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| def model(): | |
| # Importing All the modules | |
| import streamlit as st | |
| import os | |
| from PIL import Image | |
| import google.generativeai as genai | |
| from dotenv import load_dotenv | |
| import faiss # Assuming faiss library is used for the index | |
| # Load all environment Variables | |
| load_dotenv() | |
| # Configuring the api key | |
| genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) | |
| # Function to load Gemini Vison Pro Vision Model and Get response | |
| def get_gemini_response(image, prompt): | |
| # Loading the desired Model | |
| model = genai.GenerativeModel("gemini-pro-vision") | |
| response = model.generate_content([image[0], prompt]) | |
| return response.text | |
| # Function to extract data from Image Uploaded | |
| def input_image_setup(uploaded_file): | |
| # Check if a file has been uploaded | |
| if uploaded_file is not None: | |
| # Read the file into bytes | |
| bytes_data = uploaded_file.getvalue() | |
| image_parts = [ | |
| { | |
| "mime_type": uploaded_file.type, # Get the mime type of the uploaded file | |
| "data": bytes_data | |
| } | |
| ] | |
| return image_parts | |
| else: | |
| raise FileNotFoundError("No file uploaded") | |
| # Initializing our Streamlit Prompt | |
| st.title("Pet Image Analyzer") | |
| st.write( | |
| """ | |
| Welcome to the Pet Image Analyzer! This tool uses advanced AI technology to analyze images of your pets | |
| and provide insights into their breed, potential health issues, and more. Please upload an image of your pet | |
| to get started. | |
| """ | |
| ) | |
| # File uploader for image input | |
| uploaded_file = st.file_uploader("Choose a pet image...", type=["jpg", "jpeg", "png", "webp"]) | |
| image = None | |
| if uploaded_file is not None: | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption="Uploaded Image.", use_column_width=True) | |
| # Defining a System Prompt (pre-defined) | |
| input_prompt = f"""Image: (content of the uploaded image) | |
| Text: Analyze the image and provide the following information: | |
| * Breed: Identify the breed of the animal in the image (if possible). | |
| * Disease Detection: If the image shows a diseased area, identify the specific disease (if possible). | |
| * Severity: If a disease is detected, assess the severity of the disease. | |
| * Symptoms: Describe the common symptoms associated with the detected disease. | |
| * Precautions: Recommend preventative measures to avoid the disease. | |
| Give response with headings, | |
| Inform the user if the image is not related to pet care. | |
| """ | |
| submit = st.button("Analyze Image") | |
| Disclaimer = ( | |
| "**Disclaimer:** This application uses image analysis to provide potential information about your pet's health. " | |
| "The results are for informational purposes only and should not be considered a replacement for professional veterinary diagnosis. " | |
| "For any concerns about your pet's health, please consult a licensed veterinarian. They can conduct a thorough examination and provide personalized recommendations for your pet's well-being." | |
| ) | |
| if submit: | |
| if image: | |
| with st.spinner("Analyzing Image..."): | |
| image_data = input_image_setup(uploaded_file) | |
| response = get_gemini_response(image_data, input_prompt) | |
| st.subheader("Analysis Result:") | |
| st.write(response) | |
| st.warning(Disclaimer) | |
| st.balloons() | |
| else: | |
| st.error("Please upload an image to proceed.") | |
| else: | |
| st.info("Upload an image of your pet to get started!") | |
| st.write( | |
| """ | |
| To analyze your pet's image, click on the 'Choose a pet image...' button above and select an image file from your device. | |
| Once the image is uploaded, click on 'Analyze Image' to receive detailed information about your pet. | |
| """ | |
| ) | |
| # Example usage if running as a script | |
| if __name__ == "__main__": | |
| model() | |