Skip to main content

Prompt engineering tool using BLIP 1/2 + CLIP Interrogate approach.

Project description

pytorch_clip_interrogator: Image-To-Promt.

Downloads Downloads Downloads

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))

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

File details

Details for the file pytorch_clip_interrogator-2023.2.19.5-py3-none-any.whl.

File metadata

File hashes

Hashes for pytorch_clip_interrogator-2023.2.19.5-py3-none-any.whl
Algorithm Hash digest
SHA256 c6f2d40ad2b8e15b3f90b1644bd85d5febd18c59220d99a3a12a703986014e56
MD5 887cbcacfb270b217765021856d1f9a8
BLAKE2b-256 1e6ed5b38c51a76bd4ca08f0e7419519ac67a85e5663eaea34b71b6c401a20f1

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page