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| import streamlit as st | |
| import cv2 | |
| def rgb(r, g, b): | |
| return '#{:02x}{:02x}{:02x}'.format(r, g, b) | |
| def show_images(images, names, num_cols, channels="RGB"): | |
| num_images = len(images) | |
| # Calculate the number of rows and columns | |
| num_rows = -( | |
| -num_images // num_cols | |
| ) # This also handles the case when num_images is not a multiple of num_cols | |
| for row in range(num_rows): | |
| # Create the columns | |
| cols = st.sidebar.columns(num_cols) | |
| for i, col in enumerate(cols): | |
| idx = row * num_cols + i | |
| if idx < num_images: | |
| img = images[idx] | |
| if len(names) == 0: | |
| names = ["Unknown"] * len(images) | |
| name = names[idx] | |
| col.image(img, caption=name, channels=channels, width=112) | |
| def show_faces(images, names, distances, gal_images, num_cols, channels="RGB", display=st): | |
| if len(images) == 0 or len(names) == 0: | |
| display.write("No faces detected, or gallery empty!") | |
| return | |
| # Calculate the number of rows and columns | |
| num_rows = -( | |
| -len(images) // num_cols | |
| ) # This also handles the case when num_images is not a multiple of num_cols | |
| for row in range(num_rows): | |
| # Create the columns | |
| cols = display.columns(num_cols) | |
| for i, col in enumerate(cols): | |
| idx = row * num_cols + i | |
| if idx < len(images): | |
| img = images[idx] | |
| name = names[idx] | |
| dist = distances[idx] | |
| col.image(img, channels=channels, width=112) | |
| if gal_images[idx] is not None: | |
| col.text(" ⬍ matching ⬍") | |
| col.image(gal_images[idx], caption=name, channels=channels, width=112) | |
| else: | |
| col.markdown("") | |
| col.write("No match found") | |
| col.markdown( | |
| f"**Distance: {dist:.4f}**" if dist else f"**Distance: -**" | |
| ) | |
| else: | |
| col.empty() | |
| col.markdown("") | |
| col.empty() | |
| col.markdown("") | |