cyber-record 0.1.12
Cyber record offline parse tool
Requires Python: >=3.6

# cyber_record

[![Documentation Status](https://readthedocs.org/projects/cyber-record/badge/?version=latest)](https://cyber-record.readthedocs.io/en/latest/?badge=latest)

**[cyber_record](https://cyber-record.readthedocs.io/en/latest/)** is a cyber record file offline parse tool. You can use `cyber_record` to read messages from record file, or write messages to the record file.

## Quick start
First install "cyber_record" by the following command.
```sh
pip3 install cyber_record
// or update version
pip3 install cyber_record -U
```
#### python version
If protobuf prompt requires python>=3.7, you can install python3.7+ and switch default python version
```
sudo apt install python3.8
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 2
```
#### demo record
You can download a apollo demo record from [demo_sensor_data_for_vision](https://apollo-system.cdn.bcebos.com/dataset/6.0_edu/demo_sensor_data_for_vision.tar.xz)

## Command line mode
You can easily get the information in the record file by the following command.

#### Info
`cyber_record info` will output the statistics of the record file.

```shell
$ cyber_record info -f example.record.00000

record_file: example.record.00000
version:     1.0
begin_time:  2021-07-23 17:12:15.114944
end_time:    2021-07-23 17:12:15.253911
duration:    0.14 s
size:        477.55 KByte
message_number: 34
channel_number: 8

/apollo/planning                      , apollo.planning.ADCTrajectory         , 1
/apollo/routing_request               , apollo.routing.RoutingRequest         , 0
/apollo/monitor                       , apollo.common.monitor.MonitorMessage  , 0
/apollo/routing_response              , apollo.routing.RoutingResponse        , 0
/apollo/routing_response_history      , apollo.routing.RoutingResponse        , 1
/apollo/localization/pose             , apollo.localization.LocalizationEstimate, 15
/apollo/canbus/chassis                , apollo.canbus.Chassis                 , 15
/apollo/prediction                    , apollo.prediction.PredictionObstacles , 2
```

#### Echo
`cyber_record echo` will print the message of the specified topic to the terminal.

```shell
$ cyber_record echo -f example.record.00000 -t /apollo/canbus/chassis

engine_started: true
speed_mps: 0.0
throttle_percentage: 0.0
brake_percentage: 0.0
driving_mode: COMPLETE_AUTO_DRIVE
gear_location: GEAR_DRIVE
header {
  timestamp_sec: 1627031535.112813
  module_name: "SimControl"
  sequence_num: 76636
}
```


Or you can reference the `cyber_record` in the python file by
```python
from cyber_record.record import Record
```

#### recover
If you find record file is missing index, you can recover the file by `cyber_record recover`.

**It is best to backup the file before recover!!!**

1. Generate the file descriptor set. Must be executed in the `apollo` directory.
 - `descriptor_set_out` is the descriptor file name
 - `modules/drivers/proto/sensor_image.proto` the message define proto file
```
protoc --include_imports --descriptor_set_out=tmp modules/drivers/proto/sensor_image.proto
```

or you can use absolute path.
 - `descriptor_set_out` is the descriptor file name
 - `proto_path` the apollo home path
 - `/home/zero/01opencode/apollo/modules/drivers/proto/sensor_image.proto` proto file absolute path
```
protoc --include_imports --descriptor_set_out=tmp --proto_path=/home/zero/01opencode/apollo /home/zero/01opencode/apollo/modules/drivers/proto/sensor_image.proto
```

2. Recover the record file.
 - `broken.record` is the file need repair
 - `/apollo/sensor/camera/front_6mm/image` the topic of the need repair message
 - `tmp` the descriptor file generated in the previous step
 - `apollo.drivers.Image` the message type of the need repair message
```
cyber_record recover -f broken.record -t /apollo/sensor/camera/front_6mm/image -d tmp -m apollo.drivers.Image
```

## Examples
Below are some examples to help you read and write messages from record files.

## 1. Read messages
You can read messages directly from the record file in the following ways.
```python
from cyber_record.record import Record

file_name = "20210521122747.record.00000"
record = Record(file_name)
for topic, message, t in record.read_messages():
  print("{}, {}, {}".format(topic, type(message), t))
```

The following is the output log of the program
```
/apollo/localization/pose, <class 'LocalizationEstimate'>, 1627031535246897752
/apollo/canbus/chassis, <class 'Chassis'>, 1627031535246913234
/apollo/canbus/chassis, <class 'Chassis'>, 1627031535253680838
```

#### Filter Read
You can also read messages filtered by topics and time. This will improve the speed of parsing messages.
```python
def read_filter_by_both():
  record = Record(file_name)
  for topic, message, t in record.read_messages('/apollo/canbus/chassis', \
      start_time=1627031535164278940, end_time=1627031535215164773):
    print("{}, {}, {}".format(topic, type(message), t))
```


## 2. Parse messages
To avoid introducing too many dependencies, you can save messages by `record_msg`.
```
pip3 install record_msg -U
```

`record_msg` provides 3 types of interfaces

#### csv format
you can use `to_csv` to format objects so that they can be easily saved in csv format.
```python
f = open("message.csv", 'w')
writer = csv.writer(f)

def parse_pose(pose):
  '''
  save pose to csv file
  '''
  line = to_csv([pose.header.timestamp_sec, pose.pose])
  writer.writerow(line)

f.close()
```

#### image
you can use `ImageParser` to parse and save images.
```python
image_parser = ImageParser(output_path='../test')
for topic, message, t in record.read_messages():
  if topic == "/apollo/sensor/camera/front_6mm/image":
    image_parser.parse(message)
    # or use timestamp as image file name
    # image_parser.parse(image, t)
```

#### lidar
you can use `PointCloudParser` to parse and save pointclouds.
```python
pointcloud_parser = PointCloudParser('../test')
for topic, message, t in record.read_messages():
  if topic == "/apollo/sensor/lidar32/compensator/PointCloud2":
    pointcloud_parser.parse(message)
    # other modes, default is 'ascii'
    # pointcloud_parser.parse(message, mode='binary')
    # pointcloud_parser.parse(message, mode='binary_compressed')
```


## 3. Write messages
You can now also build record by messages. You can write pb_message by `record.write`.
```python
def write_message():
  pb_map = map_pb2.Map()
  pb_map.header.version = 'hello'.encode()

  with Record(write_file_name, mode='w') as record:
    record.write('/apollo/map', pb_map, int(time.time() * 1e9))
```

Its application scenario is to convert dataset into record files. Please note that it must be written in chronological order.


If you want to write raw message, you should first use `Builder` to help convert raw data to pb_message.

#### image
You can write image to record file like below. `ImageBuilder` will help you convert image to pb_image. `encoding` should be `rgb8`,`bgr8` or `gray`, `y`.
```python
def write_image():
  image_builder = ImageBuilder()
  write_file_name = "example_w.record.00002"
  with Record(write_file_name, mode='w') as record:
    img_path = 'test.jpg'
    pb_image = image_builder.build(img_path, encoding='rgb8')
    record.write('/apollo/sensor/camera/front_6mm/image',
                 pb_image,
                 int(time.time() * 1e9))
```

#### lidar
You can write image to record file like below. `PointCloudBuilder` will help you convert pcd file to pb_point_cloud.
```python
def write_point_cloud():
  point_cloud_builder = PointCloudBuilder()
  write_file_name = "example_w.record.00003"
  with Record(write_file_name, mode='w') as record:
    pcd_path = 'test.pcd'
    pb_point_cloud = point_cloud_builder.build(pcd_path)
    record.write('/apollo/sensor/lidar32/compensator/PointCloud2',
                 pb_point_cloud,
                 int(time.time() * 1e9))
```