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Improve kelp presence detection for RGB imagery (#123)
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* Update presence model

* Update stats
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tayden authored Jul 23, 2024
1 parent 80b772c commit b414e94
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18 changes: 9 additions & 9 deletions docs/about.md
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Expand Up @@ -211,25 +211,25 @@ $$

| Class | IoU | Precision | Recall | Accuracy |
|:---------|-------:|----------:|-------:|---------:|
| Kelp | 0.6593 | 0.8145 | 0.7804 | - |
| Not Kelp | 0.9885 | 0.9939 | 0.9945 | - |
| *Mean* | 0.8239 | 0.9042 | 0.8875 | 0.9892 |
| Kelp | 0.7026 | 0.7525 | 0.9122 | - |
| Not Kelp | 0.9862 | 0.9978 | 0.9883 | - |
| *Mean* | 0.8444 | 0.8752 | 0.9503 | 0.9869 |

=== "Validation split"

| Class | IoU | Precision | Recall | Accuracy |
|:---------|-------:|----------:|-------:|---------:|
| Kelp | 0.6964 | 0.7585 | 0.8917 | - |
| Not Kelp | 0.9857 | 0.9969 | 0.9886 | - |
| *Mean* | 0.8410 | 0.8777 | 0.9402 | 0.9865 |
| Kelp | 0.6892 | 0.8317 | 0.8031 | - |
| Not Kelp | 0.9635 | 0.9808 | 0.9820 | - |
| *Mean* | 0.8263 | 0.9062 | 0.8926 | 0.9671 |

=== "Train split"

| Class | IoU | Precision | Recall | Accuracy |
|:---------|-------:|----------:|-------:|---------:|
| Kelp | 0.7786 | 0.8510 | 0.8980 | - |
| Not Kelp | 0.9716 | 0.9889 | 0.9822 | - |
| *Mean* | 0.8751 | 0.9200 | 0.9401 | 0.9757 |
| Kelp | 0.7674 | 0.8446 | 0.8906 | - |
| Not Kelp | 0.9724 | 0.9897 | 0.9824 | - |
| *Mean* | 0.8699 | 0.9172 | 0.9365 | 0.9757 |

=== "RGBI"

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2 changes: 1 addition & 1 deletion kelp_o_matic/models.py
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Expand Up @@ -93,7 +93,7 @@ class KelpRGBPresenceSegmentationModel(_Model):
all_black_val = 0

torchscript_path = (
"UNetPlusPlus_EfficientNetV2_m_kelp_presence_rgb_jit_dice=0.8677.pt"
"UNetPlusPlus_EfficientNetV2_m_kelp_presence_rgb_jit_dice=0.8703.pt"
)

def post_process(self, x: "torch.Tensor") -> "np.ndarray":
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