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--- |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- f1 |
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--- |
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Predicts plant type given an image. |
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See https://www.kaggle.com/code/dima806/30-plant-types-image-detection-vit for more details. |
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``` |
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Classification report: |
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precision recall f1-score support |
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guava 0.9846 0.9600 0.9722 200 |
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galangal 0.9418 0.8900 0.9152 200 |
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bilimbi 0.9949 0.9750 0.9848 200 |
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paddy 0.9731 0.9050 0.9378 200 |
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eggplant 0.9848 0.9700 0.9773 200 |
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cucumber 0.9561 0.9800 0.9679 200 |
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cassava 0.9899 0.9800 0.9849 200 |
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papaya 0.9851 0.9950 0.9900 200 |
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banana 0.9950 0.9900 0.9925 200 |
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orange 0.9534 0.9200 0.9364 200 |
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cantaloupe 0.5271 0.3400 0.4134 200 |
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coconut 0.9950 1.0000 0.9975 200 |
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soybeans 0.9754 0.9900 0.9826 200 |
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pomelo 0.9563 0.9850 0.9704 200 |
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pineapple 0.9703 0.9800 0.9751 200 |
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melon 0.5000 0.6150 0.5516 200 |
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shallot 0.9949 0.9750 0.9848 200 |
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peperchili 0.9755 0.9950 0.9851 200 |
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spinach 0.9231 0.9600 0.9412 200 |
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tobacco 0.9151 0.9700 0.9417 200 |
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aloevera 0.9949 0.9800 0.9874 200 |
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curcuma 0.9005 0.8600 0.8798 200 |
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corn 0.9610 0.9850 0.9728 200 |
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ginger 0.8551 0.8850 0.8698 200 |
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sweetpotatoes 1.0000 0.9950 0.9975 200 |
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kale 0.9268 0.9500 0.9383 200 |
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longbeans 0.9850 0.9850 0.9850 200 |
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watermelon 0.9252 0.9900 0.9565 200 |
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mango 0.9239 0.9100 0.9169 200 |
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waterapple 0.8807 0.9600 0.9187 200 |
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accuracy 0.9292 6000 |
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macro avg 0.9282 0.9292 0.9275 6000 |
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weighted avg 0.9282 0.9292 0.9275 6000 |
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``` |
