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)