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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")
)
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