import os, struct
import numpy as np
import zlib
import imageio
import cv2

COMPRESSION_TYPE_COLOR = {-1: 'unknown', 0: 'raw', 1: 'png', 2: 'jpeg'}
COMPRESSION_TYPE_DEPTH = {-1: 'unknown', 0: 'raw_ushort', 1: 'zlib_ushort', 2: 'occi_ushort'}


class RGBDFrame():

    def load(self, file_handle):
        self.camera_to_world = np.asarray(struct.unpack('f' * 16, file_handle.read(16 * 4)), dtype=np.float32).reshape(
            4, 4)
        self.timestamp_color = struct.unpack('Q', file_handle.read(8))[0]
        self.timestamp_depth = struct.unpack('Q', file_handle.read(8))[0]
        self.color_size_bytes = struct.unpack('Q', file_handle.read(8))[0]
        self.depth_size_bytes = struct.unpack('Q', file_handle.read(8))[0]
        self.color_data = b''.join(struct.unpack('c' * self.color_size_bytes, file_handle.read(self.color_size_bytes)))
        self.depth_data = b''.join(struct.unpack('c' * self.depth_size_bytes, file_handle.read(self.depth_size_bytes)))

    def decompress_depth(self, compression_type):
        if compression_type == 'zlib_ushort':
            return self.decompress_depth_zlib()
        else:
            raise

    def decompress_depth_zlib(self):
        return zlib.decompress(self.depth_data)

    def decompress_color(self, compression_type):
        if compression_type == 'jpeg':
            return self.decompress_color_jpeg()
        else:
            raise

    def decompress_color_jpeg(self):
        return imageio.imread(self.color_data)


class SensorData:
    def __init__(self, filename):
        self.version = 4
        self.load(filename)

    def load(self, filename):
        with open(filename, 'rb') as f:
            version = struct.unpack('I', f.read(4))[0]
            assert self.version == version
            strlen = struct.unpack('Q', f.read(8))[0]
            self.sensor_name = b''.join(struct.unpack('c' * strlen, f.read(strlen)))
            self.intrinsic_color = np.asarray(struct.unpack('f' * 16, f.read(16 * 4)), dtype=np.float32).reshape(4, 4)
            self.extrinsic_color = np.asarray(struct.unpack('f' * 16, f.read(16 * 4)), dtype=np.float32).reshape(4, 4)
            self.intrinsic_depth = np.asarray(struct.unpack('f' * 16, f.read(16 * 4)), dtype=np.float32).reshape(4, 4)
            self.extrinsic_depth = np.asarray(struct.unpack('f' * 16, f.read(16 * 4)), dtype=np.float32).reshape(4, 4)
            self.color_compression_type = COMPRESSION_TYPE_COLOR[struct.unpack('i', f.read(4))[0]]
            self.depth_compression_type = COMPRESSION_TYPE_DEPTH[struct.unpack('i', f.read(4))[0]]
            self.color_width = struct.unpack('I', f.read(4))[0]
            self.color_height = struct.unpack('I', f.read(4))[0]
            self.depth_width = struct.unpack('I', f.read(4))[0]
            self.depth_height = struct.unpack('I', f.read(4))[0]
            self.depth_shift = struct.unpack('f', f.read(4))[0]
            num_frames = struct.unpack('Q', f.read(8))[0]
            self.frames = []
            for i in range(num_frames):
                frame = RGBDFrame()
                frame.load(f)
                self.frames.append(frame)

    def export_depth_images(self, output_path, image_size=None, frame_skip=1):
        if not os.path.exists(output_path):
            os.makedirs(output_path)
        print('exporting', len(self.frames) // frame_skip, ' depth frames to', output_path)
        for f in range(0, len(self.frames), frame_skip):
            if os.path.exists((os.path.join(output_path, str(f) + '.png'))):
                continue
            if f % 100 == 0:
                print('exporting', f, 'th depth frames to', os.path.join(output_path, str(f) + '.png'))

            depth_data = self.frames[f].decompress_depth(self.depth_compression_type)
            depth = np.fromstring(depth_data, dtype=np.uint16).reshape(self.depth_height, self.depth_width)
            if image_size is not None:
                depth = cv2.resize(depth, (image_size[1], image_size[0]), interpolation=cv2.INTER_NEAREST)
            imageio.imwrite(os.path.join(output_path, str(f) + '.png'), depth)

    def export_color_images(self, output_path, image_size=None, frame_skip=1):
        if not os.path.exists(output_path):
            os.makedirs(output_path)
        print('exporting', len(self.frames) // frame_skip, 'color frames to', output_path)
        for f in range(0, len(self.frames), frame_skip):
            if os.path.exists((os.path.join(output_path, str(f) + '.png'))):
                continue
            if f % 100 == 0:
                print('exporting', f, 'th color frames to', os.path.join(output_path, str(f) + '.png'))
            color = self.frames[f].decompress_color(self.color_compression_type)
            if image_size is not None:
                color = cv2.resize(color, (image_size[1], image_size[0]), interpolation=cv2.INTER_NEAREST)
            # imageio.imwrite(os.path.join(output_path, str(f) + '.jpg'), color)
            imageio.imwrite(os.path.join(output_path, str(f) + '.png'), color)

    def save_mat_to_file(self, matrix, filename):
        with open(filename, 'w') as f:
            for line in matrix:
                np.savetxt(f, line[np.newaxis], fmt='%f')

    def export_poses(self, output_path, frame_skip=1):
        if not os.path.exists(output_path):
            os.makedirs(output_path)
        print('exporting', len(self.frames) // frame_skip, 'camera poses to', output_path)
        for f in range(0, len(self.frames), frame_skip):
            self.save_mat_to_file(self.frames[f].camera_to_world, os.path.join(output_path, str(f) + '.txt'))

    def export_intrinsics(self, output_path):
        if not os.path.exists(output_path):
            os.makedirs(output_path)
        print('exporting camera intrinsics to', output_path)
        self.save_mat_to_file(self.intrinsic_color, os.path.join(output_path, 'intrinsic_color.txt'))
        self.save_mat_to_file(self.extrinsic_color, os.path.join(output_path, 'extrinsic_color.txt'))
        self.save_mat_to_file(self.intrinsic_depth, os.path.join(output_path, 'intrinsic_depth.txt'))
        self.save_mat_to_file(self.extrinsic_depth, os.path.join(output_path, 'extrinsic_depth.txt'))