[DOC] Refine Readme

Signed-off-by: LocoRichard <lichen.wang@zilliz.com>

README.md

@@ -10,7 +10,7 @@
 
 ## Description
 
-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).
+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 repository is an adaptation from [biubug6/Pytorch_Retinaface](https://github.com/biubug6/Pytorch_Retinaface).
 
 
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@@ -18,7 +18,7 @@ This operator detects faces in the images by using [RetinaFace](https://arxiv.or
 
 ## Code Example
 
-Load an image from path './turing.png' and use the pretrained RetinaFace model to generate face bounding boxes and confidence scores. 
+Load an image from path './turing.png' and use the pre-trained RetinaFace model to generate face bounding boxes and confidence scores. 
 
  *Write the pipeline in simplified style:*
 
@@ -55,7 +55,7 @@ towhee.glob['path']('turing.png') \
 
 ## Factory Constructor
 
-Create the operator via the following factory method.
+Create the operator via the following factory method:
 
 ***face_detection.retinaface()***
 
@@ -66,13 +66,13 @@ Create the operator via the following factory method.
 
 ## 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 in ndarray.
 
 **Parameters:**
 
 ​	***img:*** *towhee.types.Image (a sub-class of numpy.ndarray)* 
 
-​	the image to detect faces.
+​	the image to detect faces from.
 
 ​	supported types: numpy.ndarray
 
@@ -80,9 +80,9 @@ A face detection operator takes an image as input. It generates the bounding box
 
 *List[(int, int, int, int)]*
 
-​	The detected face bounding boxes.
+​	The position of the bounding boxes for the faces detected.
 
 *List[float]*
 
-​	The detected face bounding boxes confident scores.
+​	The confidence scores for the face detected in the bounding boxes.