yolov3
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
File Explorer
- bug-report.yml
- config.yml
- feature-request.yml
- question.yml
- ci-testing.yml
- cla.yml
- docker.yml
- format.yml
- links.yml
- merge-main-into-prs.yml
- stale.yml
- dependabot.yml
- hyp.no-augmentation.yaml
- hyp.Objects365.yaml
- hyp.scratch-high.yaml
- hyp.scratch-low.yaml
- hyp.scratch-med.yaml
- hyp.VOC.yaml
- bus.jpg
- zidane.jpg
- download_weights.sh
- get_coco.sh
- get_coco128.sh
- Argoverse.yaml
- coco.yaml
- coco128.yaml
- GlobalWheat2020.yaml
- Objects365.yaml
- SKU-110K.yaml
- VisDrone.yaml
- VOC.yaml
- xView.yaml
- __init__.py
- common.py
- experimental.py
- yolo.py
- yolov3-spp.yaml
- yolov3-tiny.yaml
- yolov3.yaml
- Dockerfile
- Dockerfile-arm64
- Dockerfile-cpu
- __init__.py
- clearml_utils.py
- hpo.py
- README.md
- __init__.py
- comet_utils.py
- hpo.py
- optimizer_config.json
- README.md
- __init__.py
- wandb_utils.py
- __init__.py
- __init__.py
- activations.py
- augmentations.py
- autoanchor.py
- autobatch.py
- callbacks.py
- dataloaders.py
- downloads.py
- general.py
- loss.py
- metrics.py
- plots.py
- torch_utils.py
- triton.py
- .dockerignore
- .gitignore
- AGENTS.md
- benchmarks.py
- CITATION.cff
- CLAUDE.md
- CONTRIBUTING.md
- detect.py
- export.py
- hubconf.py
- LICENSE
- pyproject.toml
- README.md
- README.zh-CN.md
- requirements.txt
- train.py
- tutorial.ipynb
- val.py
# Installation Guide
pythonSetup Steps
git clone https://github.com/ultralytics/yolov3
Clone the repository
cd yolov3
Navigate to the project directory
pip install -r requirements.txt
Install required packages
Key Commands
pip install -r requirements.txt
Install required python dependencies for the project.
python detect.py --weights yolov3.pt --source 0
Run object detection inference on various sources like images, videos, or webcams.
python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov3.yaml --batch-size 32
Train the YOLOv3 model using specified dataset and configuration.
python val.py --weights yolov3.pt --data coco.yaml
Evaluate the validation accuracy of the trained model.
python export.py --weights yolov3.pt --include onnx
Export the model to other formats like ONNX or TensorRT.
# Use via CDN
jsDelivrjsDelivr serves any public GitHub repository as a CDN with zero setup. Pick a version and a file to get a ready-to-paste link and snippet.
Command Glossary
Commands referenced in this DOCs, explained below.
git clone
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git clone
Clone an existing repository.
git clone {{remote_repository_location}} {{path/to/directory}}
Clone an existing repository into a new directory (the default directory is the repository name):
git clone --recursive {{remote_repository_location}}
Clone an existing repository and its submodules:
git clone {{[-n|--no-checkout]}} {{remote_repository_location}}
Clone only the `.git` directory of an existing repository:
pip install
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pip install
Install Python packages.
pip install {{package1 package2 ...}}
Install one or more packages:
pip install {{package1 package2 ...}} {{[-U|--upgrade]}}
Upgrade all specified packages to the latest version, installing any that are not already present:
pip install {{package}}=={{version}}
Install a specific version of a package:
python
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python
Python language interpreter.
python
Start a REPL (interactive shell):
python {{path/to/file.py}}
Execute a specific Python file:
python -i {{path/to/file.py}}
Execute a specific Python file and start a REPL:
