shape bug fix.

Signed-off-by: wxywb <xy.wang@zilliz.com>

README.md

@@ -5,23 +5,46 @@
 
 ## Desription
 
-A class of extremely efficient CNN models to extract 68 landmarks from a facial image[1].
+A class of extremely efficient CNN models to extract 68 landmarks from a facial image[MobileFaceNets](https://arxiv.org/pdf/1804.07573.pdf).
 
+## Code Example
+
+extracted facial landmark from './img1.jpg'. 
+
+*Write the pipeline in simplified style*:
+
+```python
+from towhee import dc
+
+dc.glob('./img1.jpg') \
+  .face_landmark_detection.mobilefacenet() \
+  .to_list()
+```
+
+*Write a same pipeline with explicit inputs/outputs name specifications:*
 
 ```python
-from towhee import ops
+from towhee import dc
 
-model = ops.face_landmark_detection.mobilefacenet()
-landmark = model(img)
+dc.glob['path']('./img1.jpg') \
+  .image_decode.cv2['path', 'img']() \
+  .face_landmark_detection.mobilefacenet() \
+  .to_list()
 ```
 
 ## Factory Constructor
 
 Create the operator via the following factory method
 
-***ops.face_landmark_detection.mobilefacenet()***
+***ops.face_landmark_detection.mobilefacenet(pretrained = True)***
+
+**Parameters:**
 
+​  ***pretrained***
 
+​  whether load the pretrained weights..
+
+​  supported types: `bool`, default is True, using pretrained weights
 
 ## Interface
 
@@ -29,13 +52,6 @@ An image embedding operator takes an image as input. it extracts the embedding b
 
 **Args:**
 
-​  ***framework***
-
-​  the framework of the model
-
-​  supported types: `str`, default is 'pytorch'
-
-
 ​  ***pretrained***
 
 ​  whether load the pretrained weights..
@@ -45,7 +61,7 @@ An image embedding operator takes an image as input. it extracts the embedding b
 
 **Parameters:**
 
-​	***image***: *towhee._types.Image*
+​	***image***: *np.ndarray*
 
 ​	The input image.
 
@@ -54,32 +70,3 @@ An image embedding operator takes an image as input. it extracts the embedding b
 
 ​	The extracted facial landmark.
 
-## Code Example
-
-extracted facial landmark from './img1.jpg'. 
-
-*Write the pipeline in simplified style*:
-
-```python
-import towhee.DataCollection as dc
-
-dc.glob('./img1.jpg')
-  .face_landmark_detection.mobilefacenet()
-  .to_list()
-```
-
-*Write a same pipeline with explicit inputs/outputs name specifications:*
-
-```python
-import towhee.DataCollection as dc
-
-dc.glob['path']('./img1.jpg')
-  .image_decode.cv2['path', 'img']()
-  .face_landmark_detection.mobilefacenet()
-  .to_list()
-```
-
-
-## Reference
-
-[1].https://arxiv.org/pdf/1804.07573.pdf

mobilefacenet.py

@@ -22,9 +22,11 @@ import torch
 
 from torchvision import transforms
 
+from towhee import register
 from towhee.operator import NNOperator
 from towhee.types.image_utils import to_pil
 from towhee._types import Image
+from towhee.types import arg, to_image_color
 
 #import mobilefacenet
 
@@ -34,8 +36,8 @@ class Mobilefacenet(NNOperator):
     Mobilefacenet
     """
 
-    def __init__(self, framework: str = 'pytorch', pretrained = True):
-        super().__init__(framework=framework)
+    def __init__(self, pretrained = True):
+        super().__init__()
         sys.path.append(str(Path(__file__).parent))
         from mobilefacenet_impl import MobileFaceNet
         self.model = MobileFaceNet([112, 112], 136)
@@ -47,7 +49,7 @@ class Mobilefacenet(NNOperator):
         
         normalize = transforms.Normalize(
             mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
-        self.tfms = transforms.Compose([transforms.Scale(112),
+        self.tfms = transforms.Compose([transforms.Scale([112,112]),
                                         transforms.ToTensor(),
                                         normalize])