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SensorData.py
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139 lines (112 loc) · 6.12 KB
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import os, struct
import numpy as np
import zlib
import imageio
import cv2
import png
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 ValueError(f"Unsupported compression type: {compression_type}")
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 ValueError(f"Unsupported compression type: {compression_type}")
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))).decode('utf-8')
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(f'exporting {len(self.frames)//frame_skip} depth frames to {output_path}')
for f in range(0, len(self.frames), frame_skip):
depth_data = self.frames[f].decompress_depth(self.depth_compression_type)
depth = np.frombuffer(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)
with open(os.path.join(output_path, str(f) + '.png'), 'wb') as fp: # write 16-bit
writer = png.Writer(width=depth.shape[1], height=depth.shape[0], bitdepth=16)
depth = depth.reshape(-1, depth.shape[1]).tolist()
writer.write(fp, 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(f'exporting {len(self.frames)//frame_skip} color frames to {output_path}')
for f in range(0, len(self.frames), frame_skip):
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)
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(f'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_poses_np(self, output_file, frame_skip=1):
"""
Exports all camera-to-world matrices into one NumPy array file.
Parameters:
- output_file: Path to the file where the array will be saved.
- frame_skip: Process every nth frame (default is 1, meaning every frame).
"""
poses = []
for f in range(0, len(self.frames), frame_skip):
poses.append(self.frames[f].camera_to_world)
poses_array = np.stack(poses) # shape: (num_frames, 4, 4)
np.save(output_file, poses_array)
print(f'Exported poses for {poses_array.shape[0]} frames to {output_file}')
def export_intrinsics(self, output_path):
if not os.path.exists(output_path):
os.makedirs(output_path)
print(f'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'))