Update

Signed-off-by: shiyu22 <shiyu.chen@zilliz.com>

README.md

@@ -14,9 +14,9 @@ This pipeline is used to **extract the feature vector of the image**. It first n
 
 **Input Arguments:**
 
-- img:
+- img_path:
   - the input image to be encoded
-  - supported types: `str`
+  - supported types: `str` (path of the image)
 
 **Pipeline Output:**
 
@@ -40,11 +40,9 @@ $ pip3 install towhee
 
 ```Python
 >>> from towhee import pipeline
->>> from PIL import Image
 
->>> img = Image.open('path/to/your/image') #for example './test.jpg'
 >>> embedding_pipeline = pipeline('user/repo_name')  #the pipeline repo, such as 'towhee/image-embedding-resnet50'
->>> embedding = embedding_pipeline(img)
+>>> embedding = embedding_pipeline('path/to/your/image')
 ```
 
 ## **How it works**

image_embedding_pipeline_template.yaml

@@ -7,7 +7,7 @@ operators:
         inputs:
             -
                 df: '_start_df'
-                name: 'img'
+                name: 'img_path'
                 col: 0
         outputs:
             -
@@ -23,7 +23,7 @@ operators:
         inputs:
             -
                 df: 'image'
-                name: 'img'
+                name: 'img_path'
                 col: 0
         outputs:
             -
@@ -65,13 +65,13 @@ dataframes:
         name: '_start_df'
         columns:
             -
-                name: 'img'
+                name: 'img_path'
                 vtype: 'str'
     -
         name: 'image'
         columns:
             -
-                name: 'img'
+                name: 'img_path'
                 vtype: 'str'
     -
         name: 'image_preproc'

test_image_embedding_pipeline_yaml.py

@@ -8,7 +8,7 @@ class TestImageEmbeddingPipelineClass(unittest.TestCase):
         self.dimension = DIMENSION  #the dimension of image embedding
         self.repo_name = REPO_NAME
         embedding_pipeline = pipeline(self.repo_name)
-        embedding = embedding_pipeline(self.TEST_IMG)
+        embedding = embedding_pipeline(TEST_IMG)
         assert (1, self.dimension)==op(img_tensor)[0].shape