This repository holds code that is intended to provide a Python interface to the Hesai JT128 hemispherical LiDAR.
- A C++17 compiler (like g++).
- cmake (version 3.14 or higher, e.g.,
sudo apt install cmake). - Python 3.12+ and pip (or uv).
- Git (for cloning the Hesai SDK).
- The Hesai SDK's system dependencies:
libpcap-dev,libssl-dev(e.g.,sudo apt install libpcap-dev libssl-dev).
python3 -m venv .venv
source .venv/bin/activateThe build process is now fully automated. Simply run:
pip install .This will:
- Read pyproject.toml
- Use scikit-build to run CMakeLists.txt.
- CMake will find pybind11, the SDK headers, and the SDK libraries.
- It will compile pybind_hesai_sdk.cpp and link it against all the .a and .so files.
- It will create a Python module file (e.g., pyhesai_wrapper_cpp.cpython-310-x86_64-linux-gnu.so) and install it into your Python environment.
- If the build is successful, the pyhesai_wrapper module is now installed and available to all Python scripts in your environment.
Both Left and Right Lidars:
from pyhesai_wrapper import stream_lidar_left_right
for left, right in stream_lidar_left_right():
if left is not None:
print(f"Points shape: {left.points.shape}, timestamp: {left.timestamp}")
if right is not None:
print(f"Points shape: {right.points.shape}, timestamp: {right.timestamp}")Left Lidar:
from pyhesai_wrapper import stream_lidar_left
for frame in stream_lidar_left():
if frame is not None:
print(f"Points shape: {frame.points.shape}, timestamp: {frame.timestamp}")Right Lidar:
from pyhesai_wrapper import stream_lidar_right
for frame in stream_lidar_right():
if frame is not None:
print(f"Points shape: {frame.points.shape}, timestamp: {frame.timestamp}")Alternatively, you can poll the next frame using next():
left, right = stream_lidar_left_right()
left_frame = next(left)
right_frame = next(right)When you fetch points using lidar.get_next() or via the streaming generators, the system returns a LidarPointCloudFrame object (or None if no new data is available yet). The properties of this object are:
points: A NumPy array of shape(N, 3)containing the X, Y, and Z Cartesian coordinates of the captured points (dtype=float32).intensity: A NumPy 1D array of shape(N,)containing the return intensity values (dtype=uint8).timestamp: A NumPy 1D array of shape(N,)containing the microsecond tick timestamps for each point (dtype=float64).confidence: A NumPy 1D array of shape(N,)containing the confidence values (dtype=uint8).ring: A NumPy 1D array of shape(N,)containing the laser ring IDs (dtype=uint16).
-
Edit
pyhesai_wrapper/config.yamlto configure your lidar settings:- Update
device_ip_addressto match your lidar's IP (default:192.168.1.201) - Update
correction_file_pathto point to your lidar's correction file - Optionally update other parameters like
udp_port,ptc_port, etc.
- Update
-
Make sure your machine is on the same network as the lidar.
-
Run the script:
stretch_lidar_show stretch_lidar_show --cluster_high_intensity stretch_lidar_show --left stretch_lidar_show --right
Note: You can cluster and display the Euclidean distance to high intensity points by passing the
--cluster_high_intensityflag -
You should see point cloud data streaming from the lidar. Press Ctrl-C to stop.
- Edit
pyhesai_wrapper/config.yamlto configure your lidar settings:- Update
device_ip_addressto match your lidar's IP (default:192.168.1.201) - Update
ptc_portto match your lidar's PTC port (default:9347)
- Update
- Make sure your machine is on the same network as the lidar.
- Run the script:
or
REx_hesai_download_calibration --left
REx_hesai_download_calibration --right
- You should see calibration data being downloaded from the lidar to the
$HELLO_FLEET_PATH/$HELLO_FLEET_ID/calibration_hesaisdirectory.
SDK-backed JT128 PTC client for return mode, point-cloud filter, PTP lock offset, diagnostics, and reachability checks.
from pyhesai_wrapper.ptc_client import (
FILTER_STRONG,
FILTER_STRONGEST,
POINT_CLOUD_MODE_MAPPING,
get_point_cloud_config,
get_point_cloud_mode,
get_return_mode,
is_new_firmware_supported,
set_filter_type,
set_point_cloud_mode,
set_return_mode,
get_ptp_lock_offset_us,
ptc_reachable,
)
ip = '192.168.1.201'
if ptc_reachable(ip):
print(get_return_mode(ip))
set_return_mode(ip, 2)
set_filter_type(ip, FILTER_STRONG) # ultra_precise unchanged
print(get_point_cloud_config(ip))
# Strongest filter (3) and POINT_CLOUD_MODE need FW
# 15.AF.B0.00.02.Y / 1.b.0028 / 2.b.0692
if is_new_firmware_supported(ip):
set_filter_type(ip, FILTER_STRONGEST)
set_point_cloud_mode(ip, POINT_CLOUD_MODE_MAPPING) # 0 general, 1 mapping, 2 mapping+ground
print(get_point_cloud_mode(ip))Noise filter levels: 0 disabled, 1 medium, 2 strong, 3 strongest (new FW only).
is_new_firmware_supported() is the single firmware gate used by Strongest filter and POINT_CLOUD_MODE. Per Hesai, it requires all three inventory patches at or above 15.AF.B0.00.02.Y / 1.b.0028 / 2.b.0692 (wrapper fields hardware_version, software_version, fpga_version). When a newer mass-production firmware ships, re-check Hesai’s version naming (especially if APP moves past …02.Z / to …03.X) and update that function.
To view complete lidar information, return mode, spin rate, PTP status, and point cloud settings:
# Show config/status for both lidars
REx_hesai_show_config
# Show config/status for a specific lidar
REx_hesai_show_config --left
REx_hesai_show_config --rightThis retrieves the serial number, model, hardware and software versions, build ID, MAC address, whether new-FW features are supported, return mode, spin rate, lock offset, ultra-precise mode, noise filter type, point-cloud mode (when supported), PTP status, and active PTP master offset (if PTP is synchronized).
Warning
Modifying the LiDAR hardware configuration can disrupt the normal operation of your robot. Be cautious when using this utility.
An interactive tool to adjust hardware settings on a specific lidar:
# Configure left lidar
REx_hesai_set_config --left
# Configure right lidar
REx_hesai_set_config --rightAfter accepting the warning, you can select from the interactive options:
- 10 - Set Return Mode (0 to 5)
- 11 - Set Spin Speed (600 or 1200 RPM)
- 12 - Set PTP Lock Offset (1 to 1000 us)
- 13 - Set Noise Filter Type (0 to 3;
3/ strongest requires new FW) - 14 - Set Point Cloud Mode (0 to 2; requires new FW)
Each setting operation performs a baseline GET, followed by the SET command, and finishes with a readback verification GET to guarantee that the hardware successfully applied the modification.
Warning
Do not power off the lidar during upgrade. The unit reboots after a successful transfer. Upgrade one lidar at a time.
Uploads a Hesai-provided JT128 firmware patch via PTC Upgrade Safe Image (0x83) and prints transfer progress. The firmware file is not shipped in this repo; obtain it from Hesai.
# Right lidar (interactive confirm)
REx_hesai_upgrade_firmware --right --firmware /path/to/JT128_upgrade.patch
# Left lidar, skip confirm prompt
REx_hesai_upgrade_firmware --left --firmware /path/to/JT128_upgrade.patch -y
# Explicit IP
REx_hesai_upgrade_firmware 192.168.1.201 --firmware /path/to/JT128_upgrade.patchOptional flags: --timeout (PTC connect timeout, default 30s), --reboot-wait (wait for lidar to return after transfer, default 120s), -y / --yes (skip confirmation).
The tool prints inventory versions before upload, streams Progress: xx.x%, waits for reboot, then prints versions again.
The version after upgrade might not show all the version
Versions after upgrade:
[after]
Hardware Version: 15.AF.B0.00.02.Y0
Software/Firmware: 1.b.0028
FPGA Version:
Build/Signature ID: 0x00000000
You can run REx_hesai_show_config and check the inventory info
INVENTORY INFO
------------------------------------------------------------------
Model: JT128
Serial Number: JT3AC9509338CB50
MAC Address: ec:9f:0d:02:f1:cd
Calibration/Mfg Date: 2025-03-05
Hardware Version: 15.AF.B0.00.02.Y0
Software/Firmware: 1.b.0028
FPGA Version: 2.b.0692
Build/Signature ID: 0x791C2330
New FW Features: supported
You can run the standalone PTC test menu directly:
python3 test/ptc_test.py --left