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# source: huggingface: fashn-ai/sapiens-body-part-segmentation
import colorsys
import matplotlib.colors as mcolors
import numpy as np
from PIL import Image
def get_palette(num_cls):
palette = [0] * (256 * 3)
palette[0:3] = [0, 0, 0]
for j in range(1, num_cls):
hue = (j - 1) / (num_cls - 1)
saturation = 1.0
value = 1.0 if j % 2 == 0 else 0.5
rgb = colorsys.hsv_to_rgb(hue, saturation, value)
r, g, b = [int(x * 255) for x in rgb]
palette[j * 3 : j * 3 + 3] = [r, g, b]
return palette
def create_colormap(palette):
colormap = np.array(palette).reshape(-1, 3) / 255.0
return mcolors.ListedColormap(colormap)
def visualize_mask_with_overlay(img: Image.Image, mask: Image.Image, labels_to_ids: dict[str, int], alpha=0.5):
img_np = np.array(img.convert("RGB"))
mask_np = np.array(mask)
num_cls = len(labels_to_ids)
palette = get_palette(num_cls)
colormap = create_colormap(palette)
overlay = np.zeros((*mask_np.shape, 3), dtype=np.uint8)
for label, idx in labels_to_ids.items():
if idx != 0:
overlay[mask_np == idx] = np.array(colormap(idx)[:3]) * 255
blended = Image.fromarray(np.uint8(img_np * (1 - alpha) + overlay * alpha))
return blended
def resize_image(pil_image, target_size):
"""
Resize a PIL image while maintaining its aspect ratio.
Args:
pil_image (PIL.Image): The input image.
target_size (tuple): The target size as (width, height).
Returns:
PIL.Image: The resized image.
"""
original_width, original_height = pil_image.size
target_width, target_height = target_size
# Calculate aspect ratios
aspect_ratio = original_width / original_height
target_aspect = target_width / target_height
if aspect_ratio > target_aspect:
# Image is wider than target, scale based on width
new_width = target_width
new_height = int(new_width / aspect_ratio)
else:
# Image is taller than target, scale based on height
new_height = target_height
new_width = int(new_height * aspect_ratio)
# Resize the image
resized_image = pil_image.resize((new_width, new_height), Image.LANCZOS)
# Create a new image with the target size and paste the resized image
new_image = Image.new('RGB', target_size, (0, 0, 0))
paste_x = (target_width - new_width) // 2
paste_y = (target_height - new_height) // 2
new_image.paste(resized_image, (paste_x, paste_y))
return new_image
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