Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (14.6%) to scientific vocabulary
Last synced: 6 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: LShang12
- License: agpl-3.0
- Language: Python
- Default Branch: main
- Size: 48.8 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Created 8 months ago
· Last pushed 8 months ago
Metadata Files
Readme
Contributing
License
Citation
README.md
WSADet: A Wavelet Scale-Aware UAV Object Detector for Complex Conditions
Documentation
See below for a quickstart install and usage examples, and see our Docs for full documentation on training, validation, prediction and deployment.
Install
Pip install the Ultralytics package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [](https://pypi.org/project/ultralytics/) [](https://www.pepy.tech/projects/ultralytics) [](https://pypi.org/project/ultralytics/) ```bash pip install ultralytics pip install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 --index-url https://download.pytorch.org/whl/cu118 pip install -r requirements.txt pip install -e . ``` For alternative installation methods including [Conda](https://anaconda.org/conda-forge/ultralytics), [Docker](https://hub.docker.com/r/ultralytics/ultralytics), and Git, please refer to the [Quickstart Guide](https://docs.ultralytics.com/quickstart/). [](https://anaconda.org/conda-forge/ultralytics) [](https://hub.docker.com/r/ultralytics/ultralytics) [](https://hub.docker.com/r/ultralytics/ultralytics)Usage
### CLI YOLO may be used directly in the Command Line Interface (CLI) with a `yolo` command: ```bash yolo predict model=yolo11n.pt source='https://ultralytics.com/images/bus.jpg' ``` `yolo` can be used for a variety of tasks and modes and accepts additional arguments, e.g. `imgsz=640`. See the YOLO [CLI Docs](https://docs.ultralytics.com/usage/cli/) for examples. ### Python YOLO may also be used directly in a Python environment, and accepts the same [arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI example above: ```python from ultralytics import YOLO # Load a model model = YOLO("yolo11n.pt") # Train the model train_results = model.train( data="coco8.yaml", # path to dataset YAML epochs=100, # number of training epochs imgsz=640, # training image size device="cpu", # device to run on, i.e. device=0 or device=0,1,2,3 or device=cpu ) # Evaluate model performance on the validation set metrics = model.val() # Perform object detection on an image results = model("path/to/image.jpg") results[0].show() # Export the model to ONNX format path = model.export(format="onnx") # return path to exported model ``` See YOLO [Python Docs](https://docs.ultralytics.com/usage/python/) for more examples.Dataset
You can use your own dataset.
File structure
``` Your dataset ├── ... ├── images | ├── train | | ├── 1.jpg | | ├── 2.jpg | | └── ... | ├── val | | ├── 1.jpg | | ├── 2.jpg | | └── ... └── labels ├── train | ├── 1.txt | ├── 2.txt | └── ... └── val ├── 100.txt ├── 101.txt └── ... ```Citation
Acknowledgement
Part of the code is adapted from previous works: YOLOv11. We thank all the authors for their contributions.
Owner
- Login: LShang12
- Kind: user
- Repositories: 1
- Profile: https://github.com/LShang12
Citation (CITATION.cff)
# This CITATION.cff file was generated with https://bit.ly/cffinit
cff-version: 1.2.0
title: Ultralytics YOLO
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Glenn
family-names: Jocher
affiliation: Ultralytics
orcid: 'https://orcid.org/0000-0001-5950-6979'
- family-names: Qiu
given-names: Jing
affiliation: Ultralytics
orcid: 'https://orcid.org/0000-0003-3783-7069'
- given-names: Ayush
family-names: Chaurasia
affiliation: Ultralytics
orcid: 'https://orcid.org/0000-0002-7603-6750'
repository-code: 'https://github.com/ultralytics/ultralytics'
url: 'https://ultralytics.com'
license: AGPL-3.0
version: 8.0.0
date-released: '2023-01-10'
GitHub Events
Total
- Issue comment event: 7
- Push event: 1
- Pull request event: 3
- Create event: 5
Last Year
- Issue comment event: 7
- Push event: 1
- Pull request event: 3
- Create event: 5
Dependencies
pyproject.toml
pypi
- matplotlib >=3.3.0
- numpy <2.0.0; sys_platform == 'darwin'
- numpy >=1.23.0
- opencv-python >=4.6.0
- pandas >=1.1.4
- pillow >=7.1.2
- psutil *
- py-cpuinfo *
- pyyaml >=5.3.1
- requests >=2.23.0
- scipy >=1.4.1
- seaborn >=0.11.0
- torch >=1.8.0
- torch >=1.8.0,!=2.4.0; sys_platform == 'win32'
- torchvision >=0.9.0
- tqdm >=4.64.0
- ultralytics-thop >=2.0.0