Prompt engineering tool using BLIP 1/2 + CLIP Interrogate approach.
Project description
pytorch_clip_interrogator: Image-To-Promt.
Install package
pip install pytorch_clip_interrogator
Install the latest version
pip install --upgrade git+https://github.com/bes-dev/pytorch_clip_interrogator.git
Features
- Fully compatible with models from Huggingface.
- Supports BLIP 1/2 model.
- Support batch processing.
Usage
Simple code
import torch
import requests
from PIL import Image
from pytorch_clip_interrogator import PromptEngineer
# build pipeline
pipe = PromptEngineer(
blip_model="Salesforce/blip2-opt-2.7b",
clip_model="openai/clip-vit-base-patch32",
device="cuda",
torch_dtype=torch.float16
)
# load image
img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'
image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
# generate caption
print(pipe(image))
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