| import cv2
|
| import os
|
| import glob
|
| import numpy as np
|
|
|
| def concat_change_detection_images(img1_path, img2_path, label_path, pred_path, output_path):
|
| img1 = cv2.imread(img1_path)
|
| img2 = cv2.imread(img2_path)
|
| label = cv2.imread(label_path) if os.path.exists(label_path) else None
|
| pred = cv2.imread(pred_path)
|
|
|
| if img1 is None or img2 is None or pred is None:
|
| print(f"Missing or unreadable image: {img1_path}, {img2_path}, {pred_path}")
|
| return
|
|
|
|
|
| h, w = img1.shape[:2]
|
| img2 = cv2.resize(img2, (w, h))
|
| pred = cv2.resize(pred, (w, h))
|
| if label is not None:
|
| label = cv2.resize(label, (w, h))
|
|
|
|
|
| if label is not None:
|
| concat = np.concatenate([img1, img2, label, pred], axis=1)
|
| else:
|
| concat = np.concatenate([img1, img2, pred], axis=1)
|
|
|
| cv2.imwrite(output_path, concat)
|
|
|
| def batch_process(img1_dir, img2_dir, label_dir, pred_dir, output_dir):
|
| os.makedirs(output_dir, exist_ok=True)
|
| img1_paths = glob.glob(os.path.join(img1_dir, "*.png"))
|
| for img1_path in img1_paths:
|
| filename = os.path.basename(img1_path)
|
| img2_path = os.path.join(img2_dir, filename)
|
| label_path = os.path.join(label_dir, filename) if label_dir else None
|
| pred_path = os.path.join(pred_dir, filename)
|
| output_path = os.path.join(output_dir, filename.replace(".png", "_concat.png"))
|
|
|
| print(f"[INFO] img1: {img1_path}, img2: {img2_path}")
|
| print(f"[INFO] label: {label_path}, pred: {pred_path}")
|
|
|
| concat_change_detection_images(img1_path, img2_path, label_path, pred_path, output_path)
|
| print(f"Saved: {output_path}")
|
|
|
|
|
| img1_dir = "data/WHU_CD/test/image1"
|
| img2_dir = "data/WHU_CD/test/image2"
|
| label_dir = "data/WHU_CD/test/label"
|
| pred_dir = "work_dirs/CLCD_BS4_epoch200/CDXFormer/version_0/ckpts/test/mask_rgb"
|
| output_dir = "mask_connect_test_dir"
|
|
|
| batch_process(img1_dir, img2_dir, label_dir, pred_dir, output_dir)
|
|
|
