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-# deepface
+# Face Embeddings using Deepface
+ *Author: Krishna katyal*
+
+
+
+
+## Description
+The pipeline is used to extract the feature vector of detected faces in images. It uses the for face embeddings [`Deepface`](https://github.com/serengil/deepface).
+
+
+
+
+
+## Code Example
+Load an image from path './test_face'.
+
+ *Write the pipeline in simplified style*:
+
+```python
+import towhee
+towhee.glob('./test_face.jpg') \
+ .image_decode.cv2() \
+ .face_embedding.deepface(model_name = 'DeepFace').tolist()
+```
+
+
+
+
+*Write a pipeline with explicit inputs/outputs name specifications:*
+
+
+```python
+import towhee
+
+towhee.glob['path']('./test_face.jpgg') \
+ .image_decode.cv2['path', 'img']() \
+ .face_embedding.deepface['img', 'vec']() \
+ .select['img','vec']() \
+ .show()
+```
+
+
+
+
+
+
+## Factory Constructor
+
+Create the operator via the following factory method
+
+***face_embedding.deepface(model_name = 'which model to use')***
+
+Model options:
+- VGG-Face
+- FaceNet
+- OpenFace
+- DeepFace
+- ArcFace
+- Dlib
+- DeepID
+
+
+
+
+
+
+## Interface
+
+A face embedding operator takes a face image as input. It extracts the embedding in ndarray.
+
+**Parameters:**
+
+ ***img:*** *towhee.types.Image (a sub-class of numpy.ndarray)*
+
+ The input image.
+
+**Returns:** *numpy.ndarray*
+
+ The extracted image embedding.
+
+
+
+
+
+
+
+**Reference**
+
+https://github.com/serengil/deepface
+
+You can refer to [Getting Started with Towhee](https://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).
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+{
+ "systemParams": "darwin-x64-83",
+ "modulesFolders": [],
+ "flags": [],
+ "linkedModules": [],
+ "topLevelPatterns": [],
+ "lockfileEntries": {},
+ "files": [],
+ "artifacts": {}
+}
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+# THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
+# yarn lockfile v1
+
+