/CWD30

Official Repository for CWD30 Dataset

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CWD30 | Project Page

Full Paper arXiv

CWD30 comprises over 219,770 high-resolution images of 20 weed species and 10 crop species, encompassing various growth stages, multiple viewing angles, and environmental conditions. The images were collected from diverse agricultural fields across different geographic locations and seasons, ensuring a representative dataset.

Data Download Link

If you use our data/paper in your projects kindly cite the paper and star the repo.

Global Distribution of Crops in the CWD30 dataset.

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MODEL ZOO

Classification Models

⚠️NOTE⚠️ We are currently in middle of uploading the weights. All might not be available.

Model Weights Acc
ResNet-18 chkpt 79.5
ResNet-50 chkpt 84.6
ResNet-101 chkpt 81.36
MobileNetv3-S chkpt 80.5
MobileNetv3-L chkpt 74.67
EffNet-B0 chkpt 83.2
EffNet-B3 chkpt 83.64
EffNet-B5 chkpt 84.5
ConvNeXt-T chkpt 85.6
ConvNeXt-M chkpt 85.9
ConvNeXt-L chkpt 84.7
ViT-T chkpt 83.43
ViT-B chkpt 86.4
CaiT-T chkpt 85.2
CaiT-S chkpt 86.9
Swin-T chkpt 85.59
Swin-B chkpt 85.3
Swin-L chkpt 87.0
MaxViT-S chkpt 86.5
MaxViT-B chkpt 87.08
CoAtNet-1 chkpt 86.1
CoAtNet-3 chkpt 84.3
EffFormer-L1 chkpt 80.5
EffFormer-L3 chkpt 82.7
EffFormer-L7 chkpt 81.2

Pretrained Weights on iNaturalist

ReNet-101 Weights Acc.
iNat21 ✅chkpt <80%
iNat17 ✅chkpt 60.41%
Semantic Segmentation Models

Access dataset via:

⚠️NOTE⚠️ We are currently in middle of uploading the weights. All might not be available.

Model BeanWeed SugarBeet CarrotWeed
UNet ✅72.49 mIOU, chkpt ✅85.47 mIOU, chkpt ✅78.32 mIOU, chkpt
DeepLab v3+ 78.03 mIOU, chkpt 86.02 mIOU, chkpt ✅83.16 mIOU, chkpt
OCR 79.51 mIOU, chkpt 87.34 mIOU, chkpt ✅86.53 mIOU, chkpt
SegNext 83.90 mIOU, chkpt 87.65 mIOU, chkpt ✅88.54 mIOU, chkpt

✅MSCAN backbone SegNext

Instances Segmentation Models

Access dataset via:

Model Data Weights PQ
MaskRCNN (ResNet-101 FPN backbone) PhenoBench ✅chkpt 44.05
MaskRCNN (ResNet-101 FPN backbone) GrowliFlower ✅chkpt 56.33

Citation

@article{ilyas2023cwd30,
  title={CWD30: A Comprehensive and Holistic Dataset for Crop Weed Recognition in Precision Agriculture},
  author={Ilyas, Talha and Arsa, Dewa Made Sri and Ahmad, Khubaib and Jeong, Yong Chae and Won, Okjae and Lee, Jong Hoon and Kim, Hyongsuk},
  journal={arXiv preprint arXiv:2305.10084},
  year={2023}
}

Paper is currently under review. ;)