| import torch
|
| from PIL import Image
|
| import requests
|
| from lavis.models import load_model_and_preprocess
|
|
|
| img_url = 'https://storage.googleapis.com/sfr-vision-language-research/LAVIS/assets/merlion.png'
|
| raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
|
| display(raw_image.resize((596, 437)))
|
|
|
| device = torch.device("cuda") if torch.cuda.is_available() else "cpu"
|
|
|
| model, vis_processors, _ = load_model_and_preprocess(
|
| name="blip2_opt", model_type="caption_coco_opt2.7b", is_eval=True, device=device
|
| )
|
|
|
| image = vis_processors["eval"](raw_image).unsqueeze(0).to(device)
|
|
|
| model.generate({"image": image})
|
|
|
|
|
| model.generate({"image": image}, use_nucleus_sampling=True, num_captions=3)
|
|
|
| model.generate({"image": image, "prompt": "Question: which city is this? Answer:"})
|
|
|
| model.generate({
|
| "image": image,
|
| "prompt": "Question: which city is this? Answer: singapore. Question: why?"}) |
