The Traffic Sign Classification sample demonstrates how to use the NVIDIA® proprietary SignNet deep neural network (DNN) to perform traffic sign classification. It outputs the class of the traffic signs from images captured by the ego car.
SignNet currently supports RCB images. RGBA images are not supported. SignNet models currently cover three geographical regions. For one of such regions, the United States (US), one model is provided: US_V2
and US_V4
. For another supported region, the European Union (EU), there are also two available models: EU_V3
and EU_V4
. For the last supported region, Japan, there is only one supported model - JP_V1
. The main difference between different model versions for the EU and US regions is in the number of supported classes. Models version 2 for each region have significantly more traffic sign classes covered than version 1 models.
The default model for the sample app is US_V2
for the US. In order to use the European traffic sign models, the Japan model, or to use the US model version 4, one would need to explicitly select it with a corresponding command line parameter when running the sample.
This sample shows a simple implementation of traffic sign classification built around the NVIDIA SignNet DNN. The classification is done by first detecting the traffic signs with the help of NVidia DriveNet DNN and then classification of found image-crops with the help of SignNet DNN. There is no tracking of traffic signs applied, so one may notice some flickering of detections. For more information on the SignNet DNN and how to customize it for your applications, consult your NVIDIA sales or business representative.
The image datasets used to train SignNet have been captured by a View Sekonix Camera Module (SF3325) with AR0231 RCCB sensor. The camera is mounted on a rig on top of the vehicle. Demo videos are captured at 2.3 MP and downsampled to 960 x 604. Eight cameras were used to collect the data for training the provided SignNet models. The following list shows the setup position and field of view (FOV) of each such camera:
To achieve the best traffic sign detection performance, NVIDIA recommends to adopt a camera setup similar to one or more cameras from the list above and align the video center vertically with the horizon before recording new videos.
Even though the SignNet DNN was trained with data from cameras setup pointing in various direction of the sensor rig (see the list above), it is recommeded to use it for the following directional and FOV setup::
The command line for the sample is:
./sample_sign_classifier --rig=[path/to/rig/file] --liveCam=[0|1]
where
--rig=[path/to/rig/file] Rig file containing all information about vehicle sensors and calibration. Default value with video: path/to/data/samples/waitcondition/rig.json Default value with live camera: path/to/data/samples/waitcondition/live_cam_rig.json --liveCam=[0|1] Use live camera or video file. Takes no effect on x86. Need to be set to 1 if passing in a rig with live camera setup. To switch the mode, pass `--liveCam=0/1` as the argument. Default value: 0
./sample_sign_classifier
./sample_sign_classifier --model=EU_V2
./sample_sign_classifier --liveCam=1
The sample creates a window, displays a video, and overlays bounding boxes for detected traffic signs. The class of the sign is displayed with the text label above the bounding box.
The following table describes the models provided as part of the package. Follow the hyperlinks to the the full list of classes supported by each model.
MODEL NAME | MODEL IDENTIFIER | SUPPORTED REGION | # OF MODEL'S OUTPUTS | # OF DISTINCT CLASS LABELS | DESCRIPTION |
---|---|---|---|---|---|
SignNet US v2.0 | US_V2 | United States of America | 312 | 273 | Advanced USA model with expanded sign coverage. |
TrafficSign_US_v4 | US_V4 | United States of America | 312 | 273 | Advanced USA model with expanded sign coverage and HWISP support. |
signnet_EU_v3_0 | EU_V3 | European Union | 242 | 232 | Advanced EU model with expanded sign coverage. |
TrafficSign_EU_v4 | EU_V4 | European Union | 242 | 232 | Advanced EU model with expanded sign coverage and HWISP. |
SignNet JP v1.0 | JP_V1 | Japan | 184 | 151 | Japan sign model. |
Note, the EU SignNet models may be appropriate to classify road signs from other non-EU countries that follow Vienna convention.
For more information, see SignNet.