app.py

import pickle
import gradio as gr
from datasets import load_dataset
from transformers import AutoModel, AutoFeatureExtractor
import wikipedia


# Only runs once when the script is first run.
with open("butts_1024_new.pickle", "rb") as handle:
    index = pickle.load(handle)

# Load model for computing embeddings.
feature_extractor = AutoFeatureExtractor.from_pretrained("sasha/autotrain-butterfly-similarity-2490576840")
model = AutoModel.from_pretrained("sasha/autotrain-butterfly-similarity-2490576840")

# Candidate images.
dataset = load_dataset("sasha/butterflies_10k_names_multiple")
ds = dataset["train"]


def query(image, top_k=4):
    inputs = feature_extractor(image, return_tensors="pt")
    model_output = model(**inputs)
    embedding = model_output.pooler_output.detach()
    results = index.query(embedding, k=top_k)
    inx = results[0][0].tolist()
    logits = results[1][0].tolist()
    images = ds.select(inx)["image"]
    captions = ds.select(inx)["name"]
    images_with_captions = [(i, c) for i, c in zip(images,captions)]
    labels_with_probs = dict(zip(captions,logits))
    labels_with_probs = {k: 1- v for k, v in labels_with_probs.items()}
    try:
    	description = wikipedia.summary(captions[0], sentences = 1)
    	description = "### " + description
    	url = wikipedia.page(captions[0]).url
    	url = " You can learn more about your butterfly [here](" + str(url) + ")!"
    	description = description + url
    except:
    	description = "### Butterflies are insects in the order Lepidoptera, which also includes moths. Adult butterflies have large, often brightly coloured wings."
    	url = "https://en.wikipedia.org/wiki/Butterfly"
    	url = " You can learn more about butterflies [here](" + str(url) + ")!"
    	description = description + url
    return images_with_captions, labels_with_probs, description


with gr.Blocks() as demo:
	gr.Markdown("# Find my Butterfly 🦋")
	gr.Markdown("## Use this Space to find your butterfly, based on the [iNaturalist butterfly dataset](https://huggingface.co/datasets/huggan/inat_butterflies_top10k)!")
	with gr.Row():
		with gr.Column(scale=1):
			inputs = gr.Image()
			btn = gr.Button("Find my butterfly!")
			description = gr.Markdown()
			
		with gr.Column(scale=2):
			outputs=gr.Gallery(rows=2)
			labels = gr.Label()
			
	gr.Markdown("### Image Examples")
	gr.Examples(
	examples=["elton.jpg", "ken.jpg", "gaga.jpg", "taylor.jpg"],
	inputs=inputs,
	outputs=[outputs,labels],
	fn=query,
	cache_examples=True,
	)
	btn.click(query, inputs, [outputs, labels, description])
	
demo.launch()