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import streamlit as st
from streamlit_option_menu import option_menu
# from tensorflow.keras.layers import RandomFlip, RandomRotation, RandomZoom
#
import tensorflow as tf
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.image import load_img, img_to_array
import numpy as np
ant_model = load_model("myrmex.h5")
st.set_page_config(
page_title="MyrmexAI", page_icon="π"
)
with st.sidebar:
pages = option_menu("",["Intro", "Get started"])
st.write("---")
st.subheader("Follow me on: ")
st.write("π -> [@Anirudh91017141](https://x.com/Anirudh91017141)")
st.write("LinkedIn -> [anirudhhegde](https://www.linkedin.com/in/anirudhhegde/)")
st.write("GitHub -> [anirudh-hegde](https://www.github.com/anirudh-hegde)")
if pages == "Intro":
st.markdown("<br><br><p style='font-size:26px'><strong>MyrmexAI</strong> is a project based on classification of ant species like "
"FireAnts, GhostAnts and WeaverAnts. The model was trained on three datasets using \
CNN and custom layers, achieving an accuracy of 87.9%<br><br></p>", unsafe_allow_html=True)
st.markdown("<h4>How to get started</h4><br>"
"1. Upload the ant image and let the model decide which species it belongs to<br>"
"2. The model will predict the ant species for the uploaded image", unsafe_allow_html=True)
elif pages == "Get started":
title = st.markdown("<h1 style='text-align: center; color: orange; font-size: 6vw'>MyrmexAI π</h1>",
unsafe_allow_html=True)
upload_img = st.file_uploader("Choose an image")
if upload_img:
# if st.button(''):
img = load_img(upload_img, target_size=(180, 180))
img_array = img_to_array(img)
img_array = tf.expand_dims(img_array, axis=0)
predictions = ant_model.predict(img_array)
predicted_class = np.argmax(predictions)
st.image(upload_img, width=400)
# print(predicted_class)
if predicted_class == 0:
st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image belongs to Fire Ant species</h1>", unsafe_allow_html=True)
elif predicted_class == 1:
st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image belongs to Ghost Ant species</h1>", unsafe_allow_html=True)
elif predicted_class == 2:
st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image belongs to Weaver Ant species</h1>", unsafe_allow_html=True)
else:
st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image doesnt match Ant species</h1>", unsafe_allow_html=True) |