diff --git a/README.md b/README.md
index 55a57e3..ef1d02f 100644
--- a/README.md
+++ b/README.md
@@ -4,34 +4,34 @@ Authors: Kyle, shiyu22
 
 ## Overview
 
-This pipeline is used to **extract the feature vector of the image**, first to normalize the image, and then to use the resnet50 model to generate the vector.
+This pipeline is used to **extract the feature vector of the image**. First step is to normalize the image, and then use resnet50 model to generate the vector.
 
-In fact, the pipeline runs by parsing [the yaml file](./image_embedding_resnet50.yaml), which declares some functions we call **Operator**, and the **DataFrame** required by each Operator. Next will introduce the interface, how to use it and how it works, have fun with it!
+The pipeline parses [the yaml file](./image_embedding_resnet50.yaml), which declares some components we call **Operator** and **DataFrame**. Next, we will introduce the interface, show how to use it and how it works, have fun with it!
 
 ## Interface
 
-`towhee.pipeline(task: str, fmc: FileManagerConfig = FileManagerConfig(), branch: str = 'main', force_download: bool = False)`  [source](https://github.com/towhee-io/towhee/blob/main/towhee/__init__.py)
+`towhee.pipeline(task: str, fmc: FileManagerConfig = FileManagerConfig(), branch: str = 'main', force_download: bool = False)`  [\[source\]](https://github.com/towhee-io/towhee/blob/main/towhee/__init__.py)
 
-**param:**
+**params:**
 
-- **task**(str), task name or pipeline repo name.
-- **fmc**(FileManagerConfig), optional file manager config for the local instance, default is FileManagerConfig().
-- **branch**(str), which branch to use for operators/pipelines on hub, defaults to 'main'.
-- **force_download**(bool), whether to redownload pipeline and operators, default is False.
+- **task**(str): task name or pipeline repo name.
+- **fmc**(FileManagerConfig): optional, file manager config for the local instance, default is a default FileManagerConfig obejct.
+- **branch**(str): optional, which branch to use for operators/pipelines on hub, defaults to 'main'.
+- **force_download**(bool): optional, whether to redownload pipeline and operators, default is False.
 
 **return:**
 
-- **_PipelineWrapper**, which is a wrapper class around `Pipeline`.
+- **_PipelineWrapper**, an instance of the wrapper class around `Pipeline`.
 
-When we declare a pipeline object with a specific task, such as `towhee/image-embedding-resnet50` in this repo, it will run according to the Yaml file, and the input and output are as follows:
+When we declare a pipeline object with a specific task, such as `towhee/image-embedding-resnet50` in this repo, it will run according to the Yaml file, and the input and output are:
 
 **inputs:**
 
-- **img_tensor**(PIL.Image), image to be embedded.
+- **img_tensor**(PIL.Image), the image to be encoded.
 
 **outputs:**
 
-- **cnn**(numpy.ndarray), the embedding of image.
+- **cnn**(numpy.ndarray), the embedding of the image.
 
 ## How to use
 
@@ -41,7 +41,7 @@ When we declare a pipeline object with a specific task, such as `towhee/image-em
 $ pip3 install towhee
 ```
 
-> You can refer to [Getting Started with Towhee](towhee.io) for more details. If you have questions, you can [submit an issue to the towhee repository](https://github.com/towhee-io/towhee/issues).
+> You can refer to [Getting Started with Towhee](towhee.io) for more details. If you have any questions, you can [submit an issue to the towhee repository](https://github.com/towhee-io/towhee/issues).
 
 2. Run it with Towhee
 
@@ -49,7 +49,7 @@ $ pip3 install towhee
 >>> from towhee import pipeline
 >>> from PIL import Image
 
->>> img = Image.open('./test_data/test.jpg')
+>>> img = Image.open('path/to/your/image')
 >>> embedding_pipeline = pipeline('towhee/image-embedding-resnet50')
 >>> embedding = embedding_pipeline(img)
 ```
@@ -62,7 +62,7 @@ First of all, you need to learn the pipeline and operator in Towhee architecture
 
 - **Operator**: An `Operator` is a single node within a pipeline. It contains files (e.g. code, configs, models, etc...) and works for reusable operations (e.g., preprocessing an image, inference with a pretrained model).
 
-This pipeline includes four functions: `_start_op`, `towhee/transform-image`, `towhee/resnet50-image-embedding` and` _end_op`. It is necessary to ensure that the input and output of the four Operators correspond to each other, and the input and output data types can be defined by DataFrame.
+This pipeline includes four functions: `_start_op`, `towhee/transform-image`, `towhee/resnet50-image-embedding` and ` _end_op`. It is necessary to ensure that the input and output of the four Operators correspond to each other, and the input and output data types can be defined by DataFrame.
 
 ![img](./pic/pipeline.png)