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import json
import gradio as gr
import os
from PIL import Image
clusters_12 = json.load(open("clusters/id_all_blip_clusters_12.json"))
clusters_24 = json.load(open("clusters/id_all_blip_clusters_24.json"))
clusters_48 = json.load(open("clusters/id_all_blip_clusters_48.json"))
clusters_by_size = {
12: clusters_12,
24: clusters_24,
48: clusters_48,
}
def show_cluster(cl_id, num_clusters):
cl_dct = clusters_by_size[num_clusters][cl_id]
images = []
for i in range(6):
img_path = "/".join([st.replace("/", "") for st in cl_dct['img_path_list'][i].split("//")][3:])
img_path = os.path.join("identities-images", img_path)
images.append(Image.open(img_path))
return (len(cl_dct['img_path_list']),
json.dumps(dict(cl_dct["labels_gender"])),
dict(cl_dct["labels_model"]),
dict(cl_dct["labels_ethnicity"]),
images)
with gr.Blocks() as demo:
gr.Markdown("# Cluster Explorer")
gr.HTML("""<span style="color:red">⚠️ <b>DISCLAIMER: the images displayed by this tool were generated by text-to-image models and may depict offensive stereotypes or contain explicit content.</b></span>""")
with gr.Row():
num_clusters = gr.Radio([12, 24, 48], label="number of clusters")
cluster_id = gr.Number(precision=0, label="cluster id")
button = gr.Button(value="Go")
with gr.Column():
a = gr.Text(label="Number of items in cluster")
with gr.Row():
c = gr.Text(label="Model makeup of cluster")
b = gr.Markdown(label="Gender label makeup of cluster")
d = gr.Text(label="Ethnicity label makeup of cluster")
gallery = gr.Gallery(label="Most representative images in cluster").style(grid=6)
button.click(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a,b,c,d, gallery])
# demo = gr.Interface(fn=show_cluster, inputs=[gr.Slider(0, 50), gr.Radio([12, 24, 48])], outputs=["text", "text", "text", "text", gr.Gallery()])
demo.launch(debug=True)
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