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import streamlit as st
from PIL import Image
import re
from io import BytesIO
import segmentation
def init():
st.set_page_config(page_title="Semantic image segmentation")
st.session_state["model"] = segmentation.create_model()
st.session_state["feature_extractor"] = segmentation.create_feature_extractor()
@st.experimental_memo(show_spinner=False)
def process_file(file):
return segmentation.segment(
Image.open(file),
st.session_state["model"],
st.session_state["feature_extractor"]
)
def get_uploaded_file():
return st.file_uploader(
label="Choose a file",
type=["png", "jpg", "jpeg"],
)
def download_button(file, name, format):
st.download_button(
label="Download processed image",
data=file,
file_name=name,
mime="image/" + format
)
def run():
st.title("Semantic image segmentation")
st.subheader("Upload your image and get an image with segmentation")
file = get_uploaded_file()
if not file:
return
placeholder = st.empty()
placeholder.info(
"Processing..."
)
image = process_file(file)
placeholder.empty()
placeholder.image(image)
filename = file.name
format = re.findall("\..*$", filename)[0][1:]
image = Image.fromarray(image)
buf = BytesIO()
image.save(buf, format="JPEG")
byte_image = buf.getvalue()
download_button(byte_image, filename, format)
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