# Copyright 2026 Toyota Research Institute.  All rights reserved.

import os
import cv2
import numpy as np

from glob import glob

from anydata.utils.read import read_image, read_depth
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_sequences(args):
    seqs = glob(f'{args.src}/sync/*')
    return seqs


def parse_sequence(seq, args):
    return parse_dst_seq(seq, args, remove=[0])

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

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']

    ### Get filenames
    filename_rgbs = sorted(glob(f'{seq}/*.jpg'))
    filename_depths = sorted(glob(f'{seq}/*.png'))

    # Get intrinsics
    fx_rgb = 5.1885790117450188e+02
    fy_rgb = 5.1946961112127485e+02
    cx_rgb = 3.2558244941119034e+02
    cy_rgb = 2.5373616633400465e+02
    intrinsics = np.array([
        [fx_rgb,    0.0, cx_rgb],
        [   0.0, fy_rgb, cy_rgb],
        [   0.0,    0.0,    1.0],
    ])

    ############ 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).resize((640, 480)))
            dense['rgb'][frame] = rgb

            ######## LOWDIM RGB             
            prepare_lowdim(lowdim, dst, cam, frame)

            ######## INTRINSICS
            filename_lowdim = add_key_to_dict(lowdim, f'{dst}/lowdim/{cam}/{frame}.npz')
            lowdim[filename_lowdim]['intrinsics'] = intrinsics

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

            ######## DEPTH
            depth = read_depth(filename_depth, div=1000)
            dense['depth'][frame] = 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='NYUv2',
            tags=['real','static','indoor','image'],
            raw_id=seq.replace(f'{args.src}/', ''),
        ),
        labels=labels,
        cameras=cameras,
        resolution=resolution,
        num_frames=num_frames,
        framerate=0,
        rgb=dict(extension='jpg'),
        intrinsics=dict(model='pinhole'),
        extrinsics=None,
        depth=dict(extension='npz',metric=True,sparse=True),
        semantic=None,
        action=None,
        language=None,
        specific=None,
    )
    write_json(filename, seq_metadata)

    return dst

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

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

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