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import streamlit as st
import pandas as pd
import json
import pickle
import numpy as np
import tensorflow as tf
from keras.models import load_model
model = load_model("model_after.h5")
with open('dict_butterfly_index.json','r') as file_2:
dict_butterfly_index = json.load(file_2)
def run():
with st.form('prediction_form'):
st.write('Personal Information')
uploaded = st.file_uploader(label='Input File Image',type=['png','jpg'])
submitted = st.form_submit_button()
st.write("Result Prediction")
if submitted:
img = tf.keras.utils.load_img(uploaded, target_size=(224, 224))
x = tf.keras.utils.img_to_array(img)/255
x = np.expand_dims(x, axis=0)
images = np.vstack((x,x))
classes = model.predict(images, batch_size=10)
idx = np.argmax(classes[0])
st.write(f"The predictions is = {dict_butterfly_index[str(idx)]}")
st.image(img,caption="Uploaded Image", use_column_width=True)
if __name__ == '__main__':
run() |