Please provide complete information as applicable to your setup.
**• Hardware Platform GPU
**• DeepStream Version-----> 6.1
**• TensorRT Version 8.4
**• NVIDIA GPU Driver Version → 525.
I’m working with Python (As a language )
what I want to do is suppose I have 3-4 full frame label detector, 1st (face), 2nd (fire,)3rd (headgear), 4th (back head) and I have couple of secondary classifier (on top of 1st )—> like AGE, Gender, Race,emotion etc.
Now what I’m doing is I’m testing with 1st face(detector),and fire(detector) and for face I unable secondary classifier (on top of face )—> AGE, Gender
that’s also mention in sgie config file work on gie-id and class id — as well.
Where I want to get information from Frame -------> everything is mix up
after frame_meta or obj_meta where and how I can segregate for others detector and detector with sgie
uri-decode-bin ----->streammux—>pgie1(face{full Frame})----->pgie2(fire{full Frame})------>pgie3(headgear{full Frame}) ----->pgie4(back_head{full Frame})—>sgie1(age{work on pgie1})----->sgie2(Gender{work on pgie1})------>sgie3(emotion{work on pgie1})------->sgie4(race{work on pgie1})–>videoconvert---->capsfilter----->filesink
Now I want to know about is my sequence is correct or not !
If yes then How I able to get information
else what would be the ideal pipeline and and How I able to get information
here Information means obj_meta, classifire_meta and alll…
Why do you want to use two primary data? As you said, you just have 1 model for primary gie. It has 4 labels. You can use different sgie to infer each label as the sample I attached.
I Have Two primary label detector --------> let’s consider as X,Y Both are independent , and I have 4 sgie model , 4 are dependent on X and No relation with Y !
I want to Fitch each primary model data (X,Y) As I mention Y only full label Detector It should contain till obj_meta
for X it should contained obj_meta and classifire_meta as well !
My first question If I use or my pipeline
src----> streammux—>X—>Y----->Sgie1(work on X)---->sgie2(work on X))-------> sgie3(work on X))—>
So you have 2 detect models, and 3 classifier models. Both the classifier models should link one of the 2 detect models. Is that correct?
So what is the use of another detect plugin? Could you describe a practical usage scenario?
Let me make the things a little breakdown
x-----> Face ,head (Detector)
y------> Fire (detector)
A------>age (classi)
B-----> Gender (classi)
c------>emotion(classi)
suppose In a office environment we need a fire detector if by any chance somewhere fire is there !
and as We need to count face or head in a frame and if face then We want to know what is age, gender,emotion and all !
What I want is fire should be a different detector and (Face,head) should be another detector !
I hope now I’m able to clarify more !
let me know any doubt
And How I can solve this means extract the Meta data let me know !