HaozheQi / P2B

P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds
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About Testing #9

Open AmingWu opened 4 years ago

AmingWu commented 4 years ago

Where are the testing results? QQ截图20200617142630

HaozheQi commented 4 years ago

Hi, @AmingWu, actually 'succ/prec' in the picture is the result, but there may be something wrong about your result. The true result is about 56.2/72.8. you may need to check the input settings of the code. 84863038-d4d4d880-b0a6-11ea-8cae-81d331738505

AmingWu commented 4 years ago

I find the testing data does not include label_02. The label_02 is only for training. Is it correct?

AmingWu commented 4 years ago

QQ截图20200628125037

AmingWu commented 4 years ago

data_tracking_label_2 only contains the training data. And it does not contain the test data.

HaozheQi commented 4 years ago

Yes, the KITTI tracking dataset only gives the label of training set. So we only used its training set to train and test our P2B, which was split as follows: scenes 0-16 for training, 17-18 for validation, and 19-20 for testing.

AmingWu commented 4 years ago

QQ截图20200628185028 I retrain the code. However, I still could not reproduce your results.

AmingWu commented 4 years ago

I use the default settings of your code.

HaozheQi commented 4 years ago

The result 6.1/3.9 indicates the tracker can not give a right prediction at all, I think there may still exist some errors in your code. Can you get a right result with the model I trained?

AmingWu commented 4 years ago

QQ截图20200629070221 This is the training process. Is it correct?

AmingWu commented 4 years ago

QQ截图20200629141709 The training is right?

HaozheQi commented 4 years ago

The output of your terminal seems to be correct. I'm not sure why your test result is wrong.

AmingWu commented 4 years ago

I use the default settings. And I do not modify the code. The dataset is correct. But, I do not reproduce your result.

AmingWu commented 4 years ago

Could you share your trained model?

HaozheQi commented 4 years ago

The model trained for car is already included in this repository, and I'm working on the release of other categories.

AmingWu commented 4 years ago

OK, I have test your model. I find the result is still wrong.

HaozheQi commented 4 years ago

You may check the code related to the test stage, I think your training stage has no error now.

AmingWu commented 4 years ago

dataset_Test = SiameseTest( input_size=1024, path='/home/room/wam/P2B/trackingdata/testing', split='Test', category_name='Car', offset_BB=0, scale_BB=1.25)

I only modify the path from opt.data_dir to '/home/room/wam/P2B/trackingdata/testing',

HaozheQi commented 4 years ago

The path of training and test should be the same, does this matter?

AmingWu commented 4 years ago

Thank you very much. I have reproduced your results. The path of training and test should be the same.

AmingWu commented 4 years ago

If I want to run other categories, I only need to modify parser.add_argument('--category_name', type=str, default = 'Car', help='Object to Track (Car/Pedetrian/Van/Cyclist)')?

zhanghm1995 commented 4 years ago

@AmingWu @HaozheQi, Hello, I wonder how did you final solve this problem, I run the following scripts:

python test_tracking.py --data_dir=/mnt/study/Datasets/KITTI/tracking/training

And also got the result like yours:

Test 1: Time 0.030s (it:0.031s) Data:0.409s (it:0.518s), Succ/Prec:6.6/4.4: 100%

And I used the KITTI training data and the default offline netR_36.pth model file.

zjtgit commented 3 years ago

@AmingWu @HaozheQi, Hello, I wonder how did you final solve this problem, I run the following scripts:

python test_tracking.py --data_dir=/mnt/study/Datasets/KITTI/tracking/training

And also got the result like yours:

Test 1: Time 0.030s (it:0.031s) Data:0.409s (it:0.518s), Succ/Prec:6.6/4.4: 100%

And I used the KITTI training data and the default offline netR_36.pth model file.

I run the test script in pycharm, and I got the same result as yours. I am sure the data which I used to test is KITTI training sequence, but it's still give me a wrong result.

Test 1: Time 0.037s (it:0.041s) Data:0.436s (it:0.493s), Succ/Prec:6.6/4.4: 100%|██████████| 6424/6424 [03:56<00:00, 27.15it/s]