PP-YOLOE
PP-YOLOE is an anchor-free object detector with detection training and class-head resizing.
- Tareas
- detection
- Tamaños
- s, m, l, x at 640 px
- Instalación
pip install libreyolo- Nivel de compatibilidad
- Compatible, desde v1.6.0. Modelos entrenables de apoyo: se mantienen operativos en CI y reciben funciones cuando surge la oportunidad.
- Licencias
- Código MIT, pesos No separate artifact grant recorded. Uso comercial
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
| Tarea | ONNX | TorchScript | ExecuTorch | TensorRT | OpenVINO | Paddle | MNN | RKNN | ncnn | TFLite | CoreML | Core AI |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Detection | Detection to ONNX: compatible | Detection to TorchScript: compatible | Detection to ExecuTorch: compatible | Detection to TensorRT: compatible | Detection to OpenVINO: compatible | Detection to Paddle: no compatible | Detection to MNN: no compatible | Detection to RKNN: no compatible | Detection to ncnn: compatible | Detection to TFLite: no compatible | Detection to CoreML: no compatible | Detection to Core AI: no compatible |
from libreyolo import LibreYOLO model = LibreYOLO("LibrePPYOLOEs.pt", device="cpu")model.export(format="onnx")Export setup lists format dependencies and loading exported artifacts.
Licensing
Comprueba la licencia en el repositorio de Hugging Face de los pesos concretos que descargues. Cada checkpoint de la organización de LibreYOLO incluye una, y no siempre es la misma en toda una familia. Ese repositorio es la fuente autorizada; el resumen siguiente describe qué se aplicaba cuando se verificó esta página por última vez.
Esta es una descripción de las licencias implicadas, no asesoramiento legal. Si la respuesta es importante a nivel comercial, lee las licencias y busca tu propio asesoramiento.
- Trabajo original
- PP-YOLOE, PaddlePaddle
- Licencia del proyecto original
- Apache-2.0
- Fuente del proyecto original
- github.com/PaddlePaddle/PaddleDetection
- Código de LibreYOLO
- MIT
- Pesos
- No separate artifact grant recorded, distribuidos por sus autores. LibreYOLO no los aloja ni los replica.
- Interpretación
- The upstream source is Apache-2.0. Pretrained artifacts download from the source CDN; a separate checkpoint license grant has not been recorded.
