app

app.py

@@ -0,0 +1,50 @@
+import numpy as np
+import gradio as gr
+from segmentation import get_mask,replace_sofa
+from styleTransfer import resize_sofa,resize_style,create_styledSofa
+from PIL import Image
+
+def style_sofa(input_img: np.ndarray, style_img: np.ndarray):
+    """
+    Styles (all) the sofas in the image to the given style.
+    This function uses a transformer to combine the image with the desired style according 
+    to a generated mask of the sofas in the image.
+    Input:
+        input_img = image containing a sofa
+        style_img = image containing a style
+    Return:
+        new_sofa  = image containing the styled sofa
+    """
+    
+    # preprocess input images to be (640,640) squares to fit requirements of the segmentation model
+    resized_img = resize_sofa(input_img)
+    resized_style = resize_style(style_img)
+    # generate mask for image
+    mask = get_mask(resized_img)
+    styled_sofa = create_styledSofa(resized_img,resized_style)
+    new_sofa = replace_sofa(resized_img,mask,styled_sofa)
+    return new_sofa
+
+image = gr.inputs.Image()
+style = gr.inputs.Image()
+
+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'],
+    ],
+    title="Style your sofa",
+    description="🛋 Customize your sofa to your wildest dreams! 🛋",
+)
+
+if __name__ == "__main__":
+    demo.launch(share=True)
+
+
+#https://github.com/dhawan98/Post-Processing-of-Image-Segmentation-using-CRF