tteepe / tracktacular Goto Github PK

Than you for sharing your great work and implementation!
I have some quenstions.
How to decide zmax in bounds, Z in resolution and z_sign in data yml file?
(e.g., bounds: [0, 1000, 0, 640, 0, **2**] , z_sign: **-1** in d_multiviewx.yml)

Hi,
Thanks for this great work. I have tried to use pre-train model but get very low performance. Would you please help me to find out where I made mistake.

I ran with this command.
python world_track.py test -c model_weights/wild_segnet/config.yaml
--ckpt model_weights/wild_segnet/model-epoch=21-val_loss=7.79-val_center=4.76.ckpt

And got this values:
IDF1 IDP IDR Rcll Prcn GT MT PT ML FP FN IDs FM MOTA MOTP IDt IDa IDm
0 1.2% 31.6% 0.6% 0.6% 31.6% 41 0 0 41 13 946 0 0 -0.7% 0.566 0 0 0
OVERALL 1.2% 31.6% 0.6% 0.6% 31.6% 41 0 0 41 13 946 0 0 -0.7% 0.566 0 0 0
Testing DataLoader 0: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40/40 [00:30<00:00, 1.30it/s]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ DataLoader 0 ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ detect/moda │ 0.0 │
│ detect/modp │ 34.748539923465074 │
│ detect/precision │ 4.545454545454546 │
│ detect/recall │ 0.20491803278688525 │
│ track/idf1 │ 1.2358393669128418 │
│ track/idp │ 31.578947067260742 │
│ track/idr │ 0.6302521228790283 │
│ track/mostly_lost │ 1.0 │
│ track/mostly_tracked │ 0.0 │
│ track/mota │ -0.7352941036224365 │
│ track/motp │ 43.35531234741211 │
│ track/num_ascend │ 0.0 │
│ track/num_false_positives │ 13.0 │
│ track/num_fragmentations │ 0.0 │
│ track/num_migrate │ 0.0 │
│ track/num_misses │ 946.0 │
│ track/num_switches │ 0.0 │
│ track/num_transfer │ 0.0 │
│ track/num_unique_objects │ 41.0 │
│ track/partially_tracked │ 0.0 │
│ track/precision │ 31.578947067260742 │
│ track/recall │ 0.6302521228790283 │
└───────────────────────────┴───────────────────────────┘

Hi, do you have pre-tramined model/weight available?

Thank you for your work and contributions to the field.

I am evaluating the model but I am getting the following error:
dt_dets = dt[np.logical_and(dt[:, 0] == seq, dt[:, 1] == frame)][:, (2, 8, 9)]
IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed
Testing DataLoader 0: 100%|██████████| 40/40 [00:12<00:00, 3.23it/s]

I appreciate your assistances
Best regards,

I have trained MultiviewX and Wildtrack data , run test command success , but I can not run predict command success...

Thanks for sharing your work,
i have a question regarding the split of the dataset:

• in 'PedestrianDataModule' you have:

      if stage == 'fit':
        self.data_train = PedestrianDataset(
            base,
            is_train=True,
            resolution=self.resolution,
            bounds=self.bounds,
        )
  
    if stage == 'fit' or stage == 'validate':
        self.data_val = PedestrianDataset(
            base,
            is_train=False,
            resolution=self.resolution,
            bounds=self.bounds,
        )
  
    if stage == 'test':
        self.data_test = PedestrianDataset(
            base,
            is_train=False,
            resolution=self.resolution,
            bounds=self.bounds
        )
  
    if stage == 'predict':
        self.data_predict = PedestrianDataset(
            base,
            is_train=False,
            resolution=self.resolution,
            bounds=self.bounds,
        )`
  

dose this means that the test and validation data are the same?