• Hardware Platform (Jetson / GPU) Jetson Xavier NX • DeepStream Version 5.0 • JetPack Version (valid for Jetson only) R32 Revision: 5.0 GCID: 25531747 Board: t186ref • TensorRT Version 7.1.3 + CUDA 10.2
• Issue Type( questions, new requirements, bugs) TrafficCamNet model doesn’t do a fantastic job recognizing slightly off angle image.
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing) please see below
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description) please see below
Hi Deepstream team,
Please see attached image for how the camera is located to take pics and run inference on.
If I am looking to rotate like 10-20 degrees, is there a way to do it before running the inference? Eventually, as I collect more images, I will run TLT to train the model with the images I want, but as I currently don’t have many images, I wanted to see if there was a way to simply feed in rotated image.
Isn’t this it? If you look at the above code, i named it nvvidconv (per other examples) but it is using Gst.ElementFactory.make("nvvideoconvert", "convertor")
I am just trying to double confirm that I am not messing anything up.
Also, if deepstream doesn’t have 10-20 degree rotation available, do you have a recommendation on running my setup? (As I mentioned previously, my goal is to use TLT when I have more images).
You’re right… Then you can try to load NvBufSurface data in a cv::Mat in READWRITE mode. This is something I already done successfully (based on dsexample), for drawing on the buffer. However I don’t known if it can become a performance bottleneck.