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import base64 | |
import os | |
import time | |
from io import BytesIO | |
from multiprocessing import Process | |
import streamlit as st | |
from PIL import Image | |
import requests | |
def start_server(): | |
os.system("uvicorn server:app --port 8080 --host 0.0.0.0 --workers 2") | |
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("minDALL-E") | |
#st.subheader("Generate images from text") | |
st.write("Generate images from text: Interactive demo for [minDALL-E](https://github.com/kakaobrain/minDALL-E)") | |
if not st.session_state["models_loaded"]: | |
load_models() | |
prompt = st.text_input("What do you want to see?") | |
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("Again!", key="again_button") | |
st.write(f"<b><i>UI credits: <a href='https://huggingface.co./spaces/flax-community/dalle-mini'>DALL-E mini Space</a></i></b>", unsafe_allow_html=True) | |