Image-Colorizer / streamlit_app.py
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import streamlit as st
import requests
import os
import sys
from PIL import Image
import io
import time
from pathlib import Path
# Fix for 'collections' has no attribute 'Sized' issue
import collections
import collections.abc
for typ in ['Sized', 'Iterable', 'Mapping', 'MutableMapping', 'Sequence', 'MutableSequence']:
if not hasattr(collections, typ):
setattr(collections, typ, getattr(collections.abc, typ))
# Add DeOldify directory to path in case direct importing is needed
sys.path.append('./DeOldify')
# Instead of adding models directory to path, set it as the working directory for model loading
os.makedirs('models', exist_ok=True)
# Create symbolic links to the model files
if not os.path.exists('models/ColorizeArtistic_gen.pth'):
os.symlink(os.path.abspath('./DeOldify/models/ColorizeArtistic_gen.pth'),
'models/ColorizeArtistic_gen.pth')
if not os.path.exists('models/ColorizeStable_gen.pth'):
os.symlink(os.path.abspath(
'./DeOldify/models/ColorizeStable_gen.pth'), 'models/ColorizeStable_gen.pth')
if not os.path.exists('models/ColorizeVideo_gen.pth'):
os.symlink(os.path.abspath(
'./DeOldify/models/ColorizeVideo_gen.pth'), 'models/ColorizeVideo_gen.pth')
# URLs for the API
# Change this if your API is running on a different address
API_URL = "http://localhost:8000"
st.set_page_config(
page_title="Image Colorization App",
page_icon="🎨",
layout="wide",
)
st.title("Black & White Image Colorization")
st.markdown("""
Turn your black and white photos into colorized versions using DeOldify technology.
Upload an image to get started!
""")
# File uploader
uploaded_file = st.file_uploader(
"Choose a black and white image...", type=["jpg", "jpeg", "png"])
# Sidebar controls
with st.sidebar:
st.header("Colorization Options")
# Model selection
model_type = st.radio(
"Select Colorization Model",
options=["Artistic", "Stable"],
index=0,
help="Artistic provides more vibrant colors, Stable provides more realistic colors"
)
# Render factor slider
render_factor = st.slider(
"Render Factor",
min_value=5,
max_value=50,
value=35,
step=1,
help="Higher values give better quality but take longer. Recommend 35 for artistic, 20 for stable."
)
# Multiple render options
st.subheader("Generate Multiple Renders")
use_multiple_renders = st.checkbox(
"Create multiple renders with different factors", value=False)
if use_multiple_renders:
min_factor = st.slider("Minimum Render Factor", 5, 40, 10, 5)
max_factor = st.slider("Maximum Render Factor",
min_factor + 5, 50, 40, 5)
step_size = st.slider("Step Size", 1, 10, 5, 1)
# Process when upload is ready
if uploaded_file is not None:
# Display the original image
col1, col2 = st.columns(2)
with col1:
st.subheader("Original Image")
image = Image.open(uploaded_file)
st.image(image, use_column_width=True)
# Process image button
process_button = st.button("Colorize Image")
if process_button:
artistic_param = True if model_type == "Artistic" else False
with st.spinner("Colorizing your image... Please wait."):
try:
if use_multiple_renders:
# Process with multiple render factors
files = {
"file": ("image.jpg", uploaded_file.getvalue(), "image/jpeg")}
params = {
"min_render_factor": min_factor,
"max_render_factor": max_factor,
"step": step_size,
"artistic": artistic_param
}
response = requests.post(
f"{API_URL}/colorize_multiple", files=files, params=params)
if response.status_code == 200:
result = response.json()
st.success("Multiple renders completed!")
# Display all the images with a slider to choose
st.subheader("Select Render Factor")
selected_index = st.select_slider(
"Choose the render factor that looks best:",
options=result["render_factors"]
)
# Find the index of the selected render factor
index = result["render_factors"].index(selected_index)
selected_image_path = result["output_paths"][index]
# Display the selected image
with col2:
st.subheader(
f"Colorized (Render Factor: {selected_index})")
colorized_img = requests.get(
f"{API_URL}/image/{selected_image_path}").content
st.image(Image.open(io.BytesIO(
colorized_img)), use_column_width=True)
# Option to download the selected image
st.download_button(
label="Download Colorized Image",
data=colorized_img,
file_name=f"colorized_rf{selected_index}.jpg",
mime="image/jpeg"
)
else:
st.error(f"Error: {response.text}")
else:
# Process with single render factor
files = {
"file": ("image.jpg", uploaded_file.getvalue(), "image/jpeg")}
params = {
"render_factor": render_factor,
"artistic": artistic_param
}
response = requests.post(
f"{API_URL}/colorize", files=files, params=params)
if response.status_code == 200:
result = response.json()
with col2:
st.subheader(
f"Colorized (Render Factor: {result['render_factor']})")
colorized_img = requests.get(
f"{API_URL}/image/{result['output_path']}").content
st.image(Image.open(io.BytesIO(
colorized_img)), use_column_width=True)
# Option to download the colorized image
st.download_button(
label="Download Colorized Image",
data=colorized_img,
file_name="colorized.jpg",
mime="image/jpeg"
)
else:
st.error(f"Error: {response.text}")
except Exception as e:
st.error(f"An error occurred: {str(e)}")
# Footer
st.markdown("---")
st.markdown("Powered by DeOldify - Image Colorization Project")