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import PIL.Image
import os
import google.generativeai as genai
from prompt import prompt
import google.ai.generativelanguage as glm
import json
# Configure API key for Google Generative AI
os.environ['GOOGLE_API_KEY'] = "AIzaSyDAG_Xl66vh4ceY81UXe3vrdwP6wIAkpBs"
genai.configure(api_key=os.environ['GOOGLE_API_KEY'])
def get_image_data(image):
# Initialize the vision model
try:
vision_model = genai.GenerativeModel('gemini-1.5-flash')
except Exception as e:
print(f"Error initializing vision model: {e}")
exit()
# Generate content using the vision model
try:
response = vision_model.generate_content([prompt, image],
generation_config=genai.types.GenerationConfig(
candidate_count=1,
stop_sequences=['.'],
max_output_tokens=200,
top_p=0.7,
top_k=4,
temperature=0.7,
)
)
# Parse the response text to extract category and type
response_text = response.text.strip().lower()
category = response_text.split('category:')[1].split('\n')[0].strip() if 'category:' in response_text else 'Unknown'
type_name = response_text.split('type:')[1].strip() if 'type:' in response_text else 'Unknown'
# Create the result dictionary
result = {
"Category": category.capitalize(),
"Type": type_name.capitalize()
}
# Print the result dictionary
return(result)
except Exception as e:
print(f"Error generating content: {e}")
# # Load the image
# image_path = 'image.png'
# try:
# image = PIL.Image.open(image_path)
# except Exception as e:
# print(f"Error loading image: {e}")
# exit()
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