added style projection

requirements.txt

@@ -10,4 +10,7 @@ gradio
 segmentation_models
 opencv-python-headless
 tensorflow-cpu
-tensorflow_hub
+tensorflow_hub
+
+paddlepaddle
+paddlehub

styleTransfer.py

@@ -2,14 +2,16 @@ from PIL import Image
 import numpy as np
 import torch
 import torch.nn as nn
-from PIL import Image
 from torchvision import transforms
 import transformer as transformer
 import StyTR as StyTR
-import numpy as np
 from collections import OrderedDict
-import tensorflow_hub as hub
+import tensorflow_hub as tfhub
 import tensorflow as tf
+import os
+import cv2 
+import paddlehub as phub
+
 
 ############################################# TRANSFORMER ############################################
 
@@ -82,7 +84,7 @@ def StyleTransformer(content_img: Image, style_img: Image):
    
 ############################################## STYLE-GAN #############################################
 
-style_transfer_model = hub.load("https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2")
+style_transfer_model = tfhub.load("https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2")
 
 def StyleGAN(content_image, style_image):
     content_image = tf.convert_to_tensor(content_image, np.float32)[tf.newaxis, ...] / 255.
@@ -91,10 +93,18 @@ def StyleGAN(content_image, style_image):
     stylized_image = output[0]
     return Image.fromarray(np.uint8(stylized_image[0] * 255))
 
-################################################# MAIN ################################################
+########################################### STYLE PROJECTION ##########################################
+
+stylepro_artistic = phub.Module(name="stylepro_artistic")
+
+def styleProjection(content_image,style_image):
+    result = stylepro_artistic.style_transfer(
+    images=[{
+        'content': np.array(content_image.convert('RGB') )[:, :, ::-1],
+        'styles': [np.array(style_image.convert('RGB') )[:, :, ::-1]]
+    }])
+
+    return Image.fromarray(np.uint8(result[0]['data'])[:,:,::-1]).convert('RGB')
+    
 
 
-def create_styledSofa(sofa:Image, style:Image):
-    #styled_sofa = StyleGAN(sofa,style)
-    styled_sofa = StyleTransformer(sofa,style)
-    return styled_sofa