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README.md
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The dataset originally came with 7.3k images, but I narrowed it down to 2.5k images
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Each class was pretty balanced for images, with ahids being the only one not in the 400s for photos
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Below are the images per class:
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Classes were reduced from 19 to 6 for better focus, classes were selected on how common its found in crops, and relevance to agriculture.
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Annotation Process:
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Dataset was reviewed and cleaned using roboflow, approximately reveiwed 50 images for annotations. Corrections like misidentified labels, or
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Image size: 640x640
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Evaluation Results:
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mAP50
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Per Class Performance (Average Precision):
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The dataset originally came with 7.3k images, but I narrowed it down to 2.5k images
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Each class was pretty balanced for images, with ahids being the only one not in the 400s for photos
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Below are the images per class:
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| Class | Image Count |
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|-------------|------------|
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| Ant | 497 |
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| Aphid | 283 |
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| Beetle | 413 |
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| Caterpillar | 409 |
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| Grasshopper | 483 |
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| Weevil | 480 |
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Classes were reduced from 19 to 6 for better focus, classes were selected on how common its found in crops, and relevance to agriculture.
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Annotation Process:
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Dataset was reviewed and cleaned using roboflow, approximately reveiwed 50 images for annotations. Corrections like misidentified labels, or
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Image size: 640x640
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Evaluation Results:
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| Metric | Value |
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|------------|-------|
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| mAP50 | 0.676 |
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| mAP50-95 | 0.345 |
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| Precision | 0.726 |
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| Recall | 0.659 |
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Per Class Performance (Average Precision):
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| Class | Average Precision (AP) |
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|-------------|------------------------|
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| Ant | 0.263 |
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| Aphid | 0.176 |
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| Beetle | 0.370 |
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| Caterpillar | 0.172 |
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| Grasshopper | 0.420 |
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| Weevil | 0.675 |
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