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
| { | |
| "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 | |
| } | |
| } |