Update image_pipeline.py

image_pipeline.py

@@ -1,16 +1,17 @@
-from transformers import AutoProcessor, AutoModelForVision2Seq
+from huggingface_hub import InferenceApi
 from PIL import Image
-from config import HF_IMAGE_MODEL
+import base64
+from config import HF_IMAGE_MODEL, HF_TOKEN
 
-# Load Hugging Face image model and processor
-processor = AutoProcessor.from_pretrained(HF_IMAGE_MODEL)
-model = AutoModelForVision2Seq.from_pretrained(HF_IMAGE_MODEL)
+# Initialize Hugging Face Inference API
+inference = InferenceApi(repo_id=HF_IMAGE_MODEL, token=HF_TOKEN)
 
 def analyze_medical_image(image_file):
     """
-    Process and analyze a medical image to generate diagnostic insights.
+    Analyze a medical image using the Hugging Face Inference API.
     """
-    image = Image.open(image_file).convert("RGB")
-    inputs = processor(images=image, return_tensors="pt").to(model.device)
-    outputs = model.generate(**inputs, max_length=256)
-    return processor.batch_decode(outputs, skip_special_tokens=True)[0]
+    with open(image_file, "rb") as img:
+        base64_image = base64.b64encode(img.read()).decode("utf-8")
+
+    response = inference(inputs={"image": base64_image})
+    return response.get("generated_text", "No insights generated.")