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51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
from pathlib import Path
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from pydantic import BaseModel
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from typing import List, Optional, Literal
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from ollama import chat
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from rich import print
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# Define the schema for image objects
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class Object(BaseModel):
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name: str
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confidence: float
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attributes: Optional[dict] = None
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class ImageDescription(BaseModel):
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summary: str
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objects: List[Object]
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scene: str
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colors: List[str]
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time_of_day: Literal['Morning', 'Afternoon', 'Evening', 'Night']
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setting: Literal['Indoor', 'Outdoor', 'Unknown']
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text_content: Optional[str] = None
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# Get path from user input
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path = input('Enter the path to your image: ')
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path = Path(path)
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# Verify the file exists
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if not path.exists():
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raise FileNotFoundError(f'Image not found at: {path}')
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# Set up chat as usual
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response = chat(
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model='llama3.2-vision',
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format=ImageDescription.model_json_schema(), # Pass in the schema for the response
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messages=[
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{
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'role': 'user',
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'content': 'Analyze this image and return a detailed JSON description including objects, scene, colors and any text detected. If you cannot determine certain details, leave those fields empty.',
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'images': [path],
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},
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],
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options={'temperature': 0}, # Set temperature to 0 for more deterministic output
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)
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# Convert received content to the schema
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image_analysis = ImageDescription.model_validate_json(response.message.content)
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print(image_analysis)
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