implement

face_sdk/core/image_cropper/arcface_cropper/FaceRecImageCropper.py

@@ -99,7 +99,7 @@ def norm_crop(img, landmark, image_size=112, mode='arcface'):
 
 # my class warpper
 class FaceRecImageCropper(BaseImageCropper):
-    """Implimentation of image cropper
+    """Implementation of image cropper
 
     Attributes:
         image: the input image.

face_sdk/core/model_handler/face_alignment/FaceAlignModelHandler.py

@@ -17,7 +17,7 @@
 from torchvision import transforms
 
 class FaceAlignModelHandler(BaseModelHandler):
-    """Implimentation of face landmark model handler
+    """Implementation of face landmark model handler
 
     Attributes:
         model: the face landmark model.

face_sdk/core/model_handler/face_detection/FaceDetModelHandler.py

@@ -19,7 +19,7 @@
 
 
 class FaceDetModelHandler(BaseModelHandler):
-    """Implimentation of face detection model handler
+    """Implementation of face detection model handler
 
     Attributes:
         model: the face detection model.

face_sdk/core/model_handler/face_recognition/FaceRecModelHandler.py

@@ -14,7 +14,7 @@
 from utils.BuzException import *
 
 class FaceRecModelHandler(BaseModelHandler):
-    """Implimentation of face recognition model handler
+    """Implementation of face recognition model handler
 
     Attributes:
         model: the face recognition model.

head/AM_Softmax.py

@@ -9,7 +9,7 @@
 from torch.nn import Module, Parameter
 
 class AM_Softmax(Module):
-    """Implimentation for "Additive Margin Softmax for Face Verification"
+    """Implementation for "Additive Margin Softmax for Face Verification"
     """
     def __init__(self, feat_dim, num_class, margin=0.35, scale=32):
         super(AM_Softmax, self).__init__()

head/AdaCos.py

@@ -14,7 +14,7 @@
 import math
 
 class AdaCos(nn.Module):
-    """Implimentation for "Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations".
+    """Implementation for "Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations".
     """
     def __init__(self, feat_dim, num_classes):
         super(AdaCos, self).__init__()

head/AdaM_Softmax.py

@@ -8,7 +8,7 @@
 from torch.nn import Module, Parameter
 
 class Adam_Softmax(Module):
-    """Implimentation for "AdaptiveFace: Adaptive Margin and Sampling for Face Recognition".
+    """Implementation for "AdaptiveFace: Adaptive Margin and Sampling for Face Recognition".
     """
     def __init__(self, feat_dim, num_class, scale=30.0, lamda=70.0):
         super(Adam_Softmax, self).__init__()

head/ArcFace.py

@@ -10,7 +10,7 @@
 from torch.nn import Module, Parameter
 
 class ArcFace(Module):
-    """Implimentation for "ArcFace: Additive Angular Margin Loss for Deep Face Recognition"
+    """Implementation for "ArcFace: Additive Angular Margin Loss for Deep Face Recognition"
     """
     def __init__(self, feat_dim, num_class, margin_arc=0.35, margin_am=0.0, scale=32):
         super(ArcFace, self).__init__()

head/CircleLoss.py

@@ -9,8 +9,8 @@
 from torch.nn import Module, Parameter
 
 class CircleLoss(Module):
-    """Implimentation for "Circle Loss: A Unified Perspective of Pair Similarity Optimization"
-    Note: this is the classification based implimentation of circle loss.
+    """Implementation for "Circle Loss: A Unified Perspective of Pair Similarity Optimization"
+    Note: this is the classification based implementation of circle loss.
     """
     def __init__(self, feat_dim, num_class, margin=0.25, gamma=256):
         super(CircleLoss, self).__init__()

head/CurricularFace.py

@@ -14,7 +14,7 @@
 import math
 
 class CurricularFace(nn.Module):
-    """Implimentation for "CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition".
+    """Implementation for "CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition".
     """
     def __init__(self, feat_dim, num_class, m = 0.5, s = 64.):
         super(CurricularFace, self).__init__()

head/MV_Softmax.py

@@ -13,7 +13,7 @@
 from torch.nn import Module, Parameter
 
 class MV_Softmax(Module):
-    """Implimentation for "Mis-classified Vector Guided Softmax Loss for Face Recognition"
+    """Implementation for "Mis-classified Vector Guided Softmax Loss for Face Recognition"
     """
     def __init__(self, feat_dim, num_class, is_am, margin=0.35, mv_weight=1.12, scale=32):
         super(MV_Softmax, self).__init__()

head/NPCFace.py

@@ -10,7 +10,7 @@
 from torch.nn import Module, Parameter
 
 class NPCFace(Module):
-    """Implimentation for "NPCFace: A Negative-Positive Cooperation
+    """Implementation for "NPCFace: A Negative-Positive Cooperation
        Supervision for Training Large-scale Face Recognition"
     """
     def __init__(self, feat_dim=512, num_class=86876, margin=0.5, scale=64):

head/SST_Prototype.py

@@ -11,7 +11,7 @@
 import torch.nn.functional as F
 
 class SST_Prototype(Module):
-    """Implimentation for "Semi-Siamese Training for Shallow Face Learning".
+    """Implementation for "Semi-Siamese Training for Shallow Face Learning".
     """
     def __init__(self, feat_dim=512, queue_size=16384, scale=30.0, loss_type='softmax', margin=0.0):
         super(SST_Prototype, self).__init__()

test_protocol/lfw/lfw_evaluator.py

@@ -9,7 +9,7 @@
 import numpy as np
 
 class LFWEvaluator(object):
-    """Implimentation of LFW test protocal.
+    """Implementation of LFW test protocal.
     
     Attributes:
         data_loader(object): a test data loader.

test_protocol/megaface/megaface_evaluator.py

@@ -159,8 +159,8 @@ def get_rankN_accuracy(self, cur_rank):
 
 class CommonMegaFaceEvaluator(MegaFaceEvaluator):
     """The common MegaFace test protocal.
-    Python implimentation of megaface test protocal, 
-    the same as the official implimentation by .bin.
+    Python implementation of megaface test protocal, 
+    the same as the official implementation by .bin.
 
     Attributes:
         facescrub_feature_dir(str): inherit from the parent class.