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app.py

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+import streamlit as st
+from super_image import EdsrModel, ImageLoader
+from PIL import Image
+import cv2
+
+st.title('Take your picture to the next level')
+
+
+col1, col2 = st.columns([3, 1])
+preds = None
+
+with col2:
+    choice = st.selectbox('Scale to', [2, 3, 4])
+    model_choice = st.selectbox('Model', ['EDSR', 'PAN', 'CARN'])
+
+with col1:
+    file = st.file_uploader('Post your picture', type=['png', 'jpeg'])
+    if file is not None:
+        image = Image.open(file)
+
+        col1, col2 = st.columns(2)
+        with col1:
+            st.subheader('Input image')
+            st.image(image)
+
+        if model_choice == "EDSR":
+
+            model = EdsrModel.from_pretrained("eugenesiow/edsr-base", scale=int(choice))
+            inputs = ImageLoader.load_image(image)
+            preds = model(inputs)
+
+            ImageLoader.save_image(preds, './scaled_2x.png')
+            img = Image.open('./scaled_2x.png')
+            with col2:
+                st.subheader('New image')
+                st.image(img, caption=f'Upscaled {choice} times image')
+    
+                with open('./scaled_2x.png', 'rb') as f:
+                    st.download_button(label="Download image", data=f, file_name="upscaled.png", mime="image/png")
+            
+        else:
+            st.text('Not supported yet. Comeback soon for fun releases')
+    

requirements.txt

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+super-image
+pillow
+transformers
+datasets