Add corrective labels_2022

data/all_dataset_params.json

@@ -808,6 +808,56 @@
             12
         ]
     },
+    "geowiki_landcover_2017,Kenya,Mali,Mali_lower_CEO_2019,Mali_upper_CEO_2019,Togo,Rwanda,Uganda,open_buildings,digitalearthafrica_eastern,digitalearthafrica_sahel,Ethiopia,Ethiopia_Tigray_2020,Ethiopia_Tigray_2021,Ethiopia_Bure_Jimma_2019,Ethiopia_Bure_Jimma_2020,Malawi_CEO_2020,Malawi_CEO_2019,Malawi_FAO,Malawi_FAO_corrected,Zambia_CEO_2019,Tanzania_CEO_2019,Namibia_corrective_labels_2020,Malawi_corrected,Namibia_CEO_2020,Namibia_WFP,Sudan_Blue_Nile_CEO_2019,Hawaii_CEO_2020,Senegal_CEO_2022,HawaiiAgriculturalLandUse2020,KenyaCEO2019,HawaiiCorrective2020,HawaiiCorrectiveGuided2020,MalawiCorrectiveLabels2020,SudanBlueNileCEO2020,SudanBlueNileCorrectiveLabels2019,EthiopiaTigrayCorrective2020,SudanAlGadarefCEO2019,MaliStratifiedCEO2019,SudanAlGadarefCEO2020,NamibiaNorthStratified2020,Namibia_field_samples_22_23,SudanGedarefDarfurAlJazirah2022,Uganda_NorthCEO2022,UgandaNorthCorrective2022_February_2022": {
+        "normalizing_dict": {
+            "mean": [
+                -11.255516637559671,
+                -18.33725418405467,
+                1436.4352778557773,
+                1402.4272840659528,
+                1426.5960525466035,
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+                2797.8451262347635,
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+                2495.1758697170035,
+                1659.2587797822239,
+                290.3950519378234,
+                0.004524519648932057,
+                863.1242659143134,
+                5.64862939589125,
+                0.3389100980227688
+            ],
+            "std": [
+                4.15337809763524,
+                5.063815336282717,
+                995.2868060874501,
+                966.5722368300801,
+                1161.837450348849,
+                1109.9708883027095,
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+                1057.7198269424493,
+                35.65957791987571,
+                0.013440213523815855,
+                646.8263409336159,
+                7.10792465117609,
+                0.22962240493696942
+            ]
+        },
+        "train_num_timesteps": [
+            12
+        ],
+        "val_num_timesteps": [
+            12
+        ]
+    },
     "geowiki_landcover_2017,Kenya,Mali,Mali_lower_CEO_2019,Mali_upper_CEO_2019,Togo,Rwanda,Uganda,open_buildings,digitalearthafrica_eastern,digitalearthafrica_sahel,Ethiopia,Ethiopia_Tigray_2020,Ethiopia_Tigray_2021,Ethiopia_Bure_Jimma_2019,Ethiopia_Bure_Jimma_2020,Malawi_CEO_2020,Malawi_CEO_2019,Malawi_FAO,Malawi_FAO_corrected,Zambia_CEO_2019,Tanzania_CEO_2019,Namibia_corrective_labels_2020,Malawi_corrected,Namibia_CEO_2020,Namibia_WFP,Sudan_Blue_Nile_CEO_2019,Hawaii_CEO_2020,Senegal_CEO_2022,HawaiiAgriculturalLandUse2020,KenyaCEO2019,HawaiiCorrective2020,HawaiiCorrectiveGuided2020,MalawiCorrectiveLabels2020,SudanBlueNileCEO2020,SudanBlueNileCorrectiveLabels2019,EthiopiaTigrayCorrective2020,SudanAlGadarefCEO2019,MaliStratifiedCEO2019,SudanAlGadarefCEO2020,NamibiaNorthStratified2020,Namibia_field_samples_22_23,SudanGedarefDarfurAlJazirah2022_February_2022": {
         "normalizing_dict": {
             "mean": [

data/datasets.dvc

@@ -1,6 +1,6 @@
 outs:
-- md5: 63c6f22459e60941aa459671fbff891b.dir
-  size: 671350235
-  nfiles: 48
+- md5: 9041fef59c732efe6fa78ba3ac8a53fd.dir
+  size: 674094424
+  nfiles: 49
   path: datasets
   hash: md5

data/models.dvc

@@ -1,6 +1,6 @@
 outs:
-- md5: f6d9020a5f9aa7b02a6982af93c571f1.dir
-  size: 77720213
-  nfiles: 60
+- md5: d2b001db28f37466ed4a787d483319a2.dir
+  size: 79241780
+  nfiles: 62
   path: models
   hash: md5

data/models.json

@@ -322,6 +322,23 @@
             "roc_auc_score": 0.8647
         }
     },
+    "Uganda_North_2022_V2": {
+        "params": "https://wandb.ai/nasa-harvest/crop-mask/runs/0ngyleht",
+        "test_metrics": {
+            "accuracy": 0.6388,
+            "f1_score": 0.5341,
+            "precision_score": 0.3917,
+            "recall_score": 0.8393,
+            "roc_auc_score": 0.8004
+        },
+        "val_metrics": {
+            "accuracy": 0.6886,
+            "f1_score": 0.6321,
+            "precision_score": 0.488,
+            "recall_score": 0.8971,
+            "roc_auc_score": 0.8259
+        }
+    },
     "Zambia_2019": {
         "params": "https://wandb.ai/nasa-harvest/crop-mask/runs/rnhjdn44",
         "test_metrics": {

data/raw.dvc

@@ -1,6 +1,6 @@
 outs:
-- md5: c033b32e0901a197d9f743c8329b24ae.dir
-  size: 443888649
-  nfiles: 387
+- md5: 4e3d5d0013c41fca834ac18be36710fc.dir
+  size: 443967181
+  nfiles: 388
   path: raw
   hash: md5

data/report.txt

@@ -422,3 +422,10 @@ eo_data_complete    1000
 ✔ training amount: 387, positive class: 20.9%
 ✔ validation amount: 294, positive class: 23.1%
 ✔ testing amount: 319, positive class: 17.6%
+
+
+
+UgandaNorthCorrective2022 (Timesteps: 19)
+----------------------------------------------------------------------------
+eo_data_complete    615
+✔ training amount: 615, positive class: 24.4%

datasets.py

@@ -448,6 +448,16 @@ def load_labels(self) -> pd.DataFrame:
         return df
 
 
+class UgandaNorthCorrective2022(LabeledDataset):
+    def load_labels(self) -> pd.DataFrame:
+        df = pd.read_csv(raw_dir / "Uganda_North_Corrective_2022.csv")
+        df.rename(columns={"latitude": LAT, "longitude": LON}, inplace=True)
+        df[CLASS_PROB] = (df["Wrong value"] == 0).astype(int)
+        df[START], df[END] = date(2022, 1, 1), date(2023, 7, 31)
+        df[SUBSET] = "training"
+        return df
+
+
 datasets: List[LabeledDataset] = [
     CustomLabeledDataset(
         dataset="geowiki_landcover_2017",
@@ -1232,6 +1242,7 @@ def load_labels(self) -> pd.DataFrame:
     Namibia_field_samples_22_23(),
     SudanGedarefDarfurAlJazirah2022(),
     Uganda_NorthCEO2022(),
+    UgandaNorthCorrective2022(),
 ]
 
 if __name__ == "__main__":