Update app.py

app.py

@@ -1,73 +1,25 @@
-import streamlit as st
-import replicate
-import os
-import requests
-from PIL import Image
-from io import BytesIO
-
-# Set up environment variables for Replicate and Stability AI API Tokens
-os.environ['REPLICATE_API_TOKEN'] = 'r8_3V5WKOBwbbuL0DQGMliP0972IAVIBo62Lmi8I'  # Replace with your actual Replicate API token
-os.environ['STABILITY_KEY'] = 'sk-GBmsWR78MmCSAWGkkC1CFgWgE6GPgV00pNLJlxlyZWyT3QQO'  # Replace with your actual Stability AI API key
-
-def upscale_image(image_path):
-    # Open the image file
-    with open(image_path, "rb") as img_file:
-        # Upscale the image using Stability AI's API and Stable Diffusion 4x Upscaler
-        stability_api_url = "https://api.stability.ai/v1/image-upscaling"
-        headers = {
-            'Authorization': f'Bearer {os.environ["STABILITY_KEY"]}',
-        }
-        files = {
-            'image': img_file,
-            'upscaler': 'stable-diffusion-x4-latent-upscaler',
-        }
-        response = requests.post(stability_api_url, headers=headers, files=files)
+# app.py
 
-        # Retrieve the upscaled image from the response
-        img = Image.open(BytesIO(response.content))
-        img.save("upscaled.png")  # Save the upscaled image
-        return img
-
-def convert_to_webp(img):
-    # Convert the image to WebP format
-    img_webp = img.convert("RGBA").save("upscaled.webp", format="WEBP")
-    return img_webp
-
-def convert_to_jpg(img):
-    # Convert the image to JPEG format with quality 95
-    img_jpg = img.convert("RGB").save("upscaled.jpg", format="JPEG", quality=95)
-    return img_jpg
+import streamlit as st
+from main import generate_image_from_text, upscale_image_stable_diffusion, further_upscale_image
 
 def main():
-    st.title("Image Upscaling")
-    st.write("Upload an image and enter a prompt to generate, upscale, and convert the image.")
-
-    uploaded_file = st.file_uploader("Choose an image...", type="png")
-    prompt = st.text_input("Enter a prompt for image generation")
-
-    if uploaded_file is not None and prompt:
-        with open("temp_img.png", "wb") as f:
-            f.write(uploaded_file.getbuffer())
-        st.success("Uploaded image successfully!")
-        if st.button("Generate, Upscale, and Convert Image"):
-            img = upscale_image("temp_img.png")
-            st.image(img, caption='Generated and Upscaled Image', use_column_width=True)
-
-            # Convert the upscaled image to WebP and JPEG formats
-            img_webp = convert_to_webp(img)
-            img_jpg = convert_to_jpg(img)
-
-            # Add download buttons for the converted images
-            st.markdown(get_binary_file_downloader_html("upscaled.webp", "Download WebP", "webp"), unsafe_allow_html=True)
-            st.markdown(get_binary_file_downloader_html("upscaled.jpg", "Download JPEG", "jpg"))
-
-# Helper function to create download link for binary files
-def get_binary_file_downloader_html(file_path, button_text, file_format):
-    with open(file_path, "rb") as f:
-        file_data = f.read()
-    base64_file = base64.b64encode(file_data).decode("utf-8")
-    download_link = f'<a href="data:image/{file_format};base64,{base64_file}" download="{file_path}">{button_text}</a>'
-    return download_link
+    st.title("Image Generation and Upscaling")
+    st.write("Enter a text prompt and an image will be generated and upscaled.")
+
+    prompt = st.text_input("Enter a textual prompt to generate an image...")
+    
+    if prompt:
+        st.success("Generating image from text prompt...")
+        image_bytes = generate_image_from_text(prompt)
+        
+        st.success("Upscaling image with stable-diffusion-x4-latent-upscaler...")
+        upscaled_image_bytes = upscale_image_stable_diffusion(image_bytes)
+        
+        st.success("Further upscaling image with GFPGAN...")
+        img = further_upscale_image(upscaled_image_bytes)
+        
+        st.image(img, caption='Upscaled Image', use_column_width=True)
 
 if __name__ == "__main__":
     main()