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#!/usr/bin/env python3
import gradio as gr
from clip_interrogator import Config, Interrogator
# MODELS = ['ViT-L (best for Stable Diffusion 1.*)', 'ViT-H (best for Stable Diffusion 2.*)']
# MODELS = ['ViT-L (best for Stable Diffusion 1.*)',]
# load BLIP and ViT-L https://huggingface.co/openai/clip-vit-large-patch14
from PIL import Image
from clip_interrogator import Config, Interrogator
ci = Interrogator(Config(clip_model_name="ViT-L-14/openai"))
def image_analysis(image):
image = image.convert('RGB')
image_features = ci.image_to_features(image)
top_mediums = ci.mediums.rank(image_features, 5)
top_artists = ci.artists.rank(image_features, 5)
top_movements = ci.movements.rank(image_features, 5)
top_trendings = ci.trendings.rank(image_features, 5)
top_flavors = ci.flavors.rank(image_features, 5)
medium_ranks = {medium: sim for medium, sim in zip(top_mediums, ci.similarities(image_features, top_mediums))}
artist_ranks = {artist: sim for artist, sim in zip(top_artists, ci.similarities(image_features, top_artists))}
movement_ranks = {movement: sim for movement, sim in zip(top_movements, ci.similarities(image_features, top_movements))}
trending_ranks = {trending: sim for trending, sim in zip(top_trendings, ci.similarities(image_features, top_trendings))}
flavor_ranks = {flavor: sim for flavor, sim in zip(top_flavors, ci.similarities(image_features, top_flavors))}
return medium_ranks, artist_ranks, movement_ranks, trending_ranks, flavor_ranks
def image_to_prompt(image, mode):
image = image.convert('RGB')
if mode == 'best':
prompt = ci.interrogate(image)
elif mode == 'classic':
prompt = ci.interrogate_classic(image)
elif mode == 'fast':
prompt = ci.interrogate_fast(image)
elif mode == 'negative':
prompt = ci.interrogate_negative(image)
return prompt
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
</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?<br>The CLIP Interrogator is here to get you answers!
</p>
<p>You can skip the queue by duplicating this space and upgrading to gpu in settings: <a style='display:inline-block' href='https://huggingface.co/spaces/pharma/CLIP-Interrogator?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>
</div>
"""
ARTICLE = """
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<p>
Example art by <a href="https://pixabay.com/illustrations/watercolour-painting-art-effect-4799014/">Layers</a>
and <a href="https://pixabay.com/illustrations/animal-painting-cat-feline-pet-7154059/">Lin Tong</a>
from pixabay.com
</p>
<p>
Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/main/clip_interrogator.ipynb">Google Colab</a>
</p>
<p>
Has this been helpful to you? Follow me on twitter
<a href="https://twitter.com/pharmapsychotic">@pharmapsychotic</a><br>
and check out more tools at my
<a href="https://pharmapsychotic.com/tools.html">Ai generative art tools list</a>
</p>
</div>
"""
CSS = """
#col-container {margin-left: auto; margin-right: auto;}
a {text-decoration-line: underline; font-weight: 600;}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from { transform: rotate(0deg); }
to { transform: rotate(360deg); }
}
#share-btn-container {
display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
}
#share-btn {
all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;
}
#share-btn * {
all: unset;
}
#share-btn-container div:nth-child(-n+2){
width: auto !important;
min-height: 0px !important;
}
#share-btn-container .wrap {
display: none !important;
}
"""
def analyze_tab():
with gr.Column():
with gr.Row():
image = gr.Image(type='pil', label="Image")
model = gr.Dropdown(MODELS, value=MODELS[0], label='CLIP Model')
with gr.Row():
medium = gr.Label(label="Medium", num_top_classes=5)
artist = gr.Label(label="Artist", num_top_classes=5)
movement = gr.Label(label="Movement", num_top_classes=5)
trending = gr.Label(label="Trending", num_top_classes=5)
flavor = gr.Label(label="Flavor", num_top_classes=5)
button = gr.Button("Analyze")
button.click(image_analysis, inputs=[image, model], outputs=[medium, artist, movement, trending, flavor])
examples=[['example01.jpg', MODELS[0]], ['example02.jpg', MODELS[0]]]
ex = gr.Examples(
examples=examples,
fn=image_analysis,
inputs=[input_image],
outputs=[medium, artist, movement, trending, flavor],
cache_examples=True,
run_on_click=True
)
ex.dataset.headers = [""]
with gr.Blocks(css=CSS) as block:
with gr.Column(elem_id="col-container"):
gr.HTML(TITLE)
with gr.Tab("Prompt"):
with gr.Row():
input_image = gr.Image(type='pil', elem_id="input-img")
with gr.Column():
input_mode = gr.Radio(['best', 'fast', 'classic', 'negative'], value='best', label='Mode')
submit_btn = gr.Button("Submit")
output_text = gr.Textbox(label="Output", elem_id="output-txt")
examples=[['example01.jpg', MODELS[0], 'best'], ['example02.jpg', MODELS[0], 'best']]
ex = gr.Examples(
examples=examples,
fn=image_to_prompt,
inputs=[input_image, input_mode],
outputs=[output_text],
cache_examples=True,
run_on_click=True
)
ex.dataset.headers = [""]
with gr.Tab("Analyze"):
analyze_tab()
gr.HTML(ARTICLE)
submit_btn.click(
fn=image_to_prompt,
inputs=[input_image, input_mode],
outputs=[output_text]
)
share_button.click(None, [], [], _js=share_js)
block.queue(max_size=64).launch(show_api=False) |