<b>[primary-gie]</b>
enable=1
gpu-id=0
#model-engine-file=model_b1_fp32.engine
labelfile-path=label.txt
batch-size=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
gie-unique-id=1
nvbuf-memory-type=0
config-file=config1.txt
<b>[secondary-gie0]</b>
enable=1
gpu-id=0
#model-engine-file=model_b1_fp32.engine
labelfile-path=label.txt
batch-size=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
gie-unique-id=2
operate-on-gie-id=1
nvbuf-memory-type=0
config-file=config2.txt
I am planning to detect cars and draw a bounding box around it via yolov3 tiny. then I will be detecting plates (and draw bounding boxes around them) inside the detected cars in the previous classifier. Ultimately I will be recognizing characters inside the detected plates. as you can imagine, I need an approach in which I will be cascading different Yolo samples, drawing bounding boxes (of plate location) inside othe bounding boxes (of car locations). is deepstream flexible enough to help me do that without having to modify the cp libraries, or I can do this only via changing the high level config.txt files?
Hey Chris.
So I am using two object detectors. The first detects people and the second detects faces.
I set my pipeline like this: persondetector → facedetector → nvtracker.
However, the tracker seems to override the Face Label to Person.
I need to Detect People and run a classifier on them. I also need to detect their faces and classify their age and gender. I have all the models ready but can’t seem to plug them properly due to the aforementioned issue.
How do I go about this?