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Singularity666
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68724c0
1
Parent(s):
c844544
Update app.py
Browse files
app.py
CHANGED
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import streamlit as st
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import
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def app():
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uploaded_file = st.file_uploader("Choose an image...", type="png")
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if uploaded_file is not None:
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with open("
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f.write(uploaded_file.
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if __name__ == "__main__":
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import streamlit as st
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import replicate
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import os
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import requests
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from PIL import Image
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from io import BytesIO
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# Set up environment variable for Replicate API Token
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os.environ['REPLICATE_API_TOKEN'] = 'r8_3V5WKOBwbbuL0DQGMliP0972IAVIBo62Lmi8I' # Replace with your actual API token
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def upscale_image(image_path):
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# Open the image file
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with open(image_path, "rb") as img_file:
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# Run the GFPGAN model
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output = replicate.run(
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"tencentarc/gfpgan:9283608cc6b7be6b65a8e44983db012355fde4132009bf99d976b2f0896856a3",
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input={"img": img_file, "version": "v1.4", "scale": 16}
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)
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# The output is a URI of the processed image
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# We will retrieve the image data and save it
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response = requests.get(output)
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img = Image.open(BytesIO(response.content))
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# Save the upscaled image to a BytesIO object
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img_byte_arr = BytesIO()
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img.save(img_byte_arr, format='PNG')
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img_byte_arr = img_byte_arr.getvalue()
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return img, img_byte_arr
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def main():
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st.title("Image Upscaling")
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st.write("Upload an image and it will be upscaled.")
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uploaded_file = st.file_uploader("Choose an image...", type="png")
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if uploaded_file is not None:
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with open("temp_img.png", "wb") as f:
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f.write(uploaded_file.getbuffer())
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st.success("Uploaded image successfully!")
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if st.button("Upscale Image"):
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img, img_bytes = upscale_image("temp_img.png")
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st.image(img, caption='Upscaled Image', use_column_width=True)
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# Add download button
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st.download_button(
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label="Download Upscaled Image",
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data=img_bytes,
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file_name="upscaled_image.png",
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mime="image/png"
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)
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if __name__ == "__main__":
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main()
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