Model card for convnextv2_tiny.ft_plantdoc_384
Overview
This model classifies diseases from plant images.
- Dataset size: 8000 images
- Number of classes: 39
- Architecture: ConvNeXtV2 Tiny (384)
Metrics
- mAP: 0.94
- Accuracy: 0.86
Model
Model Details
- Model Type: Image classification
- Backbone: convnextv2_tiny.fcmae_ft_in22k_in1k_384
- Model Stats:
- Params (M): 28.6
- GMACs: 13.1
- Activations (M): 39.5
- Image size: 384 x 384
- Papers:
- ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders: https://arxiv.org/abs/2301.00808
- Original: https://github.com/facebookresearch/ConvNeXt-V2
- Dataset: PlantDoc (8000 images)
- Pretrain Dataset: ImageNet-1k
Model Usage
Built with:
import torch
import timm
# create model
model = timm.create_model(
"convnextv2_tiny.fcmae_ft_in22k_in1k_384",
pretrained=False,
num_classes=39,
drop_rate=0.2,
drop_path_rate=0.2,
)
# load weights
state_dict = torch.load("model.bin", map_location="cpu")
model.load_state_dict(state_dict)