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--- |
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license: apache-2.0 |
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tags: |
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- UAV |
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- Deadwood |
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- detectron2 |
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--- |
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## Model description |
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This model is trained for detecting both standing and fallen deadwood from UAV RGB images. More thorough description is available on [https://mayrajeo.github.io/maskrcnn-deadwood](https://mayrajeo.github.io/maskrcnn-deadwood). |
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## Training data |
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The model was trained on expert-annotated deadwood data, acquired on during leaf-on season 16.-17.7.2019 from Hiidenportti, Sotkamo, Eastern-Finland. The ground resolution for the data varied between 3.9 and 4.4cm. In addition, the model was tested with data collected from Evo, Hämeenlinna, Southern-Finland, acquired on 11.7.2018. The data from Evo was used only for testing the models. |
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## Metrics |
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|Metric|Hiidenportti|Evo| |
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|------|------------|---| |
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|Patch AP50|0.704|0.519| |
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|Patch AP|0.366|0.252| |
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|Patch AP groundwood|0.326|0.183| |
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|Patch AP uprightwood|0.406|0.321| |
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|Scene AP50|0.683|0.511| |
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|Scene AP|0.341|0.236| |
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|Scene AP groundwood|0.246|0.160| |
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|Scene AP uprightwood|0.436|0.311| |
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## How to use |
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```python |
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from detectron2.engine import DefaultPredictor |
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from detectron2.config import get_cfg |
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from detectron2.data import build_detection_test_loader |
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import cv2 |
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cfg = get_cfg() |
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cfg.merge_from_file(<path_to_model_config>) |
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cfg.OUTPUT_DIR = '<path_to_output>' |
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cfg.MODEL.WEIGHTS = '<path_to_weights>' |
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cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 # score threshold for detections |
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predictor = DefaultPredictor(cfg) |
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img = cv2.imread('<path_to_image_patch>') |
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outputs = predictor(image) |
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``` |
