Comments (12)
Hello, Yes. Try to use our demo scripts:
Line 213 in a720e04
Pass your YOLOX weights, exp files and video and it should work.
If you trained your network for more than one class use the multi-class tracker version: mc_demo.py.
Good luck!
from bot-sort.
Thanks for the reply,
I did this exactly, passed my weights to the -c argument, -f as my exp file, and video as my path argument, detector work correctly , but for some reason detection are being discarded and the final saved video has no visualized bboxes,
I am using mot17 S50weights also,
is there any logic in mc_demo that discard detections? So i can fix it?
Thanks in advance
from bot-sort.
May you provide more information?
Maybe you need to adjust the tracker thresholds, did you change the --new_track_thresh argument according to your network scores?
Did you check that the tracker gets the detections correctly?
Are you using demo.py or mc_demo.py? if you use the one class demo.py there is --aspect_ratio_thresh argument that filters vertical objects.
from bot-sort.
I am using mc_demo, okay will check the threshold, thanks
from bot-sort.
@AhmedKhaled945 Has this been resolved? I ask because I am about to use this repo but your answer might save me some headaches if you have a workaround or found a fix.
Thanks!
from bot-sort.
hi, i want to track multiclass when i pass this code, it still track only pedestrian. Any solution for this
python3 tools/mc_demo.py video --path v1.mp4 -f yolox/exps/example/mot/yolox_x_mix_det.py -c pretrained/bytetrack_x_mot17.pth.tar --with-reid --fuse-score --fp16 --fuse --save_result
from bot-sort.
Hi.
As you mentioned before, I passed my weights to the -c argument, -f as my exp file, and video path, also using mot17 S50weights.
And the final saved video has no visualized bboxes.
Can you tell me how you solved this problem? @AhmedKhaled945
(python3 tools/demo.py video --path test.mp4 -c /home/YOLOX_outputs/yolox_voc_s/latest_ckpt.pth -f yolox/exps/example/mot/yolox_voc_s.py --with-reid --fuse-score --fp16 --fuse --save_result)
When I print outputs of [outputs, img_info = predictor.inference(img_path, timer)] line 162 in demo.py,
"None" is printed.
I think I should change [class Predictor(object)] line 89 in demo.py as I changed -f exp file.
Is there any other advice for me? @NirAharon
Thank you.
from bot-sort.
Hi @jjjuurang, Did you try this code with your trained YOLOX? because if so, it is sound like compatibility issues between YOLOX versions.
from bot-sort.
@faziii0 did you change the Exp file self.num_classes from 1 and used trained multi-class YOLOX weights?
from bot-sort.
Hi @NirAharon I am also facing the same problem.
I am using the pretrained YOLOX tiny weight from the official YOLOX github repo model zoo and along with that I am also passing the corresponding YOLOX tiny exp file of yours and I have also change the number of classes to 80 since the original YOLOX model is trained on 80 classes however still I cannot visualise any detection box in the output video.
It will be really helpful if you can suggest any update
from bot-sort.
Has this issue already been resolved?
We want to use YOLOX for object detection and are having trouble detecting objects when using the custom model.
We have confirmed that object detection with the custom model has been successful, with an accuracy of approximately 70%.
It seems to be a problem before tracking.
Thanks in advance
from bot-sort.
same issue. has anyone resolved??
from bot-sort.
Related Issues (20)
- CL.EXE -Application Error
- Prediction from Kalman
- I cant understand something in ablation study
- Deployment Code
- Improvement of ECC
- Train with distributed mode_ multiple GPUs HOT 1
- Error: all query identities do not appear in gallery HOT 2
- reproducing demo but blank output
- No inf checks were recorded for this optimizer HOT 2
- Where is the option of Tracklet Interpolation ? HOT 1
- cv2.error: OpenCV(4.8.0) /io/opencv/modules/core/src/batch_distance.cpp:274: error: (-215:Assertion failed) type == src2.type() && src1.cols == src2.cols && (type == CV_32F || type == CV_8U) in function 'batchDistance'
- Warning with gmc.py, line 273, not enough matching point. HOT 1
- Has anyone tried to use DT-DETR or similar instead of YOLO in BoT-SORT? HOT 1
- About model training
- can yolov8 support?
- multi-camera-multi-object-detection with re-identification HOT 3
- How to train without Pre-trained Backbones like resnest50?
- Bug Report: duplicate STracks in the list tracker.removed_stracks
- MOT17 test results
- Small Object tracking
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from bot-sort.