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@@ -70,9 +70,21 @@ yolov5 train --data data.yaml --img 640 --batch 16 --weights KaraAgroAI/CADI-AI
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  ### Model performance
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- | Precision | Recall | mAP50 | mAP50-95 |
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- | --- | --- | --- | --- |
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- | 0.663 | 0.632 | 0.648 | 0.291 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Example prediction
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  ### Model performance
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+ | Class | Precision | Recall | mAP@50 | mAP@50-95 |
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+ | --- | --- | --- | --- | --- |
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+ | all | 0.663 | 0.632 | 0.648 | 0.291 |
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+ | insect | 0.794 | 0.811 | 0.815 | 0.39 |
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+ | abiotic | 0.682 | 0.514 | 0.542 | 0.237 |
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+ | disease | 0.594 | 0.571 | 0.588 | 0.248 |
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+
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+ ### Limitations of the Model
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+ The model has a few limitations that affect its performance in distinguishing between the disease class and the abiotic class.
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+ The primary challenge lies in the similarity between these two classes within a typical farm setting.
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+ The model may encounter difficulties in accurately differentiating between them due to their overlapping characteristics.
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+ This limitation is an inherent challenge in the dataset and can impact the model's accuracy when classifying these classes.
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+ However, it is worth noting that the model exhibits strong performance when it comes to the insect class.
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+ This is attributed to the distinct characteristics of insect class, which make them easier to identify and classify accurately.
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  ### Example prediction
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