ Create the operator via the following factory method. -***ops.face_detection.retinaface()*** +***face_detection.retinaface()*** ## Interface -A face detection operator takes an image as input. it generates the bounding box positions and confidence scores back to ndarray. +A face detection operator takes an image as input. It generates the bounding box positions and confidence scores back to ndarray. **Parameters:** -​ ***image***: *numpy.ndarray.* +​ ***img***: *numpy.ndarray.* ​ the image to detect faces. @@ -59,11 +59,11 @@ A face detection operator takes an image as input. it generates the bounding box **Returns:** -*numpy.ndarray* +*List[(int, int, int, int)]* ​ The detected face bounding boxes. -*numpy.ndarray* +*List[float]* ​ The detected face bounding boxes confident scores. diff --git a/result1.png b/result1.png index f9e17d7c07dbb6cc397470b21ff7d5e6824c328e..e29b9f8dfd301ec3afa4dc73ab111daf32afcbde 100644 GIT binary patch literal 15629 zcmeIZWmp{Fwmt}fKnNO0aEAa1!QI`0#UQvfO=zHT8gC$2a0u=pSnyztLvRlk972G` zy>Xx7ch0@{%$?`S%(waSucxZ3x~lfBEpIJ(*Q$_L8cO&NDIcPtq2a42%fCTGyN?8p zWglPxzk&)A;%I2-vJg4BS1NLH^sgN4EFd;uG&HstkckPg@(Z>eQ&SU@oA)VN869CADusXzN94?82lk8`h)SV4K4e1YmK$Ei?qEinR&t%Y-?uxHCI?a zi-6s)z0BsvZzUf7d8xvofi>#mEBvhP%eMeOKOXcRZBDLdXyy98HZhD}vVFHH=wYG( 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