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import streamlit as st
import pandas as pd
from PIL import Image
import numpy as np
import tensorflow as tf
from tensorflow.keras.applications.resnet50 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
def main():
st.title('Jacaranda Identification')
st.markdown("This is a Deep Learning application to identify if a satellite image clip contains Jacaranda trees.\n")
st.markdown('The predicting result will be "Jacaranda", or "Others".')
st.markdown('You can click "Browse files" multiple times until adding all images before generating prediction.\n')
run_the_app()
@st.cache_resource()#(allow_output_mutation=True)
def load_model():
# Load the network. Because this is cached it will only happen once.
model = tf.keras.models.load_model('model')
return model
@st.cache_data()
def generate_df():
dict = {'Image file name':[],
'Class name': []
}
df = pd.DataFrame(dict)
return df
@st.cache_data()
def write_df(df, file, cls):
rec = {'Image file name': file.name,
'Class name': cls}
df = pd.concat([df, pd.DataFrame([rec])], ignore_index=True)
return df
@st.cache_data()
def convert_df(df):
return df.to_csv(index=False, encoding='utf-8')
def run_the_app():
class_names = ['Jacaranda', 'Others']
model = load_model()
df = generate_df()
uploaded_files = st.file_uploader(
"Upload images",
type="jpg" or 'jpeg' or 'bmp' or 'png' or 'tif',
accept_multiple_files=True)
if uploaded_files:
st.image(uploaded_files, width=100)
if st.button("Clear uploaded images"):
st.empty()
st.experimental_rerun()
if st.button("Generate prediction"):
for file in uploaded_files:
img = Image.open(file)
img_array = img_to_array(img)
img_array = tf.expand_dims(img_array, axis = 0) # Create a batch
processed_image = preprocess_input(img_array)
predictions = model.predict(processed_image)
score = predictions[0]
cls = class_names[np.argmax(score)]
st.markdown("Predicted class of the image {} is : {}".format(file, cls))
df = write_df(df, file, cls)
csv = convert_df(df)
st.download_button("Download the results as CSV",
data = csv,
file_name = "jacaranda_identification.csv")
if __name__ == "__main__":
main()
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