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import gradio as gr
from fastai.vision.all import *
import timm
# Importing the model
model = load_learner('model.pkl')
categories = model.dls.vocab
def predict_snake_type(img):
snake_type, idx, probs = model.predict(img)
return dict(zip(categories, map(float, probs)))
# Gradio Interface
input_img = gr.Image()
outputs = gr.Label(num_top_classes=5)
gr.Interface(
fn=predict_snake_type,
inputs=[input_img], outputs=outputs,
examples=[
'examples/agkistrodon-contortrix.jpg',
'examples/haldea-striatula.jpg',
'examples/masticophis-flagellum.jpg',
'examples/storeria-occipitomaculata.jpg'
],
title='Classifying Different Breeds of snakes',
description='''
This is a multi-classification model that identifies different breeds of snakes.
This model is `74%` accurate, and can identify the breeds of snakes present in this file: https://huggingface.co/spaces/UtkMal/Classifying-snake-breeds/blob/main/app.py'''
).launch() |