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from typing import Dict, List, Any
from transformers import BlipProcessor, BlipForConditionalGeneration
from PIL import Image
import requests
class EndpointHandler():
def __init__(self, path=""):
self.processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
self.model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
image_url (:obj: `str`): URL of the image to be captioned
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
# get inputs
image_url = data.pop("image_url", None)
# check if image_url exists
if image_url is None:
return [{"error": "image_url not provided"}]
# get image from URL
try:
raw_image = Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
except:
return [{"error": "unable to load image from the provided URL"}]
# unconditional image captioning
inputs = self.processor(raw_image, return_tensors="pt")
# generate captions
out = self.model.generate(**inputs)
# return the generated captions
return [{"caption": self.processor.decode(out[0], skip_special_tokens=True)}]
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