TechC-SugarCane/yolov9-models
By TechC-SugarCane · ↓ 0 · ♥ 0 · Updated 2024-12-16
What's in this repo
This page lists the files in TechC-SugarCane/yolov9-models, including YOLOv9e.onnx, YOLOv9c.onnx, YOLOv9m.onnx and more.
- 7 ONNX models (.onnx files)
- 85 files, including 33 .jpg, 20 .png, 10 .pt, 7 .onnx, 6 .yaml, 3 .0
- Last updated 2024-12-16
ONNX files
| File | Size | Download |
|---|---|---|
| pineapple/YOLOv9e.onnx | — | Download |
| sugarcane/YOLOv9c.onnx | — | Download |
| sugarcane/YOLOv9m.onnx | — | Download |
| sugarcane/YOLOv9s.onnx | — | Download |
| training/yolov9-c-sugarcane/weights/best.onnx | — | Download |
| training/yolov9-m-sugarcane/weights/best.onnx | — | Download |
| training/yolov9-s-sugarcane/weights/best.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
I'll fetch the README content from the HuggingFace model page first. The README content for this model is minimal (only contains YAML frontmatter metadata). Here's the translated version:
---
license: mit
datasets:
- TechC-SugarCane/yolov9-datasets
language:
- ja
pipeline_tag: object-detection
---
许可证: mit
数据集: TechC-SugarCane/yolov9-datasets
语言: 日语
任务类型: 目标检测
(注: 原始 README 仅包含 YAML 元数据，无其他内容)
Model info
tensorboard
onnx
object-detection
ja
dataset:TechC-SugarCane/yolov9-datasets
license:mit
region:us
↓ 0
♥ 0
Created: 2024-07-09
Updated: 2024-12-16
View on Hugging FaceFiles (85)
.gitattributes
README.md
pineapple/YOLOv9e.onnx
ONNX
pineapple/YOLOv9e.pt
sugarcane/YOLOv9c.onnx
ONNX
sugarcane/YOLOv9c.pt
sugarcane/YOLOv9m.onnx
ONNX
sugarcane/YOLOv9m.pt
sugarcane/YOLOv9s.onnx
ONNX
sugarcane/YOLOv9s.pt
training/.gitkeep
training/yolov9-c-sugarcane/F1_curve.png
training/yolov9-c-sugarcane/PR_curve.png
training/yolov9-c-sugarcane/P_curve.png
training/yolov9-c-sugarcane/R_curve.png
training/yolov9-c-sugarcane/confusion_matrix.png
training/yolov9-c-sugarcane/events.out.tfevents.1733641338.pc-0417.22816.0
training/yolov9-c-sugarcane/hyp.yaml
training/yolov9-c-sugarcane/labels.jpg
training/yolov9-c-sugarcane/labels_correlogram.jpg
training/yolov9-c-sugarcane/opt.yaml
training/yolov9-c-sugarcane/results.csv
training/yolov9-c-sugarcane/results.png
training/yolov9-c-sugarcane/train_batch0.jpg
training/yolov9-c-sugarcane/train_batch1.jpg
training/yolov9-c-sugarcane/train_batch2.jpg
training/yolov9-c-sugarcane/val_batch0_labels.jpg
training/yolov9-c-sugarcane/val_batch0_pred.jpg
training/yolov9-c-sugarcane/val_batch1_labels.jpg
training/yolov9-c-sugarcane/val_batch1_pred.jpg
training/yolov9-c-sugarcane/val_batch2_labels.jpg
training/yolov9-c-sugarcane/val_batch2_pred.jpg
training/yolov9-c-sugarcane/weights/best.onnx
ONNX
training/yolov9-c-sugarcane/weights/best.pt
training/yolov9-c-sugarcane/weights/last.pt
training/yolov9-m-sugarcane/F1_curve.png
training/yolov9-m-sugarcane/PR_curve.png
training/yolov9-m-sugarcane/P_curve.png
training/yolov9-m-sugarcane/R_curve.png
training/yolov9-m-sugarcane/confusion_matrix.png
training/yolov9-m-sugarcane/events.out.tfevents.1733657104.pc-0417.1480.0
training/yolov9-m-sugarcane/hyp.yaml
training/yolov9-m-sugarcane/labels.jpg
training/yolov9-m-sugarcane/labels_correlogram.jpg
training/yolov9-m-sugarcane/opt.yaml
training/yolov9-m-sugarcane/results.csv
training/yolov9-m-sugarcane/results.png
training/yolov9-m-sugarcane/train_batch0.jpg
training/yolov9-m-sugarcane/train_batch1.jpg
training/yolov9-m-sugarcane/train_batch2.jpg
training/yolov9-m-sugarcane/val_batch0_labels.jpg
training/yolov9-m-sugarcane/val_batch0_pred.jpg
training/yolov9-m-sugarcane/val_batch1_labels.jpg
training/yolov9-m-sugarcane/val_batch1_pred.jpg
training/yolov9-m-sugarcane/val_batch2_labels.jpg
training/yolov9-m-sugarcane/val_batch2_pred.jpg
training/yolov9-m-sugarcane/weights/best.onnx
ONNX
training/yolov9-m-sugarcane/weights/best.pt
training/yolov9-m-sugarcane/weights/last.pt
training/yolov9-m-sugarcane/{A97751C9-E235-4C98-92E0-00DA6DD2F32F}.png
training/yolov9-s-sugarcane/F1_curve.png
training/yolov9-s-sugarcane/PR_curve.png
training/yolov9-s-sugarcane/P_curve.png
training/yolov9-s-sugarcane/R_curve.png
training/yolov9-s-sugarcane/confusion_matrix.png
training/yolov9-s-sugarcane/events.out.tfevents.1733691427.pc-0417.25012.0
training/yolov9-s-sugarcane/hyp.yaml
training/yolov9-s-sugarcane/labels.jpg
training/yolov9-s-sugarcane/labels_correlogram.jpg
training/yolov9-s-sugarcane/opt.yaml
training/yolov9-s-sugarcane/results.csv
training/yolov9-s-sugarcane/results.png
training/yolov9-s-sugarcane/train_batch0.jpg
training/yolov9-s-sugarcane/train_batch1.jpg
training/yolov9-s-sugarcane/train_batch2.jpg
training/yolov9-s-sugarcane/val_batch0_labels.jpg
training/yolov9-s-sugarcane/val_batch0_pred.jpg
training/yolov9-s-sugarcane/val_batch1_labels.jpg
training/yolov9-s-sugarcane/val_batch1_pred.jpg
training/yolov9-s-sugarcane/val_batch2_labels.jpg
training/yolov9-s-sugarcane/val_batch2_pred.jpg
training/yolov9-s-sugarcane/weights/best.onnx
ONNX
training/yolov9-s-sugarcane/weights/best.pt
training/yolov9-s-sugarcane/weights/last.pt
training/yolov9-s-sugarcane/{3CE0D9A5-86B9-45E0-A14D-8C5981CD0B0A}.png