PP-YOLOE
PP-YOLOE is an anchor-free object detector with detection training and class-head resizing.
- Tasks
- detection
- Sizes
- s, m, l, x at 640 px
- Install
pip install libreyolo- Support tier
- Supported, since v1.6.0. Supporting trainables: kept green in CI, features land opportunistically.
- Licenses
- Code MIT, weights No separate artifact grant recorded. Commercial use
Install
pip install "libreyolo"Predict
from libreyolo import LibreYOLO, SAMPLE_IMAGE model = LibreYOLO("LibrePPYOLOEs.pt", device="cpu")result = model(SAMPLE_IMAGE)print(result.boxes)Released weights download from the source CDN with a pinned SHA-256 check. The constructor also accepts a local upstream checkpoint. The four sizes are s, m, l and x.
Train
Training uses ATSS assignment before switching to task-aligned assignment. static_assigner_epochs defaults to 30% of the requested epochs. A new class count rebuilds the class-prediction layers. AMP defaults to False.
Dataset setup describes the required training data.
from libreyolo import LibreYOLO model = LibreYOLO("LibrePPYOLOEs.pt", device="cpu")# coco8 is a small YOLO-format detection dataset that downloads automatically.model.train(data="coco8.yaml", epochs=1, device="cpu", workers=0)Validate
from libreyolo import LibreYOLO model = LibreYOLO("LibrePPYOLOEs.pt", device="cpu")metrics = model.val(data="coco8.yaml", workers=0)print(metrics)Use the dataset format for this task. Validation explains the dataset requirements and returned metrics.
Export
| Task | ONNX | TorchScript | ExecuTorch | TensorRT | OpenVINO | Paddle | MNN | RKNN | ncnn | TFLite | CoreML | Core AI |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Detection | Detection to ONNX: supported | Detection to TorchScript: supported | Detection to ExecuTorch: supported | Detection to TensorRT: supported | Detection to OpenVINO: supported | Detection to Paddle: not supported | Detection to MNN: not supported | Detection to RKNN: not supported | Detection to ncnn: supported | Detection to TFLite: not supported | Detection to CoreML: not supported | Detection to Core AI: not supported |
from libreyolo import LibreYOLO model = LibreYOLO("LibrePPYOLOEs.pt", device="cpu")model.export(format="onnx")Export setup lists format dependencies and loading exported artifacts.
Licensing
Check the license on the Hugging Face repository of the specific weights you download. Every checkpoint in the LibreYOLO org carries one, and they are not always the same across a family. That repository is the authoritative source; the summary below describes what applied when this page was last verified.
This is a description of the licenses involved, not legal advice. If the answer matters commercially, read the licenses yourself and take your own counsel.
- Original work
- PP-YOLOE, PaddlePaddle
- Upstream license
- Apache-2.0
- Upstream source
- github.com/PaddlePaddle/PaddleDetection
- LibreYOLO code
- MIT
- Weights
- No separate artifact grant recorded, distributed by their authors. LibreYOLO does not host or mirror them.
- Interpretation
- The upstream source is Apache-2.0. Pretrained artifacts download from the source CDN; a separate checkpoint license grant has not been recorded.
