Add application file

app.py

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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="🐜"
+)
+
+with st.sidebar:
+	pages = option_menu("",["Intro", "Get started"])
+	st.write("---")
+	st.subheader("Follow me on: ")
+	st.write("𝕏 -> [@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 🐜</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 Ants species</h1>", unsafe_allow_html=True)
+			elif predicted_class == 1:
+				st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image belongs to Ghost Ants species</h1>", unsafe_allow_html=True)
+			elif predicted_class == 2:
+				st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image belongs to Weaver Ants species</h1>", unsafe_allow_html=True)
+			else:
+				st.markdown("<h1 style='font-size: 1.5vw'>The uploaded image doesnt match Ants species</h1>", unsafe_allow_html=True)