image_pipeline.py

from transformers import BlipProcessor, BlipForConditionalGeneration
from PIL import Image

from config import HF_IMAGE_MODEL

# Load the Hugging Face processor and model for medical image analysis
processor = BlipProcessor.from_pretrained(HF_IMAGE_MODEL)
model = BlipForConditionalGeneration.from_pretrained(HF_IMAGE_MODEL)

def analyze_medical_image(image_file):
    """
    Process and analyze a medical image to generate diagnostic insights.
    """
    # Open the image file
    image = Image.open(image_file).convert("RGB")
    
    # Preprocess the image and prepare inputs
    inputs = processor(images=image, return_tensors="pt")
    
    # Generate outputs
    outputs = model.generate(**inputs, max_length=256)
    
    # Decode and return the generated text
    result = processor.decode(outputs[0], skip_special_tokens=True)
    return result