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import random
from datetime import datetime
import numpy as np
import requests
import satellighte as sat
import streamlit as st
from PIL import Image
def main():
# pylint: disable=no-member
st.set_page_config(
page_title="Satellighte Demo Page",
page_icon="📡",
layout="centered",
initial_sidebar_state="expanded",
menu_items={
"Get Help": "https://canturan10.github.io/satellighte/",
"About": "Satellite Image Classification",
},
)
st.title("Satellighte Demo Page")
url = "https://raw.githubusercontent.com/canturan10/satellighte/master/src/satellighte.png?raw=true"
satellighte = Image.open(requests.get(url, stream=True).raw)
st.sidebar.image(satellighte, width=100)
st.sidebar.title("Satellighte")
st.sidebar.caption(sat.__description__)
st.write(
"**Satellighte** is an image classification library that consist state-of-the-art deep learning methods. It is a combination of the words **'Satellite'** and **'Light'**, and its purpose is to establish a light structure to classify satellite images, but to obtain robust results."
)
st.sidebar.caption(f"Version: `{sat.__version__}`")
st.sidebar.caption(f"License: `{sat.__license__}`")
st.sidebar.caption(sat.__copyright__)
selected_model = st.selectbox(
"Select model",
sat.available_models(),
)
selected_version = st.selectbox(
"Select version",
sat.get_model_versions(selected_model),
)
model = sat.Classifier.from_pretrained(selected_model, selected_version)
model.eval()
uploaded_file = st.file_uploader(
"", type=["png", "jpg", "jpeg"], accept_multiple_files=False
)
if uploaded_file is None:
st.write("Sample Image")
# Sample image.
url = f"https://raw.githubusercontent.com/canturan10/satellighte/master/src/eurosat_samples/{random_sample}?raw=true"
image = Image.open(requests.get(url, stream=True).raw)
else:
# User-selected image.
image = Image.open(uploaded_file)
image = np.array(image.convert("RGB"))
FRAME_WINDOW = st.image([], use_column_width=True)
model = sat.Classifier.from_pretrained(selected_model, selected_version)
model.eval()
results = model.predict(image)
pil_img = sat.utils.visualize(image, results)
st.write("Results:", results)
FRAME_WINDOW.image(pil_img)
if __name__ == "__main__":
samples = [
"AnnualCrop.jpg",
"Forest.jpg",
"HerbaceousVegetation.jpg",
"PermanentCrop.jpg",
"River.jpg",
]
random.seed(datetime.now())
random_sample = samples[random.randint(0, len(samples) - 1)]
main()
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