File size: 1,237 Bytes
6544ea3 140c70d 6544ea3 d2127bb 140c70d 6544ea3 d2127bb 6544ea3 d2127bb 6544ea3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | import io
import torch
import requests
from PIL import Image
from transformers import BlipProcessor, BlipForConditionalGeneration
class EndpointHandler:
def __init__(self, model_dir):
self.processor = BlipProcessor.from_pretrained(model_dir)
self.model = BlipForConditionalGeneration.from_pretrained(model_dir)
self.model.eval()
self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
self.model.to(self.device)
def __call__(self, data):
# Unwrap Hugging Face "inputs" key if present
if isinstance(data, dict) and "inputs" in data:
data = data["inputs"]
image_url = data.get("image_url")
if not image_url:
return {"error": "Please provide an 'image_url' in the JSON payload."}
try:
response = requests.get(image_url)
response.raise_for_status()
image = Image.open(io.BytesIO(response.content)).convert("RGB")
except Exception as e:
return {"error": f"Failed to load image: {str(e)}"}
inputs = self.processor(images=image, return_tensors="pt").to(self.device)
with torch.no_grad():
out = self.model.generate(**inputs)
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