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best_smoke_cigarette-detection
Beehzod/best_smoke_cigarette-detection
best_smoke_cigarette-detection is a object detection model from Beehzod. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as mit.
Fine-tuned from the official Ultralytics YOLO11m checkpoint (yolo11m.pt) using Ultralytics.
All-time downloads
257
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Repo size
40.5 MB
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1
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Repo makeup
Click a slice to open those files.
.pt40.5 MB · 100%
At a glance
- Task
- Object Detection
- Library
- ultralytics
- License
- mit
- Access
- Public
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026
- SHA
- 8dd44e25
Base models
Model card
From the Hugging Face model README
best_smoke_cigarette-detection
Fine-tuned from the official Ultralytics YOLO11m checkpoint (yolo11m.pt) using Ultralytics.
Classes
cigarette
Dataset
- Source: richie-lab/smoking-tasfx (version 2)
- Images: 12046 train / 318 valid / 122 test
- Check the dataset page above for its license -- not necessarily the same as this repo's
licensefield, which reflects the base model's license.
Training
| Parameter | Value |
|---|---|
| Base checkpoint | yolo11m.pt |
| Epochs | 100 |
| Image size | 640 |
| Batch size | 17 |
| Optimizer | AdamW |
| Initial LR (lr0) | 0.001 |
| Patience (early stop) | 20 |
Results (held-out validation split)
| Metric | Value |
|---|---|
| mAP50 | 0.7898 |
| mAP50-95 | 0.4617 |
| Precision | 0.8199 |
| Recall | 0.7650 |
Usage
from ultralytics import YOLO
model = YOLO("best.pt")
results = model.predict("image.jpg", conf=0.25)
for r in results:
for box in r.boxes:
print(model.names[int(box.cls[0])], float(box.conf[0]))
- Task
- Object Detection
- Library
- ultralytics
- License
- mit
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026