Add docstring for some rmn utils

README.md

@@ -1,6 +1,6 @@
 # Facial Expression Recognition using Residual Masking Network, in PyTorch
 
-[![pypi package](https://img.shields.io/badge/version-v3.0.1-blue)](https://pypi.org/project/rmn)
+[![pypi package](https://img.shields.io/badge/version-v3.0.2-blue)](https://pypi.org/project/rmn)
 [![circleci](https://circleci.com/gh/phamquiluan/ResidualMaskingNetwork.svg?style=shield&circle-token=3ca7f15b6bd362b625bec536d57c45fe5ef6f2c9)](https://app.circleci.com/pipelines/github/phamquiluan/ResidualMaskingNetwork)
 [![style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/phamquiluan/residualmaskingnetwork)
 [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/challenges-in-representation-learning-a/facial-expression-recognition-on-fer2013)](https://paperswithcode.com/sota/facial-expression-recognition-on-fer2013?p=challenges-in-representation-learning-a)

rmn/__init__.py

@@ -148,6 +148,23 @@ def __init__(self, face_detector=True):
 
     @torch.no_grad()
     def detect_emotion_for_single_face_image(self, face_image):
+        """
+        Params:
+        -----------
+        face_image : np.ndarray
+            a cropped face image
+
+        Return:
+        -----------
+        emo_label : str
+            dominant emotion label
+
+        emo_proba : float 
+            dominant emotion proba
+
+        proba_list : list
+            all emotion label and their proba
+        """
         assert isinstance(face_image, np.ndarray)
         face_image = ensure_color(face_image)
         face_image = cv2.resize(face_image, image_size)
@@ -204,6 +221,17 @@ def video_demo(self):
 
     @staticmethod
     def draw(frame, results):
+        """
+        Params:
+        ---------
+        frame : np.ndarray
+
+        results : list of dict.keys('xmin', 'xmax', 'ymin', 'ymax', 'emo_label', 'emo_proba')
+
+        Returns:
+        ---------
+        frame : np.ndarray
+        """
         for r in results:
             xmin = r["xmin"]
             xmax = r["xmax"]