---
license: other
library_name: ultralytics
pipeline_tag: object-detection
tags:
- yolo
- yolov12
- snake-detection
datasets:
- the-khiem7/snakeaid-yolov12-5000-bbox
base_model: ultralytics/yolov12
model-index:
- name: SnakeAid Detect YOLOv12s 17e 5000BBox
  results: []
---

# SnakeAid Detect YOLOv12s 17e 5000BBox

## Model Summary

This repository contains a SnakeAid Detect YOLOv12 checkpoint for snake object detection. The checkpoint is published as a `.pt` file and linked to the dataset version used for the corresponding experiment.

> Safety note: this model is intended for research, prototyping, and application experiments. Do not use it as the sole authority for snake identification, emergency response, or animal handling decisions.

## Checkpoint

| Field | Value |
| --- | --- |
| File | `SnakeAid_SnakeDetector_YOLOv12s_5000Bbox_17epoch_Nhan.pt` |
| Size | 17.78 MB |
| SHA256 | `230e2db84bbcd3f07951ab8d5ed2be271a951f66655d281bf760ea5b9afdcaf0` |
| Dataset | [`the-khiem7/snakeaid-yolov12-5000-bbox`](https://huggingface.co/datasets/the-khiem7/snakeaid-yolov12-5000-bbox) |
| Architecture | YOLOv12s |
| Epochs | 17 |
| Trained by | Nhan |

## Intended Use

- Snake detection experiments with YOLOv12-compatible tooling.
- Comparing SnakeAid dataset versions and checkpoint variants.
- Downstream evaluation, prototyping, and transfer-learning baselines.

## Out-of-Scope Use

- Safety-critical snake identification without human/expert review.
- Medical, veterinary, emergency, or wildlife handling decisions based only on model output.
- Deployment to image domains not represented by the linked dataset without additional validation.

## Dataset

This model is linked to [`the-khiem7/snakeaid-yolov12-5000-bbox`](https://huggingface.co/datasets/the-khiem7/snakeaid-yolov12-5000-bbox).

The Hub metadata also includes this dataset in the `datasets` field so Hugging Face can display the training-data relationship.

## Usage Example

```python
from huggingface_hub import hf_hub_download

checkpoint_path = hf_hub_download(
    repo_id="the-khiem7/snakeaid-detect-yolov12s-17e-5000bbox",
    filename="SnakeAid_SnakeDetector_YOLOv12s_5000Bbox_17epoch_Nhan.pt",
)
print(checkpoint_path)
```

If your environment supports Ultralytics-compatible YOLOv12 checkpoints:

```python
from huggingface_hub import hf_hub_download
from ultralytics import YOLO

checkpoint_path = hf_hub_download(
    repo_id="the-khiem7/snakeaid-detect-yolov12s-17e-5000bbox",
    filename="SnakeAid_SnakeDetector_YOLOv12s_5000Bbox_17epoch_Nhan.pt",
)
model = YOLO(checkpoint_path)
results = model.predict("path/to/image.jpg")
```

## Evaluation

No standardized metrics were uploaded with this checkpoint. Evaluate it on a held-out split or a domain-specific benchmark before comparing it with other detectors or deploying it.

## Training And Reproducibility Notes

Known metadata:

- Architecture: YOLOv12s
- Epochs: 17
- Trained by: Nhan

The original training code, hyperparameters, random seed, and evaluation logs were not included in this upload.

## Related Dataset Version

- [`snakeaid-yolov12-5000-bbox`](https://huggingface.co/datasets/the-khiem7/snakeaid-yolov12-5000-bbox)