Update image_pipeline.py

image_pipeline.py

@@ -1,17 +1,25 @@
-from transformers import AutoProcessor, AutoModel
+from transformers import BlipProcessor, BlipForConditionalGeneration
 from PIL import Image
 
-from config import HF_IMAGE_MODEL, HF_TOKEN
+from config import HF_IMAGE_MODEL
 
-# Load the Hugging Face model for medical image analysis
-model = AutoModel.from_pretrained(HF_IMAGE_MODEL, trust_remote_code=True)
-processor = AutoProcessor.from_pretrained(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)
-    return processor.decode(outputs[0], skip_special_tokens=True)
+    
+    # Decode and return the generated text
+    result = processor.decode(outputs[0], skip_special_tokens=True)
+    return result