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""" Code inspired by https://huggingface.co/spaces/flax-community/dalle-mini
"""
import base64
import os
import time
from io import BytesIO
from multiprocessing import Process
import streamlit as st
from PIL import Image
import requests
import logging
def start_server():
os.system("uvicorn server:app --port 8080 --host 0.0.0.0 --workers 1")
def load_models():
if not is_port_in_use(8080):
with st.spinner(text="Loading models, please wait..."):
proc = Process(target=start_server, args=(), daemon=True)
proc.start()
while not is_port_in_use(8080):
time.sleep(1)
st.success("Model server started.")
else:
st.success("Model server already running...")
st.session_state["models_loaded"] = True
def is_port_in_use(port):
import socket
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
return s.connect_ex(("0.0.0.0", port)) == 0
def generate(prompt):
correct_request = f"http://0.0.0.0:8080/correct?prompt={prompt}"
response = requests.get(correct_request)
images = response.json()["images"]
images = [Image.open(BytesIO(base64.b64decode(img))) for img in images]
return images
if "models_loaded" not in st.session_state:
st.session_state["models_loaded"] = False
st.header("Logo generator")
#st.subheader("Generate images from text")
st.write("Generate logos from text")
if not st.session_state["models_loaded"]:
load_models()
prompt = st.text_input("Your text prompt. Tip: start with 'a logo of...':")
DEBUG = False
# UI code taken from https://huggingface.co/spaces/flax-community/dalle-mini/blob/main/app/streamlit/app.py
if prompt != "":
container = st.empty()
container.markdown(
f"""
<style> p {{ margin:0 }} div {{ margin:0 }} </style>
<div data-stale="false" class="element-container css-1e5imcs e1tzin5v1">
<div class="stAlert">
<div role="alert" data-baseweb="notification" class="st-ae st-af st-ag st-ah st-ai st-aj st-ak st-g3 st-am st-b8 st-ao st-ap st-aq st-ar st-as st-at st-au st-av st-aw st-ax st-ay st-az st-b9 st-b1 st-b2 st-b3 st-b4 st-b5 st-b6">
<div class="st-b7">
<div class="css-whx05o e13vu3m50">
<div data-testid="stMarkdownContainer" class="css-1ekf893 e16nr0p30">
<img src="https://raw.githubusercontent.com/borisdayma/dalle-mini/main/app/streamlit/img/loading.gif" width="30"/>
Generating predictions for: <b>{prompt}</b>
</div>
</div>
</div>
</div>
</div>
</div>
""",
unsafe_allow_html=True,
)
print(f"Getting selections: {prompt}")
selected = generate(prompt)
margin = 0.1 # for better position of zoom in arrow
n_columns = 3
cols = st.columns([1] + [margin, 1] * (n_columns - 1))
for i, img in enumerate(selected):
cols[(i % n_columns) * 2].image(img)
container.markdown(f"**{prompt}**")
st.button("Run again", key="again_button")
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