# Copyright 2026 Toyota Research Institute.  All rights reserved.

import os
import numpy as np

from glob import glob

from anydata.utils.read import read_numpy, read_image, read_depth, read_json
from anydata.utils.write import write_json, write_lowdim, write_labels
from anydata.converters.utils import run, add_key_to_dict, fill_metadata, parse_dst_seq, frame_name, crawl, prepare_lowdim

#######################################################

def get_depth(filename):
    depth = read_depth(filename, div=1000)
    return depth
    
def get_mask(filename):
    return np.array(read_image(filename, '1'))
    
#######################################################

def get_sequences(args):
    seqs = crawl(args.src, 'metadata')
    seqs = [os.path.dirname(seq) for seq in seqs]
    return seqs


def parse_sequence(seq, args):
    return parse_dst_seq(seq, args)

#######################################################

def process_sequence(i, seq, dst, args):

    ### Initialize lists and dicts
    cameras = ['0']
    num_frames = {cam: dict() for cam in cameras}
    resolution = {cam: dict() for cam in cameras}
    labels, lowdim = [], {}
    dense_labels = ['rgb','depth','mask_depth']

    ### Get filenames
    filename_rgbs = sorted(glob(f'{seq}/rgb/*'))
    filename_depths = sorted(glob(f'{seq}/depth/*'))
    filename_mask_depths = sorted(glob(f'{seq}/masks/*'))

    ### Get extrinsics
    with open(f'{seq}/cam_poses.txt', 'r') as file:
        extrinsics = file.read().splitlines()
    for i in range(len(extrinsics)):
        extrinsics[i] = [d for d in extrinsics[i].split(' ') if len(d) > 0]
        extrinsics[i] = [float(d) for d in extrinsics[i][1:]]
        extrinsics[i] = np.array(extrinsics[i]).reshape(4, 4)

    # Get metadata information
    metadata = read_json(f'{seq}/metadata')
    fps = metadata['fps']
    intrinsics = metadata['K']
    intrinsics = np.array(intrinsics).reshape(3, 3)
    intrinsics = np.transpose(intrinsics)

    ### Object name
    object_name = filename_rgbs[0].split('/')[4]

    ############ LOOP OVER CAMERAS
    for cam in cameras:
        dense = {label: dict() for label in dense_labels}

        ######## RGB FILENAMES
        for i, filename_rgb in enumerate(filename_rgbs):
            frame = frame_name(i)

            ######## RGB
            rgb = np.array(read_image(filename_rgb))
            dense['rgb'][frame] = rgb

            ######## LOWDIM RGB             
            filename_lowdim = add_key_to_dict(lowdim, f'{dst}/lowdim/{cam}/{frame}.npz')
            prepare_lowdim(lowdim, dst, cam, frame)

            ######## INTRINSICS + EXTRINSICS
            lowdim[filename_lowdim]['extrinsics'] = extrinsics[i]
            lowdim[filename_lowdim]['intrinsics'] = intrinsics

        ######## DEPTH FILENAMES
        for i, filename_depth in enumerate(filename_depths):
            frame = frame_name(i)

            ######## DEPTH
            depth = get_depth(filename_depth)
            dense['depth'][frame] = depth

        ######## MASK DEPTH FILENAMES
        for i, filename_mask_depth in enumerate(filename_mask_depths):
            obj, num, _, _ = filename_mask_depth.split('/')[-4:]
            frame = frame_name(i)

            ######## MASK DEPTH
            mask_depth = get_mask(filename_mask_depth)
            dense['mask_depth'][frame] = mask_depth

        ######## WRITE LABELS
        write_labels(dst, cam, args.storage, dense, labels, resolution, num_frames)

    ######## WRITE LOWDIM
    write_lowdim(args, dst, labels, num_frames, lowdim)

############ METADATA 
    filename = f'{dst}/metadata.json'
    seq_metadata = fill_metadata(
        args=args,
        info=dict(
            name='WildRGBD',
            tags=['real','static','inward','object'],
            raw_id=seq.replace(f'{args.src}/', ''),
        ),
        labels=labels,
        cameras=cameras,
        resolution=resolution,
        num_frames=num_frames,
        framerate=fps,
        rgb=dict(extension='jpg'),
        intrinsics=dict(model='pinhole'),
        extrinsics=dict(transform='cam2world',metric=False),
        depth=dict(extension='npz',metric=False,sparse=True),
        semantic=None,
        action=None,
        language=None,
        specific=dict(object=object_name),
    )
    write_json(filename, seq_metadata)

    return dst

#######################################################

if __name__ == '__main__':
    converter = os.path.basename(__file__)
    run(converter, get_sequences, parse_sequence, process_sequence)

#######################################################