Jetson nano googlenet detect information

andy8902 · May 5, 2020, 7:34am

When I detect the object, the terminal displays object class rate(on the top picture). Screenshot from 2020-05-05 15-14-46 The imagenet.py is on bottom picture.Can I use the imagenet.py to change terminal’s inormation ? Screenshot from 2020-05-05 14-29-55

AastaLLL · May 5, 2020, 8:56am

Hi,

Not sure which source do you use.
But you can update the output from the source code like this:

github.com

dusty-nv/pytorch-classification/blob/master/train.py#L174


train_dataset = datasets.ImageFolder(
    traindir,
    transforms.Compose([
        #transforms.Resize(224),
        transforms.RandomResizedCrop(args.resolution),
        transforms.RandomHorizontalFlip(),
        transforms.ToTensor(),
        normalize,
    ]))


num_classes = len(train_dataset.classes)
print('=> dataset classes:  ' + str(num_classes) + ' ' + str(train_dataset.classes))


if args.distributed:
    train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
else:
    train_sampler = None


train_loader = torch.utils.data.DataLoader(
    train_dataset, batch_size=args.batch_size, shuffle=(train_sampler is None),
    num_workers=args.workers, pin_memory=True, sampler=train_sampler)

Thanks.

andy8902 · May 6, 2020, 3:05am

Tha labels are car,doormax,doormid, and doormin on googlenet.After training googlenet, I used googlenet to detect object. I make GPIO LED(https://www.jetsonhacks.com/2019/06/07/jetson-nano-gpio/) with dection.If doormin and doormid recognition rate are closely, I want two leds light togehter.

nadeemm · October 14, 2021, 10:01pm