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from fastai.vision.all import *
import gradio as gr
learn = load_learner("model_2.pkl")
categories = learn.dls.vocab
for index, category in enumerate(categories):
if category == "Random Anime Photos":
categories[index] = "Others"
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.Image()
label = gr.Label()
examples = [
"Luffy.jpg",
"Naruto-Kurama-Mode.png",
"Goku.jpg",
"Ichigo.jpeg",
"Robin.jpeg",
]
title = "Top 10 Shounen Anime Protagonists Classifier"
description = "Fine tuned a resnet152 image classifier such that it is able to recognize protagonists of top 10 Shounen Animes."
start_article = (
"<p> Animes and its protagonists this image classifier will recognize:</p>"
)
anime_characters = [
"1. One Piece - Monkey D. Luffy<br>",
"2. Naruto: Shippuden - Naruto Uzumaki<br>",
"3. My Hero Academia - Izuku Midoriya<br>",
"4. Dragon Ball Z - Son Goku aka Kakarot<br>",
"5. Fairy Tail - Natsu Dragneel<br>",
"6. Yu Yu Hakusho - Yusuke Urameshi<br>",
"7. Bleach - Ichigo Kurosaki<br>",
"8. Hunter X Hunter - Gon Freecss<br>",
"9. Fullmetal Alchemist - Edward Elric<br>",
"10. Attack on Titan - Eren Yeager<br>",
]
end_article = "<p>Rest all other anime characters will be classified as others.</p>"
final_article = start_article + "".join(anime_characters) + end_article
intf = gr.Interface(
fn=classify_image,
inputs=image,
outputs=label,
examples=examples,
title=title,
description=description,
article=final_article,
)
intf.launch(inline=False, share=True) |