SIXray Yolov10

This is a project using SIXray dataset to build up security image recognition for some common danger goods: Gun, Knife, Wrench, Pliers, and Scissors.

This repo is targeted to compare the YOLOv10 method with the original and YOLOv4 method in the dimensions of detect precision, training parameters and also optimisers.

Building Commands

• Build Environment with Conda

1. Install anaconda
2. Create environment

conda create -n yolov10 python==3.10 --strict-channel-priority -c conda-forge -y
conda activate yolov10

• Set VScode Terminal with conda

In settings.json

"terminal.integrated.profiles.windows": {
    "PowerShell": {
        "path": "C:\\Windows\\System32\\WindowsPowerShell\\v1.0\\powershell.exe"
    },
    "Anaconda Prompt": {
        "path": "C:\\Windows\\System32\\cmd.exe",
        "args": ["/K", "C:\\Users\\你的使用者名稱\\Anaconda3\\Scripts\\activate.bat"]
    }
},
"terminal.integrated.defaultProfile.windows": "Anaconda Prompt"

• Clone This Repo

git clone https://github.com/Annie04082020/SIXray_YOLOv10.git

• Clone YOLOv10 inside of this repo

cd SIXray_YOLOv10
git clone https://github.com/THU-MIG/yolov10.git

• Install requirements

cd yolov10
pip install -r requirements.txt
pip install -e .
cd ..
pip install -r requirements.txt

• Start Training

set KMP_DUPLICATE_LIB_OK=TRUE
python train.py

• If needed to install different cuda in env:

pip uninstall torch torchvision torchaudio -y
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

Validation

python
>>> import torch
>>> print(torch.cuda.is_available())
# Expected Output：True

• Can't import ultralytics: (from YOLOv10)

cd yolov10
pip install -r requirements.txt
pip install -e .