How to setting the different labels.txt while using two models in the same program

user6348 · November 18, 2021, 2:31am

Environment

TensorRT Version :
8.0.1
CUDA Version :
10.2
Operating System + Version :
Jetson NX (jetpack 4.6)

I want to use the detection and number recognition from this repo (GitHub - winter2897/Real-time-Auto-License-Plate-Recognition-with-Jetson-Nano: This repository provides you with a detailed guide on how to build a real-time license plate detection and recognition system. The source code of the repository implemented on Jetson Nano reached 40 FPS.) in same program, however I have no idea on setting 2 different class_labels since there cannot find the argument setting about labels in the code but need to set in command line like

python3 detectnet-img.py --model=./networks/az_plate/az_plate_ssdmobilenetv1.onnx --class_labels=./networks/az_plate/labels.txt --input_blob=input_0 --output_cvg=scores --output_bbox=boxes --overlay=none images/car.jpg out.jpg

Any idea on this?

Also how to set 2 different models, since the --model can only be set in command line not in code…

AastaLLL · November 18, 2021, 8:23am

Hi,

Have you checked this with the repository owner?

It looks like the sample only supports a single detection model.
But you can add it easily by modifying the source below:

github.com

winter2897/Real-time-Auto-License-Plate-Recognition-with-Jetson-Nano/blob/main/detectnet-camera.py#L63


      
          # create video sources & outputs
          input = jetson.utils.videoSource(opt.input_URI, argv=sys.argv)
          output = jetson.utils.videoOutput(opt.output_URI, argv=sys.argv+is_headless)
          
          
# process frames until the user exits
          while True:
          	# capture the next image
          	img = input.Capture()
          
          
	# detect objects in the image (with overlay)
          	detections = net.Detect(img, overlay=opt.overlay)
          
          
	# print the detections
          	print("detected {:d} objects in image".format(len(detections)))
          
          
	for detection in detections:
          		print(detection)
          
          
	# render the image
          	output.Render(img)

Thanks.

user6348 · November 18, 2021, 3:19pm

I am confusing that why I set --network=./network/az_plate/az_plate/az_plate_ssdmobilenetv1.onnx will get differenct detection result from setting --model=./network/az_plate/az_plate/az_plate_ssdmobilenetv1.onnx?

system · December 8, 2021, 6:54am

This topic was automatically closed 14 days after the last reply. New replies are no longer allowed.