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import gradio as gr | |
from sklearn.metrics.pairwise import cosine_similarity | |
import numpy as np | |
from joblib import load | |
import h5py | |
from io import BytesIO | |
# Load the model and data once at startup | |
with h5py.File('complete_artist_data.hdf5', 'r') as f: | |
# Deserialize the vectorizer | |
vectorizer_bytes = f['vectorizer'][()].tobytes() | |
vectorizer_buffer = BytesIO(vectorizer_bytes) | |
vectorizer = load(vectorizer_buffer) | |
# Load X_artist | |
X_artist = f['X_artist'][:] | |
# Load artist names and decode to strings | |
artist_names = [name.decode() for name in f['artist_names'][:]] | |
def find_similar_artists(new_tags_string, top_n): | |
# | |
new_image_tags = [tag.replace('_', ' ').strip() for tag in new_tags_string.split(",")] | |
unseen_tags = set(new_image_tags) - set(vectorizer.vocabulary_.keys()) | |
unseen_tags_str = f'Unseen Tags: {", ".join(unseen_tags)}' if unseen_tags else 'No unseen tags.' | |
X_new_image = vectorizer.transform([','.join(new_image_tags)]) | |
similarities = cosine_similarity(X_new_image, X_artist)[0] | |
top_artist_indices = np.argsort(similarities)[-top_n:][::-1] | |
top_artists = [(artist_names[i], similarities[i]) for i in top_artist_indices] | |
top_artists_str = "\n".join([f"{rank+1}. {artist[3:]} ({score:.4f})" for rank, (artist, score) in enumerate(top_artists)]) | |
dynamic_prompts_formatted_artists = "{" + "|".join([artist for artist, _ in top_artists]) + "}" | |
return unseen_tags_str, top_artists_str, dynamic_prompts_formatted_artists | |
iface = gr.Interface( | |
fn=find_similar_artists, | |
inputs=[ | |
gr.Textbox(label="Enter image tags", placeholder="e.g. fox, outside, detailed background, ..."), | |
gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Number of artists") | |
], | |
outputs=[ | |
gr.Textbox(label="Unseen Tags", info="These tags are not used in the artist calculation. Even valid e6 tags may be \"unseen\" if they have insufficient data."), | |
gr.Textbox(label="Top Artists", info="These are the artists most strongly associated with your tags. The number in parenthes is a similarity score between 0 and 1, with higher numbers indicating greater similarity."), | |
gr.Textbox(label="Dynamic Prompts Format", info="For if you're using the Automatic1111 webui (https://github.com/AUTOMATIC1111/stable-diffusion-webui) with the Dynamic Prompts extension activated (https://github.com/adieyal/sd-dynamic-prompts) and want to try them all individually.") | |
], | |
title="Tagset Completer", | |
description="Enter a list of comma-separated e6 tags" | |
) | |
iface.launch() | |