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Update app.py
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app.py
CHANGED
@@ -3,6 +3,7 @@ from PIL import Image
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import google.generativeai as genai
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import io
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import os
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# Configure Google Gemini API (replace with your actual API key)
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GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
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@@ -14,7 +15,6 @@ genai.configure(api_key=GOOGLE_API_KEY)
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# Function to generate the modified image
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def generate_modified_image(uploaded_image, background_description):
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try:
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# Update the model name here
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model = genai.GenerativeModel('gemini-1.5-flash')
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img = Image.open(uploaded_image)
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@@ -24,7 +24,7 @@ def generate_modified_image(uploaded_image, background_description):
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"Here is the image:",
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img, # Pass the PIL Image object directly
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f"Modify the background of this image to: '{background_description}'. Be creative and make the new background look realistic and integrated with the foreground.",
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"Output only the modified image."
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]
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response = model.generate_content(prompt_parts, stream=False)
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@@ -32,20 +32,25 @@ def generate_modified_image(uploaded_image, background_description):
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if response and hasattr(response, 'parts') and len(response.parts) > 0:
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for part in response.parts:
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return None
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else:
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st.error("Failed to
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return None
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except Exception as e:
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st.error(f"An error occurred: {e}")
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return None
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# Streamlit web app
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import google.generativeai as genai
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import io
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import os
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import base64
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# Configure Google Gemini API (replace with your actual API key)
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GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
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# Function to generate the modified image
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def generate_modified_image(uploaded_image, background_description):
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try:
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model = genai.GenerativeModel('gemini-1.5-flash')
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img = Image.open(uploaded_image)
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"Here is the image:",
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img, # Pass the PIL Image object directly
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f"Modify the background of this image to: '{background_description}'. Be creative and make the new background look realistic and integrated with the foreground.",
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"Output only the modified image. Ensure the output is a valid image format (like PNG or JPEG) encoded as bytes."
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]
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response = model.generate_content(prompt_parts, stream=False)
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if response and hasattr(response, 'parts') and len(response.parts) > 0:
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for part in response.parts:
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try:
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# Try to get the image data directly if it's a blob
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if hasattr(part, 'blob'):
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image_bytes = part.blob.data
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return Image.open(io.BytesIO(image_bytes))
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elif hasattr(part, 'text'):
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st.warning(f"Received text response instead of image: {part.text}")
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else:
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st.warning(f"Unexpected part type in response: {part}")
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except Exception as part_err:
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st.error(f"Error processing response part: {part_err}")
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st.error("No valid image data found in the response.")
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return None
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else:
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st.error("Failed to get a valid response from the model.")
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return None
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except Exception as e:
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st.error(f"An error occurred during generation: {e}")
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return None
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# Streamlit web app
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