Prepare Your Dataset for YOLO the Right Way
Project description
YoloPrep
YoloPrep is a lightweight Python toolkit to prepare your object detection dataset for training with YOLOv5, YOLOv8, or other YOLO-based frameworks.
Output Structure
images/
└── train/
├── image_001.jpg
├── image_002.jpg
labels/
└── train/
├── image_001.txt ← empty YOLO annotation
├── image_002.txt
Installation
pip install yoloprep
Example
from yoloprep.core import YoloImagePreparator
prep = YoloImagePreparator(
source_dir="raw_images",
image_out_dir="images/train",
label_out_dir="labels/train",
image_size=640
)
prep.extract_frames("video.mp4", every_n_frames=10)
prep.prepare()
Command Line
yoloprep --source raw_images --size 640
License
MIT License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
yoloprep-0.0.1.tar.gz
(3.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file yoloprep-0.0.1.tar.gz.
File metadata
- Download URL: yoloprep-0.0.1.tar.gz
- Upload date:
- Size: 3.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.22
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f988b729b0844d0aad46b53446a268daece454c376ce0b6b9b19ce9ee0b47f89
|
|
| MD5 |
d09ff654dbf31f1879f6afdf3c31d2cc
|
|
| BLAKE2b-256 |
fc945f1e9dbcbd2f63fad6d4d56cb6f1c6af10f04141365f0c7f9bbd822c21cf
|
File details
Details for the file yoloprep-0.0.1-py3-none-any.whl.
File metadata
- Download URL: yoloprep-0.0.1-py3-none-any.whl
- Upload date:
- Size: 4.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.22
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
24f4235d9144bff28f852c4c73d78286e2744dc4c7feb625c81d3f92ceb846ea
|
|
| MD5 |
b96b886a222ceebdaea31a20bfa18d51
|
|
| BLAKE2b-256 |
2a402737450b483af9a7b0716a1c31ce0a94aacdfb068cfc6a0be4d03483c2cd
|