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#@title Setup
import os, subprocess
def setup():
install_cmds = [
['pip', 'install', 'ftfy', 'gradio', 'regex', 'tqdm', 'transformers==4.21.2', 'timm', 'fairscale', 'requests'],
['pip', 'install', 'open_clip_torch'],
['pip', 'install', '-e', 'git+https://github.com/pharmapsychotic/BLIP.git@lib#egg=blip'],
['git', 'clone', '-b', 'open-clip', 'https://github.com/pharmapsychotic/clip-interrogator.git']
]
for cmd in install_cmds:
print(subprocess.run(cmd, stdout=subprocess.PIPE).stdout.decode('utf-8'))
setup()
# download cache files
print("Download preprocessed cache files...")
CACHE_URLS = [
'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_artists.pkl',
'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_flavors.pkl',
'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_mediums.pkl',
'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_movements.pkl',
'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_trendings.pkl',
]
os.makedirs('cache', exist_ok=True)
for url in CACHE_URLS:
print(subprocess.run(['wget', url, '-P', 'cache'], stdout=subprocess.PIPE).stdout.decode('utf-8'))
import sys
sys.path.append('src/blip')
sys.path.append('clip-interrogator')
import gradio as gr
from clip_interrogator import Config, Interrogator
config = Config()
config.blip_offload = True
config.chunk_size = 2048
config.flavor_intermediate_count = 512
config.blip_num_beams = 64
ci = Interrogator(config)
def inference(image, mode, best_max_flavors):
image = image.convert('RGB')
if mode == 'best':
return ci.interrogate(image, max_flavors=int(best_max_flavors))
elif mode == 'classic':
return ci.interrogate_classic(image)
else:
return ci.interrogate_fast(image)
title = """
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<h1 style="font-weight: 900; margin-bottom: 7px;">
CLIP Interrogator 2.1
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
Want to figure out what a good prompt might be to create new images like an existing one? The CLIP Interrogator is here to get you answers!
<br />This version is specialized for producing nice prompts for use with Stable Diffusion 2.0 using the ViT-H-14 OpenCLIP model!
</p>
</div>
"""
article = """
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<p>
Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/open-clip/clip_interrogator.ipynb">Google Colab</a>
</p>
<p>
Has this been helpful to you? Follow Pharma on twitter
<a href="https://twitter.com/pharmapsychotic">@pharmapsychotic</a>
and check out more tools at his
<a href="https://pharmapsychotic.com/tools.html">Ai generative art tools list</a>
</p>
</div>
"""
inputs = [
gr.inputs.Image(type='pil'),
gr.Radio(['best', 'classic', 'fast'], label='', value='best'),
gr.Number(value=4, label='best mode max flavors'),
]
outputs = [
gr.outputs.Textbox(label="Output"),
]
io = gr.Interface(
inference,
inputs,
outputs,
allow_flagging=False,
)
io.launch() |