# Copyright (c) 2023, ETH Zurich and UNC Chapel Hill.
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# Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

import argparse
import collections
import os
import struct

import numpy as np

CameraModel = collections.namedtuple('CameraModel',
                                     ['model_id', 'model_name', 'num_params'])
Camera = collections.namedtuple('Camera',
                                ['id', 'model', 'width', 'height', 'params'])
BaseImage = collections.namedtuple(
    'Image', ['id', 'qvec', 'tvec', 'camera_id', 'name', 'xys', 'point3D_ids'])
Point3D = collections.namedtuple(
    'Point3D', ['id', 'xyz', 'rgb', 'error', 'image_ids', 'point2D_idxs'])


class Image(BaseImage):

    def qvec2rotmat(self):
        return qvec2rotmat(self.qvec)


CAMERA_MODELS = {
    CameraModel(model_id=0, model_name='SIMPLE_PINHOLE', num_params=3),
    CameraModel(model_id=1, model_name='PINHOLE', num_params=4),
    CameraModel(model_id=2, model_name='SIMPLE_RADIAL', num_params=4),
    CameraModel(model_id=3, model_name='RADIAL', num_params=5),
    CameraModel(model_id=4, model_name='OPENCV', num_params=8),
    CameraModel(model_id=5, model_name='OPENCV_FISHEYE', num_params=8),
    CameraModel(model_id=6, model_name='FULL_OPENCV', num_params=12),
    CameraModel(model_id=7, model_name='FOV', num_params=5),
    CameraModel(model_id=8, model_name='SIMPLE_RADIAL_FISHEYE', num_params=4),
    CameraModel(model_id=9, model_name='RADIAL_FISHEYE', num_params=5),
    CameraModel(model_id=10, model_name='THIN_PRISM_FISHEYE', num_params=12)
}
CAMERA_MODEL_IDS = dict([(camera_model.model_id, camera_model)
                         for camera_model in CAMERA_MODELS])
CAMERA_MODEL_NAMES = dict([(camera_model.model_name, camera_model)
                           for camera_model in CAMERA_MODELS])


def read_next_bytes(fid,
                    num_bytes,
                    format_char_sequence,
                    endian_character='<'):
    """Read and unpack the next bytes from a binary file.
    :param fid:
    :param num_bytes: Sum of combination of {2, 4, 8}, e.g. 2, 6, 16, 30, etc.
    :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}.
    :param endian_character: Any of {@, =, <, >, !}
    :return: Tuple of read and unpacked values.
    """
    data = fid.read(num_bytes)
    return struct.unpack(endian_character + format_char_sequence, data)


def write_next_bytes(fid, data, format_char_sequence, endian_character='<'):
    """pack and write to a binary file.
    :param fid:
    :param data: data to send, if multiple elements are sent at the same time,
    they should be encapsuled either in a list or a tuple
    :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}.
    should be the same length as the data list or tuple
    :param endian_character: Any of {@, =, <, >, !}
    """
    if isinstance(data, (list, tuple)):
        bytes = struct.pack(endian_character + format_char_sequence, *data)
    else:
        bytes = struct.pack(endian_character + format_char_sequence, data)
    fid.write(bytes)


def read_cameras_text(path):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::WriteCamerasText(const std::string& path)
        void Reconstruction::ReadCamerasText(const std::string& path)
    """
    cameras = {}
    with open(path, 'r') as fid:
        while True:
            line = fid.readline()
            if not line:
                break
            line = line.strip()
            if len(line) > 0 and line[0] != '#':
                elems = line.split()
                camera_id = int(elems[0])
                model = elems[1]
                width = int(elems[2])
                height = int(elems[3])
                params = np.array(tuple(map(float, elems[4:])))
                cameras[camera_id] = Camera(
                    id=camera_id,
                    model=model,
                    width=width,
                    height=height,
                    params=params)
    return cameras


def read_cameras_binary(path_to_model_file):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::WriteCamerasBinary(const std::string& path)
        void Reconstruction::ReadCamerasBinary(const std::string& path)
    """
    cameras = {}
    with open(path_to_model_file, 'rb') as fid:
        num_cameras = read_next_bytes(fid, 8, 'Q')[0]
        for _ in range(num_cameras):
            camera_properties = read_next_bytes(
                fid, num_bytes=24, format_char_sequence='iiQQ')
            camera_id = camera_properties[0]
            model_id = camera_properties[1]
            model_name = CAMERA_MODEL_IDS[camera_properties[1]].model_name
            width = camera_properties[2]
            height = camera_properties[3]
            num_params = CAMERA_MODEL_IDS[model_id].num_params
            params = read_next_bytes(
                fid,
                num_bytes=8 * num_params,
                format_char_sequence='d' * num_params)
            cameras[camera_id] = Camera(
                id=camera_id,
                model=model_name,
                width=width,
                height=height,
                params=np.array(params))
        assert len(cameras) == num_cameras
    return cameras


def write_cameras_text(cameras, path):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::WriteCamerasText(const std::string& path)
        void Reconstruction::ReadCamerasText(const std::string& path)
    """
    HEADER = '# Camera list with one line of data per camera:\n' + \
             '#   CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]\n' + \
             '# Number of cameras: {}\n'.format(len(cameras))
    with open(path, 'w') as fid:
        fid.write(HEADER)
        for _, cam in cameras.items():
            to_write = [cam.id, cam.model, cam.width, cam.height, *cam.params]
            line = ' '.join([str(elem) for elem in to_write])
            fid.write(line + '\n')


def write_cameras_binary(cameras, path_to_model_file):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::WriteCamerasBinary(const std::string& path)
        void Reconstruction::ReadCamerasBinary(const std::string& path)
    """
    with open(path_to_model_file, 'wb') as fid:
        write_next_bytes(fid, len(cameras), 'Q')
        for _, cam in cameras.items():
            model_id = CAMERA_MODEL_NAMES[cam.model].model_id
            camera_properties = [cam.id, model_id, cam.width, cam.height]
            write_next_bytes(fid, camera_properties, 'iiQQ')
            for p in cam.params:
                write_next_bytes(fid, float(p), 'd')
    return cameras


def read_images_text(path):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadImagesText(const std::string& path)
        void Reconstruction::WriteImagesText(const std::string& path)
    """
    images = {}
    with open(path, 'r') as fid:
        while True:
            line = fid.readline()
            if not line:
                break
            line = line.strip()
            if len(line) > 0 and line[0] != '#':
                elems = line.split()
                image_id = int(elems[0])
                qvec = np.array(tuple(map(float, elems[1:5])))
                tvec = np.array(tuple(map(float, elems[5:8])))
                camera_id = int(elems[8])
                image_name = elems[9]
                elems = fid.readline().split()
                xys = np.column_stack([
                    tuple(map(float, elems[0::3])),
                    tuple(map(float, elems[1::3]))
                ])
                point3D_ids = np.array(tuple(map(int, elems[2::3])))
                images[image_id] = Image(
                    id=image_id,
                    qvec=qvec,
                    tvec=tvec,
                    camera_id=camera_id,
                    name=image_name,
                    xys=xys,
                    point3D_ids=point3D_ids)
    return images


def read_images_binary(path_to_model_file):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadImagesBinary(const std::string& path)
        void Reconstruction::WriteImagesBinary(const std::string& path)
    """
    images = {}
    with open(path_to_model_file, 'rb') as fid:
        num_reg_images = read_next_bytes(fid, 8, 'Q')[0]
        for _ in range(num_reg_images):
            binary_image_properties = read_next_bytes(
                fid, num_bytes=64, format_char_sequence='idddddddi')
            image_id = binary_image_properties[0]
            qvec = np.array(binary_image_properties[1:5])
            tvec = np.array(binary_image_properties[5:8])
            camera_id = binary_image_properties[8]
            image_name = ''
            current_char = read_next_bytes(fid, 1, 'c')[0]
            while current_char != b'\x00':  # look for the ASCII 0 entry
                image_name += current_char.decode('utf-8')
                current_char = read_next_bytes(fid, 1, 'c')[0]
            num_points2D = read_next_bytes(
                fid, num_bytes=8, format_char_sequence='Q')[0]
            x_y_id_s = read_next_bytes(
                fid,
                num_bytes=24 * num_points2D,
                format_char_sequence='ddq' * num_points2D)
            xys = np.column_stack([
                tuple(map(float, x_y_id_s[0::3])),
                tuple(map(float, x_y_id_s[1::3]))
            ])
            point3D_ids = np.array(tuple(map(int, x_y_id_s[2::3])))
            images[image_id] = Image(
                id=image_id,
                qvec=qvec,
                tvec=tvec,
                camera_id=camera_id,
                name=image_name,
                xys=xys,
                point3D_ids=point3D_ids)
    return images


def write_images_text(images, path):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadImagesText(const std::string& path)
        void Reconstruction::WriteImagesText(const std::string& path)
    """
    if len(images) == 0:
        mean_observations = 0
    else:
        mean_observations = sum(
            (len(img.point3D_ids) for _, img in images.items())) / len(images)
    HEADER = '# Image list with two lines of data per image:\n' + \
             '#   IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME\n' + \
             '#   POINTS2D[] as (X, Y, POINT3D_ID)\n' + \
             '# Number of images: {}, mean observations per image: {}\n'.format(len(images), mean_observations)

    with open(path, 'w') as fid:
        fid.write(HEADER)
        for _, img in images.items():
            image_header = [
                img.id, *img.qvec, *img.tvec, img.camera_id, img.name
            ]
            first_line = ' '.join(map(str, image_header))
            fid.write(first_line + '\n')

            points_strings = []
            for xy, point3D_id in zip(img.xys, img.point3D_ids):
                points_strings.append(' '.join(map(str, [*xy, point3D_id])))
            fid.write(' '.join(points_strings) + '\n')


def write_images_binary(images, path_to_model_file):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadImagesBinary(const std::string& path)
        void Reconstruction::WriteImagesBinary(const std::string& path)
    """
    with open(path_to_model_file, 'wb') as fid:
        write_next_bytes(fid, len(images), 'Q')
        for _, img in images.items():
            write_next_bytes(fid, img.id, 'i')
            write_next_bytes(fid, img.qvec.tolist(), 'dddd')
            write_next_bytes(fid, img.tvec.tolist(), 'ddd')
            write_next_bytes(fid, img.camera_id, 'i')
            for char in img.name:
                write_next_bytes(fid, char.encode('utf-8'), 'c')
            write_next_bytes(fid, b'\x00', 'c')
            write_next_bytes(fid, len(img.point3D_ids), 'Q')
            for xy, p3d_id in zip(img.xys, img.point3D_ids):
                write_next_bytes(fid, [*xy, p3d_id], 'ddq')


def read_points3D_text(path):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadPoints3DText(const std::string& path)
        void Reconstruction::WritePoints3DText(const std::string& path)
    """
    points3D = {}
    with open(path, 'r') as fid:
        while True:
            line = fid.readline()
            if not line:
                break
            line = line.strip()
            if len(line) > 0 and line[0] != '#':
                elems = line.split()
                point3D_id = int(elems[0])
                xyz = np.array(tuple(map(float, elems[1:4])))
                rgb = np.array(tuple(map(int, elems[4:7])))
                error = float(elems[7])
                image_ids = np.array(tuple(map(int, elems[8::2])))
                point2D_idxs = np.array(tuple(map(int, elems[9::2])))
                points3D[point3D_id] = Point3D(
                    id=point3D_id,
                    xyz=xyz,
                    rgb=rgb,
                    error=error,
                    image_ids=image_ids,
                    point2D_idxs=point2D_idxs)
    return points3D


def read_points3D_binary(path_to_model_file):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadPoints3DBinary(const std::string& path)
        void Reconstruction::WritePoints3DBinary(const std::string& path)
    """
    points3D = {}
    with open(path_to_model_file, 'rb') as fid:
        num_points = read_next_bytes(fid, 8, 'Q')[0]
        for _ in range(num_points):
            binary_point_line_properties = read_next_bytes(
                fid, num_bytes=43, format_char_sequence='QdddBBBd')
            point3D_id = binary_point_line_properties[0]
            xyz = np.array(binary_point_line_properties[1:4])
            rgb = np.array(binary_point_line_properties[4:7])
            error = np.array(binary_point_line_properties[7])
            track_length = read_next_bytes(
                fid, num_bytes=8, format_char_sequence='Q')[0]
            track_elems = read_next_bytes(
                fid,
                num_bytes=8 * track_length,
                format_char_sequence='ii' * track_length)
            image_ids = np.array(tuple(map(int, track_elems[0::2])))
            point2D_idxs = np.array(tuple(map(int, track_elems[1::2])))
            points3D[point3D_id] = Point3D(
                id=point3D_id,
                xyz=xyz,
                rgb=rgb,
                error=error,
                image_ids=image_ids,
                point2D_idxs=point2D_idxs)
    return points3D


def write_points3D_text(points3D, path):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadPoints3DText(const std::string& path)
        void Reconstruction::WritePoints3DText(const std::string& path)
    """
    if len(points3D) == 0:
        mean_track_length = 0
    else:
        mean_track_length = sum(
            (len(pt.image_ids) for _, pt in points3D.items())) / len(points3D)
    HEADER = '# 3D point list with one line of data per point:\n' + \
             '#   POINT3D_ID, X, Y, Z, R, G, B, ERROR, TRACK[] as (IMAGE_ID, POINT2D_IDX)\n' + \
             '# Number of points: {}, mean track length: {}\n'.format(len(points3D), mean_track_length)

    with open(path, 'w') as fid:
        fid.write(HEADER)
        for _, pt in points3D.items():
            point_header = [pt.id, *pt.xyz, *pt.rgb, pt.error]
            fid.write(' '.join(map(str, point_header)) + ' ')
            track_strings = []
            for image_id, point2D in zip(pt.image_ids, pt.point2D_idxs):
                track_strings.append(' '.join(map(str, [image_id, point2D])))
            fid.write(' '.join(track_strings) + '\n')


def write_points3D_binary(points3D, path_to_model_file):
    """
    see: src/base/reconstruction.cc
        void Reconstruction::ReadPoints3DBinary(const std::string& path)
        void Reconstruction::WritePoints3DBinary(const std::string& path)
    """
    with open(path_to_model_file, 'wb') as fid:
        write_next_bytes(fid, len(points3D), 'Q')
        for _, pt in points3D.items():
            write_next_bytes(fid, pt.id, 'Q')
            write_next_bytes(fid, pt.xyz.tolist(), 'ddd')
            write_next_bytes(fid, pt.rgb.tolist(), 'BBB')
            write_next_bytes(fid, pt.error, 'd')
            track_length = pt.image_ids.shape[0]
            write_next_bytes(fid, track_length, 'Q')
            for image_id, point2D_id in zip(pt.image_ids, pt.point2D_idxs):
                write_next_bytes(fid, [image_id, point2D_id], 'ii')


def detect_model_format(path, ext):
    if os.path.isfile(os.path.join(path, 'cameras' + ext)) and \
       os.path.isfile(os.path.join(path, 'images' + ext)) and \
       os.path.isfile(os.path.join(path, 'points3D' + ext)):
        print("Detected model format: '" + ext + "'")
        return True

    return False


def read_model(path, ext=''):
    # try to detect the extension automatically
    if ext == '':
        if detect_model_format(path, '.bin'):
            ext = '.bin'
        elif detect_model_format(path, '.txt'):
            ext = '.txt'
        else:
            print("Provide model format: '.bin' or '.txt'")
            return

    if ext == '.txt':
        cameras = read_cameras_text(os.path.join(path, 'cameras' + ext))
        images = read_images_text(os.path.join(path, 'images' + ext))
        points3D = read_points3D_text(os.path.join(path, 'points3D') + ext)
    else:
        cameras = read_cameras_binary(os.path.join(path, 'cameras' + ext))
        images = read_images_binary(os.path.join(path, 'images' + ext))
        points3D = read_points3D_binary(os.path.join(path, 'points3D') + ext)
    return cameras, images, points3D


def write_model(cameras, images, points3D, path, ext='.bin'):
    if ext == '.txt':
        write_cameras_text(cameras, os.path.join(path, 'cameras' + ext))
        write_images_text(images, os.path.join(path, 'images' + ext))
        write_points3D_text(points3D, os.path.join(path, 'points3D') + ext)
    else:
        write_cameras_binary(cameras, os.path.join(path, 'cameras' + ext))
        write_images_binary(images, os.path.join(path, 'images' + ext))
        write_points3D_binary(points3D, os.path.join(path, 'points3D') + ext)
    return cameras, images, points3D


def qvec2rotmat(qvec):
    array_10 = 1 - 2 * qvec[2]**2 - 2 * qvec[3]**2
    array_11 = 2 * qvec[1] * qvec[2] - 2 * qvec[0] * qvec[3]
    array_12 = 2 * qvec[3] * qvec[1] + 2 * qvec[0] * qvec[2]
    array_1 = [array_10, array_11, array_12]
    array_20 = 2 * qvec[1] * qvec[2] + 2 * qvec[0] * qvec[3]
    array_21 = 1 - 2 * qvec[1]**2 - 2 * qvec[3]**2
    array_22 = 2 * qvec[2] * qvec[3] - 2 * qvec[0] * qvec[1]
    array_2 = [array_20, array_21, array_22]
    array_30 = 2 * qvec[3] * qvec[1] - 2 * qvec[0] * qvec[2]
    array_31 = 2 * qvec[2] * qvec[3] + 2 * qvec[0] * qvec[1]
    array_32 = 1 - 2 * qvec[1]**2 - 2 * qvec[2]**2
    array_3 = [array_30, array_31, array_32]

    return np.array([array_1, array_2, array_3])