frizalul/learn-flower-classification

1import streamlit as st2import tensorflow as tf3import numpy as np4from PIL import Image5 6 7st.set_option('deprecation.showfileUploaderEncoding', False)8 9@st.cache(allow_output_mutation=True)10def load_model():11	model = tf.keras.models.load_model('./flower_model_trained.hdf5')12	return model13 14 15def predict_class(image, model):16 17	image = tf.cast(image, tf.float32)18	image = tf.image.resize(image, [180, 180])19 20	image = np.expand_dims(image, axis = 0)21 22	prediction = model.predict(image)23 24	return prediction25 26 27model = load_model()28st.title('Flower Classifier')29 30file = st.file_uploader("Upload an image of a flower", type=["jpg", "png"])31 32 33if file is None:34	st.text('Waiting for upload....')35 36else:37	slot = st.empty()38	slot.text('Running inference....')39 40	test_image = Image.open(file)41 42	st.image(test_image, caption="Input Image", width = 400)43 44	pred = predict_class(np.asarray(test_image), model)45 46	class_names = ['daisy', 'dandelion', 'rose', 'sunflower', 'tulip']47 48	result = class_names[np.argmax(pred)]49 50	output = 'The image is a ' + result51 52	slot.text('Done')53 54	st.success(output)55 56