| """ |
| Fetoscopy placental vessel segmentation and registration challenge (FetReg) |
| EndoVis - MICCAI2021 |
| Challenge link: https://www.synapse.org/#!Synapse:syn25313156 |
| Visualization script for image and mask for the semantic segmentation task |
| """ |
|
|
| import os |
| import cv2 |
| import numpy as np |
| import matplotlib.pyplot as plt |
|
|
|
|
| def get_colormap(): |
| """ |
| Returns FetReg colormap |
| """ |
| colormap = np.asarray( |
| [ |
| [0, 0, 0], |
| [255, 0, 0], |
| [0, 0, 255], |
| [0, 255, 0], |
|
|
| ] |
| ) |
| return colormap |
|
|
| def plot_image_n_label(img_path_fname, mask_path_fname): |
| """ |
| Plot of image and RGB mask for visualisation |
| Params |
| img_path_fname : Input image path |
| mask_path_fname: Input segmentation mask path |
| Return |
| plot of image and RGB mask |
| """ |
| |
| img = cv2.imread(img_path_fname) |
| img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) |
| mask = cv2.imread(mask_path_fname, cv2.COLOR_BGR2GRAY) |
| |
| colormap = get_colormap() |
| |
| mask_rgb = np.zeros(mask.shape[:2] + (3,), dtype=np.uint8) |
| for cnt in range(len(colormap)): |
| mask_rgb[mask == cnt] = colormap[cnt] |
| |
|
|
| fig, axs = plt.subplots(1, 2, figsize=(14, 7)) |
| axs[0].imshow(img) |
| axs[0].axis("off") |
|
|
|
|
| axs[1].imshow(mask_rgb) |
| axs[1].axis("off") |
| fig.tight_layout() |
| |
| |
| return fig |
|
|
|
|
| if __name__ == "__main__": |
| import argparse |
|
|
| parser = argparse.ArgumentParser() |
| parser.add_argument("--root", help="Path to root (video) folder that contains images and labels subfolders", required=True) |
| parser.add_argument("--output", help="Output path to save plot", required=True) |
| args = parser.parse_args() |
|
|
| assert os.path.isdir(args.root), f"{args.root} directory does not exist" |
| |
| img_path = os.path.join(args.root, 'images') |
| mask_path = os.path.join(args.root, 'labels') |
| assert os.path.exists(img_path), f"{img_path} images/labels do not exist." |
| assert os.path.exists(mask_path), f"{mask_path} images/labels do not exist." |
| |
|
|
| Img_list = np.sort(os.listdir(img_path)) |
| |
|
|
| for cnt in range(len(Img_list)): |
| fname = Img_list[cnt] |
| img_path_fname = os.path.join(img_path, fname) |
| mask_path_fname = os.path.join(mask_path, fname) |
| |
| fig = plot_image_n_label(img_path_fname, mask_path_fname) |
| if not os.path.isdir(args.output): |
| os.makedirs(args.output) |
| fname2 = fname.replace('png','jpg') |
| fig.savefig(os.path.join(args.output, fname2)) |
|
|
|
|
