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import os.path
import streamlit as st
from models.deep_colorization.colorizers import *
import cv2
from PIL import Image
import tempfile
import moviepy.editor as mp
import time
from tqdm import tqdm
def format_time(seconds: float) -> str:
"""Formats time in seconds to a human readable format"""
if seconds < 60:
return f"{int(seconds)} seconds"
elif seconds < 3600:
minutes = seconds // 60
seconds %= 60
return f"{minutes} minutes and {int(seconds)} seconds"
elif seconds < 86400:
hours = seconds // 3600
minutes = (seconds % 3600) // 60
seconds %= 60
return f"{hours} hours, {minutes} minutes, and {int(seconds)} seconds"
else:
days = seconds // 86400
hours = (seconds % 86400) // 3600
minutes = (seconds % 3600) // 60
seconds %= 60
return f"{days} days, {hours} hours, {minutes} minutes, and {int(seconds)} seconds"
# Function to colorize video frames
def colorize_frame(frame, colorizer) -> np.ndarray:
tens_l_orig, tens_l_rs = preprocess_img(frame, HW=(256, 256))
return postprocess_tens(tens_l_orig, colorizer(tens_l_rs).cpu())
image = Image.open(r'img/streamlit.png') # Brand logo image (optional)
# Create two columns with different width
col1, col2 = st.columns([0.8, 0.2])
with col1: # To display the header text using css style
st.markdown(""" <style> .font {
font-size:35px ; font-family: 'Cooper Black'; color: #FF4B4B;}
</style> """, unsafe_allow_html=True)
st.markdown('<p class="font">Upload your photo or video here...</p>', unsafe_allow_html=True)
with col2: # To display brand logo
st.image(image, width=100)
# Add a header and expander in side bar
st.sidebar.markdown('<p class="font">Color Revive App</p>', unsafe_allow_html=True)
with st.sidebar.expander("About the App"):
st.write("""
Use this simple app to colorize your black and white images and videos with state of the art models.
""")
# Add file uploader to allow users to upload photos
uploaded_file = st.file_uploader("", type=['jpg', 'png', 'jpeg', 'mp4'])
# Add 'before' and 'after' columns
if uploaded_file is not None:
file_extension = os.path.splitext(uploaded_file.name)[1].lower()
if file_extension in ['jpg', 'png', 'jpeg']:
image = Image.open(uploaded_file)
col1, col2 = st.columns([0.5, 0.5])
with col1:
st.markdown('<p style="text-align: center;">Before</p>', unsafe_allow_html=True)
st.image(image, width=300)
# Add conditional statements to take the user input values
with col2:
st.markdown('<p style="text-align: center;">After</p>', unsafe_allow_html=True)
filter = st.sidebar.radio('Colorize your image with:',
['Original', 'ECCV 16', 'SIGGRAPH 17'])
if filter == 'ECCV 16':
colorizer_eccv16 = eccv16(pretrained=True).eval()
img = load_img(uploaded_file)
tens_l_orig, tens_l_rs = preprocess_img(img, HW=(256, 256))
out_img_eccv16 = postprocess_tens(tens_l_orig, colorizer_eccv16(tens_l_rs).cpu())
st.image(out_img_eccv16, width=300)
elif filter == 'SIGGRAPH 17':
colorizer_siggraph17 = siggraph17(pretrained=True).eval()
img = load_img(uploaded_file)
tens_l_orig, tens_l_rs = preprocess_img(img, HW=(256, 256))
out_img_siggraph17 = postprocess_tens(tens_l_orig, colorizer_siggraph17(tens_l_rs).cpu())
st.image(out_img_siggraph17, width=300)
else:
st.image(image, width=300)
elif file_extension == 'mp4': # If uploaded file is a video
# Save the video file to a temporary location
temp_file = tempfile.NamedTemporaryFile(delete=False)
temp_file.write(uploaded_file.read())
# Open the video using cv2.VideoCapture
video = cv2.VideoCapture(temp_file.name)
# Get video information
fps = video.get(cv2.CAP_PROP_FPS)
# Create two columns for video display
col1, col2 = st.columns([0.5, 0.5])
with col1:
st.markdown('<p style="text-align: center;">Before</p>', unsafe_allow_html=True)
st.video(temp_file.name)
with col2:
st.markdown('<p style="text-align: center;">After</p>', unsafe_allow_html=True)
filter = st.sidebar.radio('Colorize your video with:',
['Original', 'ECCV 16', 'SIGGRAPH 17'])
if filter == 'ECCV 16':
colorizer = eccv16(pretrained=True).eval()
elif filter == 'SIGGRAPH 17':
colorizer = siggraph17(pretrained=True).eval()
if filter != 'Original':
with st.spinner("Colorizing frames..."):
# Colorize video frames and store in a list
output_frames = []
total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
progress_bar = st.empty()
start_time = time.time()
for i in tqdm(range(total_frames), unit='frame', desc="Progress"):
ret, frame = video.read()
if not ret:
break
colorized_frame = colorize_frame(frame, colorizer)
output_frames.append((colorized_frame * 255).astype(np.uint8))
elapsed_time = time.time() - start_time
frames_completed = len(output_frames)
frames_remaining = total_frames - frames_completed
time_remaining = (frames_remaining / frames_completed) * elapsed_time
progress_bar.progress(frames_completed / total_frames)
if frames_completed < total_frames:
progress_bar.text(f"Time Remaining: {format_time(time_remaining)}")
else:
progress_bar.empty()
with st.spinner("Merging frames to video..."):
frame_size = output_frames[0].shape[:2]
output_filename = "output.mp4"
fourcc = cv2.VideoWriter_fourcc(*"mp4v") # Codec for MP4 video
out = cv2.VideoWriter(output_filename, fourcc, fps, (frame_size[1], frame_size[0]))
# Display the colorized video using st.video
for frame in output_frames:
frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
out.write(frame_bgr)
out.release()
# Convert the output video to a format compatible with Streamlit
converted_filename = "converted_output.mp4"
clip = mp.VideoFileClip(output_filename)
clip.write_videofile(converted_filename, codec="libx264")
# Display the converted video using st.video()
st.video(converted_filename)
# Add a download button for the colorized video
st.download_button(
label="Download Colorized Video",
data=open(converted_filename, "rb").read(),
file_name="colorized_video.mp4"
)
# Close and delete the temporary file after processing
video.release()
temp_file.close()
# Add a feedback section in the sidebar
st.sidebar.title(' ') # Used to create some space between the filter widget and the comments section
st.sidebar.markdown(' ') # Used to create some space between the filter widget and the comments section
st.sidebar.subheader('Please help us improve!')
with st.sidebar.form(key='columns_in_form',
clear_on_submit=True): # set clear_on_submit=True so that the form will be reset/cleared once
# it's submitted
rating = st.slider("Please rate the app", min_value=1, max_value=5, value=3,
help='Drag the slider to rate the app. This is a 1-5 rating scale where 5 is the highest rating')
text = st.text_input(label='Please leave your feedback here')
submitted = st.form_submit_button('Submit')
if submitted:
st.write('Thanks for your feedback!')
st.markdown('Your Rating:')
st.markdown(rating)
st.markdown('Your Feedback:')
st.markdown(text)
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