| from transformers import ViltProcessor, ViltForQuestionAnswering | |
| import requests | |
| from PIL import Image | |
| def image(url, text): | |
| image = Image.open(requests.get(url, stream=True).raw) | |
| processor = ViltProcessor.from_pretrained("dandelin/vilt-b32-finetuned-vqa") | |
| model = ViltForQuestionAnswering.from_pretrained("dandelin/vilt-b32-finetuned-vqa") | |
| # prepare inputs | |
| encoding = processor(image, text, return_tensors="pt") | |
| # forward pass | |
| outputs = model(**encoding) | |
| logits = outputs.logits | |
| idx = logits.argmax(-1).item() | |
| print("question asked:", text) | |
| print("image link:", url) | |
| print("Predicted answer:", model.config.id2label[idx]) | |
| return "Predicted answer:", model.config.id2label[idx] | |
| # prepare image + question | |