Datasets:
Formats:
imagefolder
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
1K - 10K
License:
| import os, glob | |
| import cv2 | |
| import numpy as np | |
| from tqdm import tqdm | |
| # adjust these paths | |
| color_dir = "path/to/your/color/images" | |
| depth_dir = "path/to/your/depth/images" | |
| out_dir = "path/to/your/rgbd/images" | |
| os.makedirs(out_dir, exist_ok=True) | |
| print("Processing color and depth images...") | |
| for color_path in tqdm(glob.glob(os.path.join(color_dir, "*.png"))): | |
| base = os.path.basename(color_path) | |
| depth_path = os.path.join(depth_dir, base) | |
| if not os.path.exists(depth_path): | |
| continue | |
| rgb = cv2.imread(color_path, cv2.IMREAD_UNCHANGED) # H×W×3 | |
| depth = cv2.imread(depth_path, cv2.IMREAD_UNCHANGED) # H×W (raw depth) | |
| depth = cv2.normalize(depth, None, 0, 255, cv2.NORM_MINMAX) | |
| depth = depth.astype(np.uint8) | |
| # merge to H×W×4 (B,G,R,Depth) | |
| rgba = cv2.merge([ rgb[:,:,0], rgb[:,:,1], rgb[:,:,2], depth ]) | |
| cv2.imwrite(os.path.join(out_dir, base), rgba) | |
| print("RGBD data preparation completed.") | |