Comments (9)
torch.device("cpu") or device=torch.device("cuda:0")
from yolo_tracking.
@thptai maybe you could be a contributor for this project,
if you modify the README with your solution and make a pull request!!
like below way
(e.g.)
import cv2
**import torch**
import numpy as np
from pathlib import Path
from boxmot import DeepOCSORT
tracker = DeepOCSORT(
model_weights=Path('osnet_x0_25_msmt17.pt'), # which ReID model to use
**device=torch.device('cuda:0'),**
fp16=False,
)
vid = cv2.VideoCapture(0)
...
Thank you for sharing your idea
hope you have a peaceful dayπ
from yolo_tracking.
I will fix this at tracker level instead. Thx for pointing this bug out!
from yolo_tracking.
Should have been fixed. Let me know @J4BEZ , @thptai, @programmeddeath1 if it works now
from yolo_tracking.
@mikel-brostrom Sorry for late reply and very appreciate for your hard workπββοΈ
In my case, I caught an error like below.
...
with open(ROOT / "pyproject.toml", "r") as file:
FileNotFoundError: [Errno 2] No such file or directory: 'D:\\J4BEZ\\Anaconda\\envs\\sample\\Lib\\site-packages\\pyproject.toml'
when I download poetry.lock and pyproject.toml to the root of my env where I install boxmot
(in this case, under D:\\J4BEZ\\Anaconda\\envs\\sample\\Lib\\site-packages\\
)
and run the sample code ,
it works perfectly as we expected!
from yolo_tracking.
In my case, I install boxmot not git clone https://github.com/mikel-brostrom/yolo_tracking.git
but pip install -U boxmot
.
so the poetry.lock and pyproject.toml which exist outside of 'boxmot' folder have left when I install boxmot
if we copy poetry.lock and pyproject.toml to boxmot folder and change the path in torch_utils.py line 66
with open(ROOT / "pyproject.toml", "r") as file:
We would be able to solve the issue!
Very appreciate for your hard work and hope you have a peaceful dayπ
from yolo_tracking.
I see. On it. I have a solution for it π
from yolo_tracking.
I was fetching the version from pyproject.toml
. Should be from __init__.py
under the boxmot
pkg folder. This is now fixed. Thanks for pointing this bug out as well π
from yolo_tracking.
the solution of @thptai would be the bestππ
another way, you(@programmeddeath1 ) can modify the line 18 of boxmot/appearance/backends/base_backend.py
from
self.cuda = torch.cuda.is_available() and self.device.type != "cpu"
to
self.cuda = torch.cuda.is_available() and self.device != "cpu"
but I recommend the solution of @thptai , that modify "code of Custom tracking examples",
because mine could be affect other.
from yolo_tracking.
Related Issues (20)
- Illegal instruction (core dumped) for BoTSORT HOT 4
- ModuleNotFoundError: No module named 'ultralytics.nn.modules.conv'; 'ultralytics.nn.modules' is not a package.
- frame count bug still exists HOT 1
- AttributeError: 'Segment' object has no attribute 'detect' HOT 2
- Question about the initialization of the process uncertainty matrix (`Q`) in `ocsort.py` HOT 2
- Tracking id for ByteTracker not being able to reset HOT 5
- Question on Color Conversion in DeepOCSort During Tracking HOT 1
- How to train custom Reid dataset from scratch on yolo_tracking? HOT 3
- Inquiry regarding liscence HOT 2
- How to get original frame without result augmentation when using yolo.track function?
- Add "reset()" method to all the trackers HOT 2
- Retrain ReID HOT 2
- Minimum number of hits quesiton HOT 2
- Question about Evaluation on First 10 Frames HOT 2
- How to increase the size of history_observations. HOT 2
- Why ReID improves HybridSORT performance HOT 4
- DiffMOT
- tracking of HybridSORT when moving to the next part of the video HOT 1
- MASA: Matching Anything By Segmenting Anything (CVPR24) HOT 3
- IndexError Occurs When max_age is Set Above 60 HOT 1
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