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6748ade | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 | # Yolov7 with ByteTrack
1. Clone repo.
```
git clone https://github.com/axcelerateai/yolov7-bytetrack-streamlit.git
cd yolov7-bytetrack-streamlit
```
2. Install requirements.
### Pip
```
python3 -m venv .env
source .env/bin/activate
```
```
pip install Cython numpy
```
```
pip install -r requirements.txt
```
- [Note]: `cython_bbox` have no windows distribution on pypi. If you're a windows user then run following command to install `cython_bbox` from source.
```
# for windows
pip install -e git+https://github.com/samson-wang/cython_bbox.git#egg=cython-bbox
# for linux
pip install cython-bbox
```
### conda
```
conda env create -f environment.yml
```
```
conda activate yolov7_bytetrack
```
- [Note]: `cython_bbox` have no windows distribution on pypi. If you're a windows user then run following command to install `cython_bbox` from source.
```
# for windows
pip install -e git+https://github.com/samson-wang/cython_bbox.git#egg=cython-bbox
# for linux
pip install cython-bbox
```
3. Download weights.
```
python download_weights.py
```
4. Run stremlit server
```
streamlit run yolov7-tiny-demo.py --server.port [LPORT]
```
- `LPORT` = Local port of system
### Test yolov7-tiny
- To run Yolov7-Tiny
```
streamlit run yolov7-tiny-demo.py --server.port 2085
```
### Test yolov7
```
streamlit run yolov7-demo.py --server.port 2085
```
### Test yolor
```
streamlit run yolor-demo.py --server.port 2085
```
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