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ad35ed2 | 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 | from transformers import CLIPModel, CLIPProcessor
from typing import Dict, List, Any
from PIL import Image
from transformers import pipeline
import requests
import torch
class EndpointHandler():
def __init__(self, path=""):
"""
path:
"""
self.device = "cuda" if torch.cuda.is_available() else "cpu"
self.processor = CLIPProcessor.from_pretrained(path)
self.model = CLIPModel.from_pretrained(path).to(self.device)
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
inputs (:obj: `str` | `PIL.Image` | `np.array`)
kwargs
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
result = {}
inputs = data.pop("inputs", data)
image_url = inputs['image_url']
image = Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
processed_image = self.processor(images=image, return_tensors="pt").to(self.device)
output = self.model.get_image_features(processed_image["pixel_values"])[0].tolist()
result["embedding"] = output
return result
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