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yolov8s_visdrone
ENOT-AutoDL/yolov8s_visdrone
yolov8s_visdrone is a object detection model from ENOT-AutoDL. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as apache-2.0.
This repository contains models accelerated with ENOT-AutoDL framework. We trained yolov8s on VisDrone dataset and used it as our baseline. Also we provide simple python script to measure flops and metrics.
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At a glance
- Task
- Object Detection
- Library
- ultralytics
- License
- apache-2.0
- Access
- Public
- Created
- Nov 7, 2023
- Updated
- Mar 11, 2024
- SHA
- 13f27116
Datasets
Model card
From the Hugging Face model README
ENOT-AutoDL YOLOv8 optimization on VisDrone dataset
This repository contains models accelerated with ENOT-AutoDL framework. We trained yolov8s on VisDrone dataset and used it as our baseline. Also we provide simple python script to measure flops and metrics.
YOLOv8 Small
| Model | GMACs | Image Size | mAP50 | mAP50-95 |
|---|---|---|---|---|
| YOLOv8 Ultralytics Baseline | 14,28 | 640 | 40,2 | 24,2 |
| YOLOv8n Enot Baseline | 8,57 | 928 | 42,9 | 26,0 |
| YOLOv8s Enot Baseline | 30,03 | 928 | 49,4 | 30,6 |
| YOLOv8s (x2) | 15,01 (x2) | 928 | 48,3 (-1,1) | 29,8 (-0,8) |
| YOLOv8s (x3) | 10,01 (x3) | 928 | 46,0 (-3,4) | 28,3 (-2,3) |
Validation
To validate results, follow this steps:
- Install all required packages:
pip install -r requrements.txt
- Use validation script:
python validate.py enot_neural_architecture_selection_x2/weights/best.pt --imgsz 928
- Use measure_macs script:
python measure_macs.py enot_neural_architecture_selection_x2/weights/best.pt --imgsz 928
- Task
- Object Detection
- Library
- ultralytics
- License
- apache-2.0
- Created
- Nov 7, 2023
- Updated
- Mar 11, 2024