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| import google.generativeai as genai | |
| import streamlit as st | |
| import numpy as np | |
| from PIL import Image | |
| #from dotenv import load_dotenv | |
| #load_dotenv() | |
| import json | |
| import os | |
| GOOGLE_API_KEY=os.getenv('GOOGLE_API_KEY') | |
| genai.configure(api_key=GOOGLE_API_KEY) | |
| st.set_page_config(page_title='Description Generator', | |
| page_icon=':milky_way:', | |
| layout='centered', | |
| initial_sidebar_state='collapsed' | |
| ) | |
| st.header('Image Description Generator(Share Image get description)') | |
| uploaded_file = st.file_uploader("Choose a file", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file is not None: | |
| # To read file as bytes: | |
| #bytes_data = uploaded_file.getvalue() | |
| file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8) | |
| st.image(uploaded_file) | |
| #from IPython.display import Image | |
| img = Image.open(uploaded_file) | |
| prompt = """This image contains a sketch. | |
| try to identify and Describe the sketch as thoroughly as possible based on what you | |
| see in the image, making sure to note all of the features. Return output in json format: | |
| {description: description, features: [feature1, feature2, feature3, etc]}""" | |
| submit=st.button('Generate') | |
| if submit: | |
| model = genai.GenerativeModel('gemini-1.5-flash') | |
| response = model.generate_content([prompt, img]) | |
| response=json.loads(response.text) | |
| st.write((response['description'])) | |
| number=1 | |
| for feature in response['features']: | |
| st.write("Feature "+str(number)+" : "+str(feature)) | |
| number+=1 | |