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YOLO-CROWD is a lightweight crowd counting and face detection model that is based on Yolov5s and can run on edge devices, as well as fixing the problems of face occlusion, varying face scales, and other challenges of crowd counting

License: MIT License

Dockerfile 0.02% Jupyter Notebook 97.67% Shell 0.08% Python 2.23%

yolo-crowd's Introduction

πŸ‘‹ Hi there, I'm Mustapha Merabet!

πŸ˜„ About Me:

Typing animation showing my roles and certifications

  • 🌱 Hello, I'm Zaki, a State Engineer in Computer Systems Engineering, currently student in Machine Learning for Data Science at Paris CitΓ© University.
  • πŸ”­ I've a passion for technology and innovation, and always exploring the exciting realms of AI, Data Science, Dev.
  • πŸ’Ό Currently diving deep into the world of Data Science, AI, exploring its endless possibilities.
  • πŸ€” Fascinated by Data Science and its power to unveil insights from complex datasets.
  • ⚑ Tech at heart, with a keen interest in Dev practices for efficient software development.
  • πŸŽ“ I hold a Comuter Systems Engineering degree from ESI-SBA.

I'm State Engineer in Computer Systems Engineering graduated from Higher School of Computer Science and a current student in Machine Learning for Data Science at Paris CitΓ© University. With a passion for technology and innovation, I'm always exploring the exciting realms of AI, Data Science, Dev.

Languages and Tools:

python java pytorch tensorflow azure c cplusplus css3 dart docker express figma firebase flask flutter git hadoop html5 illustrator javascript linux matlab mongodb mssql mysql nodejs opencv oracle pandas photoshop php postgresql postman laravel scikit_learn seaborn sqlite arduino

πŸ’¬ Let's Connect & Collaborate

Whether it's AI, Data Science, Dev or just a tech enthusiast chat, I'm always open to engaging conversations and collaborations! πŸ˜„

yolo-crowd's People

Contributors

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yolo-crowd's Issues

Inconsistent Prediction

image 3/3 /YOLO-CROWD/../p2pnet/crowd_counting/test3.jpg: 
torch.Size([1, 3, 304, 640]) # resize by yolo code 
Traceback (most recent call last):
  File "detect.py", line 282, in <module>
    detect()
  File "detect.py", line 103, in detect
    pred = model(img, augment=opt.augment)[0]
  File "/home/casxm/anaconda3/envs/prod_env2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/casxm/albert/YOLO-CROWD/models/yolo.py", line 124, in forward
    return self.forward_once(x, profile, visualize)  # single-scale inference, train
  File "/home/casxm/albert/YOLO-CROWD/models/yolo.py", line 140, in forward_once
    x = m(x)  # run
  File "/home/casxm/anaconda3/envs/prod_env2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/xxxx/YOLO-CROWD/models/common.py", line 714, in forward
    return torch.cat(x, self.d)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 20 but got size 19 for tensor number 1 in the list.

The error appears when I detect some images from the Internet. So far I haven't located the bug. I'll continue dig into this issue. If you know anything about this, please let me now.

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