I am thinking of making a new model with only three labels animal, person, and vehicleIs there any way within DeepStack to group animals and get confirmation on animal rather than on the name of the animal which is never correct in my case?
Correct.@Charles_CO I don't think there is a way to edit a model once it's run through training. It would take another full training session with snapshots identified as the object(s) you want to be detected. I could be wrong about that, but seriously doubt that I am.
I think that makes sense. Recognition is not perfect yet to reliably distinguish between different animals but if we can get it to the point where we can reliably separate animals, people and cars, that would make most users satisfied IMO. I think that is what most people probably look for anyway.I am thinking of making a new model with only three labels animal, person, and vehicle
I have a RTX3090 on another computer running AMD 5950x CPU. If I can figure out how to run training, maybe I can help with training lower priority/less important models.I am thinking of making a new model with only three labels animal, person, and vehicle
If you want to give it a try, you need to install CUDA & cuDNN and follow the Local Setup in the below link. I am using a RTX3060 ti for local training.I have a RTX3090 on another computer running AMD 5950x CPU. If I can figure out how to run training, maybe I can help with training lower priority/less important models.
Do you do your training on Linux or on Windows in Power Shell?If you want to give it a try, you need to install CUDA & cuDNN and follow the Local Setup in the below link. I am using a RTX3060 ti for local training.
GitHub - johnolafenwa/deepstack-trainer: Custom Object Detection Training for DeepStack
Custom Object Detection Training for DeepStack. Contribute to johnolafenwa/deepstack-trainer development by creating an account on GitHub.github.com
In Windows with pythonDo you do your training on Linux or on Windows in Power Shell?
if you would like to do this, or maybe give a link to the sample data so i could train my own set (P1000 + GTX 1080 ti) then i will happily make a "general light" with just person/vehicle/animal.I am thinking of making a new model with only three labels animal, person, and vehicle
@aadje93 the original DeepStack object model was trained using the COCO Dataset. You can use FiftyOne to download and filter out the labels you do not want. Most of my custom model I used the COCO datasetif you would like to do this, or maybe give a link to the sample data so i could train my own set (P1000 + GTX 1080 ti) then i will happily make a "general light" with just person/vehicle/animal.
As i dont need to know if it was a truck, car or bus that loaded my stuff. Just a vehicle is enough for ALPR cam
Better to run 30-40 images through a razor fast deepstack than 3-4 as it takes to long.
When you say use "sub stream", do you mean unchecking "Use main stream if available" in trigger settings?sub stream data on high
YesWhen you say use "sub stream", do you mean unchecking "Use main stream if available" in trigger settings?