Predicts plant type given an image.
See https://www.kaggle.com/code/dima806/30-plant-types-image-detection-vit for more details.
Classification report:
precision recall f1-score support
guava 0.9846 0.9600 0.9722 200
galangal 0.9418 0.8900 0.9152 200
bilimbi 0.9949 0.9750 0.9848 200
paddy 0.9731 0.9050 0.9378 200
eggplant 0.9848 0.9700 0.9773 200
cucumber 0.9561 0.9800 0.9679 200
cassava 0.9899 0.9800 0.9849 200
papaya 0.9851 0.9950 0.9900 200
banana 0.9950 0.9900 0.9925 200
orange 0.9534 0.9200 0.9364 200
cantaloupe 0.5271 0.3400 0.4134 200
coconut 0.9950 1.0000 0.9975 200
soybeans 0.9754 0.9900 0.9826 200
pomelo 0.9563 0.9850 0.9704 200
pineapple 0.9703 0.9800 0.9751 200
melon 0.5000 0.6150 0.5516 200
shallot 0.9949 0.9750 0.9848 200
peperchili 0.9755 0.9950 0.9851 200
spinach 0.9231 0.9600 0.9412 200
tobacco 0.9151 0.9700 0.9417 200
aloevera 0.9949 0.9800 0.9874 200
curcuma 0.9005 0.8600 0.8798 200
corn 0.9610 0.9850 0.9728 200
ginger 0.8551 0.8850 0.8698 200
sweetpotatoes 1.0000 0.9950 0.9975 200
kale 0.9268 0.9500 0.9383 200
longbeans 0.9850 0.9850 0.9850 200
watermelon 0.9252 0.9900 0.9565 200
mango 0.9239 0.9100 0.9169 200
waterapple 0.8807 0.9600 0.9187 200
accuracy 0.9292 6000
macro avg 0.9282 0.9292 0.9275 6000
weighted avg 0.9282 0.9292 0.9275 6000
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