import streamlit as st from PIL import Image import tensorflow as tf import matplotlib.pyplot as plt import numpy as np model = tf.keras.models.load_model('modelo.h5') file = st.file_uploader("Por favor suba una imagen de ropa (jpg, png, jpeg)", type=['jpg','png','jpeg']) if file is not None: bytes_data = file.read() x = np.array(Image.open(BytesIO(bytes_data))) x = x / 255.00 plt.figure() plt.imshow(imagen, cmap=plt.cm.binary) plt.colorbar() plt.grid(False) plt.show() col1, col2, col3 = st.columns(3) with col1: st.write("") with col2: image = Image.open(file) st.markdown('

Image

',unsafe_allow_html=True) st.image(image,width=300) with col3: st.write("")