README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- image-segmentation
- image-classification
tags:
- weed
- agriculture
- segmentation
- semantic-segmentation
- height-estimation
- regression
- growth-stage
- multi-task-learning
- weedsense
- precision-agriculture
- plant-phenotyping
- temporal
pretty_name: "WeedSense: Multi-Task Weed Analysis Dataset"
size_categories:
- 100K<n<1M
---

# WeedSense Dataset

Multi-task temporal dataset of **16 weed species** for semantic segmentation, height regression, and growth stage classification from the **WeedSense** paper:

> **WeedSense: Multi-Task Learning for Weed Segmentation, Height Estimation, and Growth Stage Classification**
> Toqi Tahamid Sarker, Khaled R Ahmed, Taminul Islam, Cristiana Bernardi Rankrape, Karla Gage
> Southern Illinois University Carbondale, USA
> **ICCV 2025**
>
> [Paper (arXiv)](https://arxiv.org/abs/2508.14486) | [Project Page](https://weedsense.github.io/) | [Code](https://github.com/toqitahamid/WeedSense)

## Overview

| Property | Value |
|---|---|
| Total frames | **120,341** |
| Weed species | **16** |
| Growth duration | **11 weeks** |
| Total videos | **349** |
| Frame resolution | **720 x 960 pixels** |
| Annotation types | **Segmentation masks, Height (cm), Growth stage (week)** |
| Semantic classes | **17** (16 species + background) |
| Height range | **0.2 - 155 cm** |

## Data Splits

| Split | Images | Percentage |
|---|---|---|
| Train | 96,134 | ~80% |
| Validation | 12,333 | ~10% |
| Test | 11,874 | ~10% |

## Folder Structure

Large folders are distributed as **zip archives** (HF enforces a 10,000-file-per-directory limit).

```
train/
  images.zip              # RGB images (720 x 960) as .jpg
  masks.zip               # Segmentation masks (single-channel, class IDs 0-16) as .png
  mmseg_masks.zip         # Segmentation masks formatted for MMSegmentation as .png
  xml.zip                 # VOC-format bounding box annotations as .xml
  train_data.csv          # Metadata: img, species, height, week
val/
  images.zip
  masks.zip
  mmseg_masks.zip
  xml.zip
  val_data.csv
test/
  images.zip
  masks.zip
  mmseg_masks.zip
  xml.zip
  test_data.csv
```

### After Extracting

Each zip extracts into a flat list of files. For example, `train/images.zip` contains:
```
ABUTH_week_10_IMG_1656_frame_0.jpg
ABUTH_week_10_IMG_1656_frame_1.jpg
SETFA_week_8_IMG_1344_frame_13.jpg
...
```

### File Naming Convention

All files follow the pattern: `{SPECIES}_week_{WEEK}_IMG_{VIDEO_ID}_frame_{FRAME}.{ext}`

Example: `SETFA_week_8_IMG_1344_frame_13.jpg`

### CSV Metadata

Each split CSV contains columns:

| Column | Type | Description |
|---|---|---|
| `img` | string | Image filename (e.g., `ABUTH_week_10_IMG_1656_frame_0.jpg`) |
| `species` | string | Weed species EPPO code (e.g., `ABUTH`, `SETFA`) |
| `height` | float | Plant height in centimeters (0.2 - 155.0 cm) |
| `week` | int | Growth stage week (1 - 11) |

### Segmentation Mask Values

| Pixel Value | Class |
|---|---|
| 0 | Background |
| 1 | ABUTH (Velvetleaf) |
| 2 | AMAPA (Palmer Amaranth) |
| 3 | AMARE (Redroot Pigweed) |
| 4 | AMATA / AMATU (Tall Waterhemp) |
| 5 | AMBEL (Common Ragweed) |
| 6 | CHEAL (Common Lambsquarters) |
| 7 | CYPES (Yellow Nutsedge) |
| 8 | DIGSA (Large Crabgrass) |
| 9 | ECHCG (Barnyardgrass) |
| 10 | ERICA (Horseweed) |
| 11 | PANDI (Fall Panicum) |
| 12 | SETFA (Giant Foxtail) |
| 13 | SETPU (Yellow Foxtail) |
| 14 | SIDSP (Prickly Sida) |
| 15 | SORHA (Johnsongrass) |
| 16 | SORVU (Shattercane) |

## Weed Species Summary

| EPPO Code | Scientific Name | Max Height (cm) | Growth Rate (cm/week) | Category |
|---|---|---|---|---|
| AMATU | *Amaranthus tuberculatus* | 155.0 | 13.72 | Fast |
| SORHA | *Sorghum halepense* | 121.0 | 14.06 | Fast |
| SETFA | *Setaria faberi* | 124.0 | 11.75 | Fast |
| SORVU | *Sorghum bicolor* | 100.0 | 9.84 | Medium |
| PANDI | *Panicum dichotomiflorum* | 87.0 | 8.40 | Medium |
| SETPU | *Setaria pumila* | 99.0 | 8.20 | Medium |
| DIGSA | *Digitaria sanguinalis* | 77.0 | 7.53 | Medium |
| ECHCG | *Echinochloa crus-galli* | 80.0 | 7.38 | Medium |
| SIDSP | *Sida spinosa* | 69.0 | 6.77 | Medium |
| AMARE | *Amaranthus retroflexus* | 75.0 | 6.86 | Medium |
| ABUTH | *Abutilon theophrasti* | 72.0 | 6.32 | Medium |
| AMBEL | *Ambrosia artemisiifolia* | 71.0 | 6.19 | Medium |
| AMAPA | *Amaranthus palmeri* | 62.0 | 5.66 | Slow |
| CYPES | *Cyperus esculentus* | 56.0 | 5.42 | Slow |
| CHEAL | *Chenopodium album* | 30.0 | 2.86 | Slow |
| ERICA | *Erigeron canadensis* | 17.3 | 1.70 | Slow |

## Data Collection

- **Location**: SIU Horticulture Research Center greenhouse, Southern Illinois University Carbondale, USA
- **Equipment**: iPhone 15 Pro Max positioned 1.5 feet above specimens
- **Capture**: 360-degree video at 1440 x 1920 resolution, 30 FPS
- **Environment**: 1000W HPS grow lights, 30-32 degree C
- **Preprocessing**: Temporal downsampling (every 2nd frame), spatial downscaling to 720 x 960
- **Annotation**: SAM2-Hiera-L semi-automatic segmentation with manual verification and correction
- **Height**: 325 manual weekly measurements (0.2 - 155 cm)

## Benchmark Results (WeedSense Model)

| Task | Metric | Value |
|---|---|---|
| Segmentation | mIoU | 89.78% |
| Segmentation | mF1 | 94.54% |
| Height Estimation | MAE | 1.67 cm |
| Height Estimation | RMSE | 2.32 cm |
| Height Estimation | R squared | 0.9941 |
| Growth Stage | Accuracy | 99.99% |
| Growth Stage | F1 | 99.99% |

## Usage

```python
from huggingface_hub import snapshot_download, hf_hub_download
import zipfile, os

# Download entire dataset
local_dir = snapshot_download(repo_id="baselab/weedsense", repo_type="dataset")

# Extract a zip file
with zipfile.ZipFile(os.path.join(local_dir, "train", "images.zip"), "r") as z:
    z.extractall(os.path.join(local_dir, "train", "images"))

# Load metadata
import pandas as pd
train_csv = hf_hub_download(
    repo_id="baselab/weedsense",
    repo_type="dataset",
    filename="train/train_data.csv",
)
df = pd.read_csv(train_csv)
print(df.head())
#                                        img species  height  week
# 0  ABUTH_week_10_IMG_1656_frame_0.jpg   ABUTH    50.0    10
# 1  ABUTH_week_10_IMG_1656_frame_1.jpg   ABUTH    50.0    10
```

## Citation

If you use this dataset, please cite:

```bibtex
@inproceedings{sarker2025weedsense,
  title={Weedsense: Multi-task learning for weed segmentation, height estimation, and growth stage classification},
  author={Sarker, Toqi Tahamid and Ahmed, Khaled R and Islam, Taminul and Rankrape, Cristiana Bernardi and Gage, Karla},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={7180--7190},
  year={2025}
}
```

## License

This dataset is released under the [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license. Commercial use is not permitted. Derivative works must use the same license.