fix error still...

app.py

@@ -102,21 +102,25 @@ def style_sofa(input_img: np.ndarray, style_img: np.ndarray):
 image = gr.inputs.Image()
 style = gr.inputs.Image()
 
+# Examples
+example1 = ['sofa_example1.jpg','style_example1.jpg'],
+example2 = ['sofa_example1.jpg','style_example2.jpg'],
+example3 = ['sofa_example1.jpg','style_example3.jpg'],
+example4 = ['sofa_example1.jpg','style_example4.jpg'],
+example5 = ['sofa_example1.jpg','style_example5.jpg'],
+
 demo = gr.Interface(
     style_sofa,
-    [image,style],
-    'image',
-    examples=[
-        ['sofa_example1.jpg','style_example1.jpg'],
-        ['sofa_example1.jpg','style_example2.jpg'],
-        ['sofa_example1.jpg','style_example3.jpg'],
-        ['sofa_example1.jpg','style_example4.jpg'],
-        ['sofa_example1.jpg','style_example5.jpg'],
-    ],
+    inputs = [image,style],
+    outputs = 'image',
+    examples=[example1,example2,example3,example4,example5],
     title="🛋 Style your sofa 🛋 ",
     description="Customize your sofa to your wildest dreams!\
                 \nProvide a picture of your sofa and a desired pattern\
                  or choose one of the examples below",
+    # article="**References**\n\n"
+    # "<a href='https://www.tensorflow.org/hub/tutorials/tf2_arbitrary_image_stylization' target='_blank'>1. Tutorial to implement Fast Neural Style Transfer using the pretrained model from TensorFlow Hub</a>  \n"
+    # "<a href='https://huggingface.co/spaces/luca-martial/neural-style-transfer' target='_blank'>2. The idea to build a neural style transfer application was inspired from this Hugging Face Space </a>"
 )
 
 if __name__ == "__main__":

requirements.txt

@@ -9,4 +9,5 @@ gradio
 
 segmentation_models
 opencv-python-headless
-tensorflow-cpu
+tensorflow-cpu
+tensorflow_hub

styleTransfer.py

@@ -8,7 +8,13 @@ import transformer as transformer
 import StyTR as StyTR
 import numpy as np
 from collections import OrderedDict
+import tensorflow_hub as hub
+import tensorflow as tf
 
+style_transfer_model = hub.load("https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2")
+
+
+############################################# TRANSFORMER ############################################
 def test_transform(size, crop):
     transform_list = []
    
@@ -84,11 +90,8 @@ def StyleTransformer(content_img: Image, style_img: Image,
     network.eval()
     network.to(device)
 
-
-
     content_tf = test_transform(content_size, crop)
     style_tf = test_transform(style_size, crop)
-
     
     content_tf1 = content_transform()       
     content = content_tf(content_img.convert("RGB"))
@@ -104,9 +107,19 @@ def StyleTransformer(content_img: Image, style_img: Image,
     with torch.no_grad():
         output= network(content,style)     
     output = output[0].cpu()
-    output = transforms.ToPILImage(output)
+    torch2PIL = transforms.ToPILImage()
+    output = torch2PIL(output)
     return output
    
+############################################## STYLE-GAN #############################################
+
+def perform_style_transfer(content_image, style_image):
+    content_image = tf.convert_to_tensor(content_image, np.float32)[tf.newaxis, ...] / 255.
+    style_image = tf.convert_to_tensor(style_image, np.float32)[tf.newaxis, ...] / 255.
+    output = style_transfer_model(content_image, style_image)
+    stylized_image = output[0]
+    return Image.fromarray(np.uint8(stylized_image[0] * 255))
+
 def create_styledSofa(sofa:Image, style:Image):
     styled_sofa = StyleTransformer(sofa,style)
     return styled_sofa