File size: 3,806 Bytes
4429d74 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 |
import streamlit as st
from PIL import Image, ImageFilter
import io
import zipfile
import time
def apply_filters(image):
"""Apply various filters to the image."""
filters = {
"Detail": ImageFilter.DETAIL,
"Edge Enhance": ImageFilter.EDGE_ENHANCE,
"Edge Enhance More": ImageFilter.EDGE_ENHANCE_MORE,
"Smooth": ImageFilter.SMOOTH,
"Smooth More": ImageFilter.SMOOTH_MORE,
"Sharpen": ImageFilter.SHARPEN
}
filtered_images = {}
for filter_name, filter_type in filters.items():
filtered_images[filter_name] = image.filter(filter_type)
return filtered_images
# Streamlit UI
st.title("Face Filtering App")
# Instructions sidebar
with st.sidebar:
st.header("Instructions")
st.write(
"1) If you choose only one image to upload, the results will be shown on display, and you can click the 'Download Processed Images' button to download the processed images in zip format.\n"
"2) If you choose more than one image, it will not display any image as results; instead, it will directly show you the 'Download Processed Images' button, and you can click on it to download the processed images in zip format."
)
uploaded_files = st.file_uploader("Choose images", accept_multiple_files=True, type=["jpg", "jpeg", "png"])
if st.button("Process Images"):
if uploaded_files:
processed_images = []
# Create a progress bar
progress_bar = st.progress(0)
# Show a spinner while processing images
for idx, uploaded_file in enumerate(uploaded_files):
image = Image.open(uploaded_file)
# Show original image if only one file is uploaded
if len(uploaded_files) == 1:
st.image(image, caption=f"Original Image: {uploaded_file.name}", use_column_width=True)
# Apply filters
filtered_images = apply_filters(image)
for filter_name, filtered_image in filtered_images.items():
if len(uploaded_files) == 1:
st.image(filtered_image, caption=f"{filter_name} Filter", use_column_width=True)
# Save each filtered image to a temporary in-memory buffer
buffered = io.BytesIO()
filtered_image.save(buffered, format="PNG")
processed_images.append((f"{uploaded_file.name.split('.')[0]}_{filter_name}.png", buffered.getvalue()))
# Update progress bar
progress = (idx + 1) / len(uploaded_files)
progress_bar.progress(progress)
# Simulate processing time
time.sleep(0.1)
# Create a zip file for download
zip_buffer = io.BytesIO()
with zipfile.ZipFile(zip_buffer, 'w') as zip_file:
for filename, img_data in processed_images:
zip_file.writestr(filename, img_data)
zip_buffer.seek(0)
# Provide a download button for the zip file
st.download_button(
label="Download Processed Images",
data=zip_buffer,
file_name="processed_images.zip",
mime="application/zip"
)
# Show balloon pop-up when processing is complete
st.balloons()
else:
st.warning("Please upload at least one image.")
# Copyright notice
st.markdown(
"""
<style>
.copyright {
position: fixed;
bottom: 10px;
right: 10px;
font-size: 18px;
color: #0F81C9;
}
</style>
<div class="copyright">
Copyright: [email protected]
</div>
""",
unsafe_allow_html=True
)
|