Statements (53)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
object detection model
|
| gptkbp:accuracy |
higher than YOLOv5s, YOLOv5m, YOLOv5l
|
| gptkbp:application |
real-time object detection
|
| gptkbp:architecture |
gptkb:CSPDarknet53_backbone
PANet neck YOLO head |
| gptkbp:developedBy |
gptkb:Ultralytics
|
| gptkbp:hasVariant |
gptkb:YOLOv5l
gptkb:YOLOv5m gptkb:YOLOv5n gptkb:YOLOv5s |
| https://www.w3.org/2000/01/rdf-schema#label |
YOLOv5x
|
| gptkbp:inferenceSpeed |
slower than smaller YOLOv5 models
|
| gptkbp:input |
gptkb:DVD
gptkb:illustrator |
| gptkbp:license |
GPL-3.0
|
| gptkbp:output |
class labels
bounding boxes confidence scores |
| gptkbp:partOf |
YOLOv5 family
|
| gptkbp:platform |
gptkb:PyTorch
|
| gptkbp:releaseYear |
2020
|
| gptkbp:repository |
https://github.com/ultralytics/yolov5
|
| gptkbp:resolution |
640x640 by default
|
| gptkbp:size |
largest model in YOLOv5 family
~173M parameters |
| gptkbp:supports |
transfer learning
augmentation batch inference multi-GPU training ONNX export CoreML export OpenVINO export TensorRT export custom dataset training export to TorchScript half-precision (FP16) inference |
| gptkbp:trainer |
gptkb:COCO_dataset
|
| gptkbp:usedFor |
agriculture
autonomous vehicles industrial automation robotics sports analytics medical imaging smart cities wildlife monitoring retail analytics video surveillance |
| gptkbp:uses |
non-maximum suppression
anchor boxes |
| gptkbp:writtenBy |
gptkb:Python
|
| gptkbp:bfsParent |
gptkb:YOLOv5
|
| gptkbp:bfsLayer |
7
|