Loss and gram matrix

1508.06576/feature_maps.py

@@ -2,6 +2,7 @@ import torch
 from logger import Logger
 LOGGER = Logger().logger()
 LOGGER.info("Started Feature Maps")
+#Author: @meetdoshi
 class FeatureMaps:
     def __init__(self,arch="vgg19"):
         '''

1508.06576/logger.py

-from distutils.log import Log
 import logging
 import os
+#Author: @meetdoshi
 class Logger:
     '''
     Singleton logger class

1508.06576/loss.py

 import numpy as np
+import torch
 from logger import Logger
 LOGGER = Logger().logger()
 
@@ -24,21 +25,36 @@ class Loss:
     def gram_matrix(F):
         '''
         Function to compute the gram matrix of a feature representation at a layer
+        Author: @himalisaini
         '''
+        shape_mat = F.shape
+        num_channels = shape_mat[1]
+        height = shape_mat[2]
+        width = shape_mat[3]
+        return torch.mm(F.view(num_channels,(height*width)),F.view(num_channels,(height*width)).t())
 
     @staticmethod
     def style_loss(F,A):
         '''
         Function to compute style loss between two feature representations at multiple layers
         @params
-
-        '''
+        Author: @soumyagupta
+        '''
+        num_channels = F[1]
+        h = F[2]
+        w = F[3]
+        style_gram_matrix = Loss.gram_matrix(F)
+        target_gram_matrix = Loss.gram_matrix(A)
+        loss_s = np.sum((style_gram_matrix-target_gram_matrix)**2)
+        constant = 1/(4.0*(num_channels**2)*((h*w)**2))
+        return constant*loss_s
 
     @staticmethod
     def total_loss(alpha,beta,cont_fmap_real,cont_fmap_noise,style_fmap_real,style_fmap_noise):
         '''
         Function which computes total loss and returns it
         @params
-
+        Author: @jiteshg
         '''
-    
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+        loss_t = alpha*Loss.content_loss(cont_fmap_real,cont_fmap_noise) + beta*Loss.style_loss(style_fmap_real,style_fmap_noise)
+        return loss_t
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1508.06576/preprocess.py

-from distutils.log import Log
 from logger import Logger
+from torch import transforms
+from PIL import Image
 import numpy as np
 LOGGER = Logger().logger()
-
+#Author: @meetdoshi
 class Preprocessor:
+    @staticmethod
+    def load_image(path):
+        '''
+        Function to load image
+        @params
+        path: os.path
+        '''
+        img = Image.open(path)
+        return img
+
     @staticmethod
     def subtract_mean(img):
         '''
@@ -21,15 +32,22 @@ class Preprocessor:
         @params
         img: 3d numpy array
         '''
+        loader = transforms.Compose([transforms.ToTensor(),transforms.Resize([224,224]),transforms.Normalize(mean=[0.485, 0.456, 0.406],std=[0.229, 0.224, 0.225],),])
+        img = loader(img).unsqueeze(0)
+        return img
 
 
     @staticmethod
-    def process(img):
+    def process(path):
         '''
         Function to preprocess the image
         @params
-        img: 2d numpy a[103.939, 116.779, 123.68]rray
+        path: os.path
         '''
+        img = Preprocessor.load_image(path)
+        img = Preprocessor.reshape_img(img)
+        img = Preprocessor.subtract_mean(img)
+        return img
 
 if __name__=="__main__":
     prec = Preprocessor()

1508.06576/style_transfer.py

@@ -15,10 +15,12 @@ class StyleTransfer:
         pass
 
     @staticmethod
-    def pipepline():
+    def pipeline():
         '''
         Pipeline for style transfer
         @params: None
+        Author: @gaurangathavale
         '''
         
 
+    
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