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") )