I’m working with Jetson Inferences, and I need to locate the coaxial cables on a unit, but since it’s very small, I decided to label the area around it.
These are some examples of my dataset, in total there are 300 images with several labels in each one.
These are my training commands:
$ python3 train_ssd.py --dataset-type=voc --data=data/Coaxiales --model-dir=models/Coaxiales --batch-size=2 --num-workers=4 --epochs=200
$ python3 onnx_export.py --resolution=512 --model-dir=models/Coaxiales/
I am varying the threshold to observe the results from 0.2, 0.21, 0.22… to 0.4, and I do not obtain favorable results in any of them.
What modifications could I make to my training to achieve better results?
Is it possible to develop this project, given that the inspection unit is 100 x 60 cm and the coaxial cables have a diameter of 5 mm.
The Jetson stopped outputting a video signal. The LED lights up and I can see it through a host, but it doesn’t output a video signal. What happened to my Jetson?