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import streamlit as st |
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from tensorflow.keras.models import load_model |
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import numpy as np |
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import matplitlib.pyplot as plt |
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st.header("Photo to Monet") |
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st.caption('Upload an image 256x256') |
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model = load_model('g_model_AtoB_002160.h5') |
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@st.cache |
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def load_image(image_file): |
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img=plt.imread(image_file) |
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return img |
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imgpath = st.file_uploader("Choose a file", type =['png', 'jpeg', 'jpg']) |
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if imgpath is not None: |
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img = load_image(imgpath ) |
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st.image(img, width=250) |
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def convert(image): |
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img=load_image(img,target_size=(256,256)) |
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img_array = np.reshape(img, (1, 256, 256, 3)) |
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result=model.predict(img_array) |
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result=np.squeeze(img,axis=0) |
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return result |
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if st.button('Convert'): |
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result=convert(imagepath) |
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st.image(result) |
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