Dataset used: kaggle/plantdisease

data avaliable:

Potato healthy : 152
Potato Late blight : 1000
Potato Early blight : 1000
Pepper bell healthy : 1478
Pepper bell Bacterial spot : 997
Tomato Leaf Mold : 952
Tomato Spider mites Two spotted spider mite : 1676
Tomato Early blight : 1000
Tomato Tomato YellowLeaf Curl Virus : 3209
Tomato Late blight : 1909
Tomato healthy : 1591
Tomato Target Spot : 1404
Tomato Bacterial spot : 2127
Tomato Tomato mosaic virus : 373
Tomato Septoria leaf spot : 1771

total available: 20639

model-1 accuracy: 74.9576985836029 %

data used during training of model-1: [less due to google colab limitations]

Potato healthy : 152
Potato Late blight : 200
Potato Early blight : 200
Pepper bell healthy : 200
Pepper bell Bacterial spot : 200
Tomato Leaf Mold : 200
Tomato Spider mites Two spotted spider mite : 200
Tomato Early blight : 200
Tomato Tomato YellowLeaf Curl Virus : 200
Tomato Late blight : 200
Tomato healthy : 200
Tomato Target Spot : 200
Tomato Bacterial spot : 200
Tomato Tomato mosaic virus : 200
Tomato Septoria leaf spot : 200

total used: 2952

contributing 101:

# clone using http not ssh as lfs have problems with ssh
# set remote url to https
git clone https://github.com/codecult-org/leaf-disease-detection.git

# install git-lfs to pull the model
sudo pacman -S git-lfs # for arch based distros

# to download the model
git lfs install
git lfs pull