Tabular Classification
Scikit-learn
Joblib
remote-sensing
tree-canopy
sentinel-2
philippines
metro-manila
civic-technology
Instructions to use xmpuspus/leaves-ph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use xmpuspus/leaves-ph with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("xmpuspus/leaves-ph", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
File size: 1,510 Bytes
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"n": 656,
"n_canopy": 115,
"baseline_ndvi>0.62": {
"precision": 0.691,
"recall": 0.669,
"f1": 0.68,
"iou": 0.515,
"accuracy": 0.936,
"pred_canopy_pct": 9.793,
"truth_canopy_pct": 10.114
},
"ndvi_only": {
"threshold": 0.54,
"precision": 0.622,
"recall": 0.678,
"f1": 0.649,
"iou": 0.481,
"accuracy": 0.926,
"pred_canopy_pct": 11.025,
"truth_canopy_pct": 10.114
},
"ndvi+dw": {
"threshold": 0.2,
"precision": 0.519,
"recall": 0.758,
"f1": 0.616,
"iou": 0.445,
"accuracy": 0.904,
"pred_canopy_pct": 14.774,
"truth_canopy_pct": 10.114
},
"ndvi+dw+esa": {
"threshold": 0.26,
"precision": 0.708,
"recall": 0.77,
"f1": 0.738,
"iou": 0.584,
"accuracy": 0.945,
"pred_canopy_pct": 10.992,
"truth_canopy_pct": 10.114
},
"ndvi+dw+meta+esa": {
"threshold": 0.38,
"precision": 0.716,
"recall": 0.821,
"f1": 0.765,
"iou": 0.619,
"accuracy": 0.949,
"pred_canopy_pct": 11.598,
"truth_canopy_pct": 10.114
},
"ndvi+dw+meta+esa+density": {
"threshold": 0.24,
"precision": 0.65,
"recall": 0.808,
"f1": 0.721,
"iou": 0.563,
"accuracy": 0.937,
"pred_canopy_pct": 12.579,
"truth_canopy_pct": 10.114
},
"all_minus_ndvi": {
"threshold": 0.72,
"precision": 0.659,
"recall": 0.607,
"f1": 0.632,
"iou": 0.462,
"accuracy": 0.929,
"pred_canopy_pct": 9.314,
"truth_canopy_pct": 10.114
}
} |