Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU): Jetson Nano
• DeepStream Version: 5.0 GA
• JetPack Version (valid for Jetson only): 4.4
Hello everyone, I am writing this topic because I have a series of doubts regarding the results I am having with a deepstream application. The application in which I work contemplates the use of nvinfer + nvtracker + nvdsanalytics. The video source is IP cameras (RTSP).
The configuration of the cameras is as follows:
- Codec H.265
- FPS: 21
- Bit Rate: 2048
- Bit Rate Type: VBR
- Resolution: 1920x1080
The deepstream application in general is configured as follows:
- Model: resnet10 (resnet10.caffemodel_b2_gpu0_fp16.engine)
- Pgie interval: 4
- streammux: 1920x1080, livesource = 1
- nvtracker: NvDCF with default configuration file
Here you can see the application working on a demo video file:
Here instead, it is seen in real operation in an apparently less complex video sequence:
*If someone wants to see the video file at higher resolution, they can request it
I do not know if I am correct, but my impression is that there is a decrease in the accuracy of the detection. Also I think that the malfunction of nvinfer causes a malfunction in nvtracker, since the detected object is lost quickly. This raises the following doubts:
- Do you think it is a problem with the location of the camera? If so, is there a document with recommendations in this regard? (distances, angles, etc)
- Do you have information regarding the images with which the resnet10 model was trained? for peoplenet there is information about it.
- Are there nvinfer or nvtracker configuration parameters that must be adjusted depending on the scene and allow to improve this performance?
- Is there a problem that I am not noticing?