utils.py

import numpy as np
from PIL import Image
import cv2


def save_uploadedfile(uploaded_image, save_path):
    im = Image.open(uploaded_image)
    if im.mode in ("RGBA", "P"):
        im = im.convert("RGB")
    im.save(save_path)


def overlay(image, mask, color, alpha, resize=None):
    """Combines image and its segmentation mask into a single image.

    Params:
        image: Training image. np.ndarray,
        mask: Segmentation mask. np.ndarray,
        color: Color for segmentation mask rendering.  tuple[int, int, int] = (255, 0, 0)
        alpha: Segmentation mask's transparency. float = 0.5,
        resize: If provided, both image and its mask are resized before blending them together.
        tuple[int, int] = (1024, 1024))

    Returns:
        image_combined: The combined image. np.ndarray

    """
    colored_mask = np.expand_dims(mask, 0).repeat(3, axis=0)
    colored_mask = np.moveaxis(colored_mask, 0, -1)
    masked = np.ma.MaskedArray(image, mask=colored_mask, fill_value=color)
    image_overlay = masked.filled()

    if resize is not None:
        image = cv2.resize(image.transpose(1, 2, 0), resize)
        image_overlay = cv2.resize(image_overlay.transpose(1, 2, 0), resize)

    image_combined = cv2.addWeighted(image, 1 - alpha, image_overlay, alpha, 0)

    return image_combined


def apply_masks(img, masks):
    for mask in masks:
        h, w, _ = img.shape
        mask = cv2.resize(mask, (w, h))
        img = overlay(img, mask, color=(0, 255, 0), alpha=0.3)
    return img