the-khiem7/snakeaid-yolov12-5000-bbox

---
license: cc0-1.0
task_categories:
- object-detection
tags:
- yolo
- yolov12
- snake-detection
- roboflow
pretty_name: SnakeAid YOLOv12 5000 BBox
---

# SnakeAid YOLOv12 5000 BBox

## Dataset Summary

This repository contains a YOLO-format SnakeAid object-detection dataset for snake detection experiments. It is organized as image/label pairs across `train, valid, test` splits and is intended for training or evaluating YOLO-family detectors, including the related SnakeAid Detect YOLOv12 checkpoints linked below.

> Safety note: snake detection can be safety-critical in real-world use. Treat model outputs trained on this data as assistive signals only; do not use them as the sole basis for handling, approaching, or identifying a snake.

## Key Details

| Field | Value |
| --- | --- |
| Format | YOLO object detection |
| Splits | `train, valid, test` |
| Images | 5291 |
| Label files | 5291 |
| Classes | 22 |
| License metadata | `cc0-1.0` |
| Uploadable local files | 21172 |

## Splits

| Split | Images | Labels |
| --- | ---: | ---: |
| train | 4795 | 4795 |
| valid | 265 | 265 |
| test | 231 | 231 |

## File Layout

```text
data.yaml
train/images/*.jpg
train/labels/*.txt
valid/images/*.jpg
valid/labels/*.txt
test/images/*.jpg
test/labels/*.txt
```

Each image is paired with a YOLO `.txt` label file using the same stem. Class names and split paths are defined in `data.yaml`.

## Classes

| Class ID | Name |
| ---: | --- |
| 0 | `cap_nia_bac` |
| 1 | `cap_nia_nam` |
| 2 | `cap_nong` |
| 3 | `ho_mang_chua` |
| 4 | `ho_mang_xiem` |
| 5 | `khiem_vach` |
| 6 | `luc_cuom` |
| 7 | `luc_nua` |
| 8 | `luc_xanh` |
| 9 | `luc_xanh_duoi_do` |
| 10 | `ran_cuom` |
| 11 | `ran_dai_lon` |
| 12 | `ran_hoa_can_van_dom` |
| 13 | `ran_hoa_co_do` |
| 14 | `ran_rao` |
| 15 | `ran_rao_trau` |
| 16 | `ran_ri_ca` |
| 17 | `ran_roi` |
| 18 | `ran_sai_co` |
| 19 | `ran_soc_dua` |
| 20 | `ran_soc_go` |
| 21 | `ran_trun` |

## Loading Example

```python
from huggingface_hub import snapshot_download

dataset_dir = snapshot_download(
repo_id="the-khiem7/snakeaid-yolov12-5000-bbox",
repo_type="dataset",
)
print(dataset_dir)
```

For YOLO training, point your training command at the downloaded `data.yaml`.

## Provenance

- workspace: anh-by-i-n-nh-em
- project: my-first-project-hyskh
- version: 6
- license: Public Domain
- url: https://universe.roboflow.com/anh-by-i-n-nh-em/my-first-project-hyskh/dataset/6

## Related Models

- [the-khiem7/snakeaid-detect-yolov12s-17e-5000bbox](https://huggingface.co/the-khiem7/snakeaid-detect-yolov12s-17e-5000bbox)
- [the-khiem7/snakeaid-detect-yolov12-v4-5000bbox](https://huggingface.co/the-khiem7/snakeaid-detect-yolov12-v4-5000bbox)

## Limitations

- The dataset is provided as a local YOLO export, not as a fully curated benchmark.
- Class balance, duplicate images, annotation quality, and real-world geographic coverage have not been independently audited in this upload workflow.
- Performance can vary significantly with lighting, camera angle, occlusion, species similarity, and image quality.
- Use additional validation before deploying a detector trained on this data in field or safety-sensitive settings.

---
license: CC0 1.0
task_categories:
- 目标检测（object-detection）
tags:
- YOLO
- YOLOv12
- 蛇类检测（snake-detection）
- Roboflow
pretty_name: SnakeAid YOLOv12 5000 BBox
---

# SnakeAid YOLOv12 5000 BBox

## 数据集概述
本仓库包含一个适配蛇类检测实验的YOLO格式SnakeAid目标检测数据集。该数据集按照训练集、验证集、测试集划分，以图像与标签对的形式组织，可用于训练或评估YOLO系列检测器，包括下文链接的相关SnakeAid Detect YOLOv12模型权重。

> 安全提示：蛇类检测在实际应用中关乎安全。仅可将基于本数据集训练的模型输出作为辅助信号，不可将其作为处理、接近或识别蛇类的唯一依据。

## 关键详情
| 字段 | 取值 |
| --- | --- |
| 格式 | YOLO目标检测格式 |
| 划分集 | `train, valid, test` |
| 图像总数 | 5291张 |
| 标签文件数 | 5291个 |
| 类别数 | 22类 |
| 许可证元数据 | `cc0-1.0` |
| 可上传本地文件数 | 21172个 |

## 划分集详情
| 划分集 | 图像数 | 标签数 |
| --- | ---: | ---: |
| 训练集（train） | 4795 | 4795 |
| 验证集（valid） | 265 | 265 |
| 测试集（test） | 231 | 231 |

## 文件布局
text
data.yaml
train/images/*.jpg
train/labels/*.txt
valid/images/*.jpg
valid/labels/*.txt
test/images/*.jpg
test/labels/*.txt

每张图像均对应一个同名的YOLO格式`.txt`标签文件。类别名称与划分集路径均在`data.yaml`中定义。

## 类别列表
| 类别ID | 类别名称 |
| ---: | --- |
| 0 | `cap_nia_bac` |
| 1 | `cap_nia_nam` |
| 2 | `cap_nong` |
| 3 | `ho_mang_chua` |
| 4 | `ho_mang_xiem` |
| 5 | `khiem_vach` |
| 6 | `luc_cuom` |
| 7 | `luc_nua` |
| 8 | `luc_xanh` |
| 9 | `luc_xanh_duoi_do` |
| 10 | `ran_cuom` |
| 11 | `ran_dai_lon` |
| 12 | `ran_hoa_can_van_dom` |
| 13 | `ran_hoa_co_do` |
| 14 | `ran_rao` |
| 15 | `ran_rao_trau` |
| 16 | `ran_ri_ca` |
| 17 | `ran_roi` |
| 18 | `ran_sai_co` |
| 19 | `ran_soc_dua` |
| 20 | `ran_soc_go` |
| 21 | `ran_trun` |

## 加载示例
python
from huggingface_hub import snapshot_download

dataset_dir = snapshot_download(
repo_id="the-khiem7/snakeaid-yolov12-5000-bbox",
repo_type="dataset",
)
print(dataset_dir)

若需进行YOLO训练，可将训练命令指向下载后的`data.yaml`文件。

## 数据集来源
- 工作区：anh-by-i-n-nh-em
- 项目：my-first-project-hyskh
- 版本：6
- 许可证：公共领域
- 网址：https://universe.roboflow.com/anh-by-i-n-nh-em/my-first-project-hyskh/dataset/6

## 相关模型
- [the-khiem7/snakeaid-detect-yolov12s-17e-5000bbox](https://huggingface.co/the-khiem7/snakeaid-detect-yolov12s-17e-5000bbox)
- [the-khiem7/snakeaid-detect-yolov12-v4-5000bbox](https://huggingface.co/the-khiem7/snakeaid-detect-yolov12-v4-5000bbox)

## 局限性说明
- 本数据集仅以本地YOLO导出格式提供，并非经过全面整理的基准测试集。
- 本次上传流程中未对类别平衡、重复图像、标注质量以及真实世界地理覆盖范围进行独立审核。
- 模型性能会因光照、拍摄角度、遮挡、物种相似度以及图像质量的不同而出现显著差异。
- 在野外或安全敏感场景中部署基于本数据集训练的检测器前，请先进行额外验证。