| import os |
| import numpy as np |
| from plyfile import PlyData |
| from tqdm import tqdm |
|
|
|
|
| def preprocess(gt_path, save_path): |
| """Preprocess the CompleteScanNet dataset gt labels. |
| |
| Args: |
| gt_path (str): Path to `CompleteScanNet_GT` directory. |
| save_path (str): Path where the preprocessed gt labels to be saved. The preprocessed labels |
| is a ndarray each with shape (N, 7), N is for voxels number, 7 is for [x, y, z, r, g, b, label]. |
| """ |
| os.makedirs(save_path, exist_ok=True) |
| ply_paths = os.listdir(gt_path) |
| for p in tqdm(ply_paths, desc="Preprocessing gt labels: ", colour='green'): |
| pth = os.path.join(gt_path, p) |
| |
| ply_data = PlyData.read(pth) |
| vertex = ply_data['vertex'] |
| new_xs = np.array(vertex['z']) |
| new_ys = np.array(vertex['x']) |
| new_zs = np.array(vertex['y']) |
| new_rs = np.array(vertex['red']) |
| new_gs = np.array(vertex['green']) |
| new_bs = np.array(vertex['blue']) |
| new_labels = np.array(vertex['label']) |
| voxels = np.stack([new_xs, new_ys, new_zs, new_rs, new_gs, new_bs, new_labels], axis=1) |
| |
| filename = os.path.join(save_path, p) |
| filename = filename.replace('ply', 'npy') |
| with open(filename, 'wb') as fp: |
| np.save(fp, voxels) |
| |
|
|
| if __name__ == "__main__": |
| gt = os.getenv["COMPLETE_SCANNET_GT_PATH"] |
| preprocessed = os.getenv["COMPLETE_SCANNET_PREPROCESS_PATH"] |
| preprocess(gt, preprocessed) |
