fixed evaluator

VMarsocci · Oct 13, 2024 · fc50576 · fc50576
1 parent 8c3a376
commit fc50576
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Showing 3 changed files with 12 additions and 59 deletions.
diff --git a/pangaea/datasets/sen1floods11.py b/pangaea/datasets/sen1floods11.py
@@ -14,24 +14,8 @@ class Sen1Floods11(RawGeoFMDataset):
 
     def __init__(
         self,
-        split: str,
-        dataset_name: str,
-        multi_modal: bool,
-        multi_temporal: int,
-        root_path: str,
-        classes: list,
-        num_classes: int,
-        ignore_index: int,
-        img_size: int,
-        bands: dict[str, list[str]],
-        distribution: list[int],
-        data_mean: dict[str, list[str]],
-        data_std: dict[str, list[str]],
-        data_min: dict[str, list[str]],
-        data_max: dict[str, list[str]],
-        download_url: str,
-        auto_download: bool,
-        gcs_bucket: str, 
+        gcs_bucket: str,
+        **kwargs
     ):
         """Initialize the Sen1Floods11 dataset.
         Link: https://github.com/cloudtostreet/Sen1Floods11
@@ -67,45 +51,12 @@ def __init__(
 
         self.gcs_bucket = gcs_bucket
 
-        super(Sen1Floods11, self).__init__(
-            split=split,
-            dataset_name=dataset_name,
-            multi_modal=multi_modal,
-            multi_temporal=multi_temporal,
-            root_path=root_path,
-            classes=classes,
-            num_classes=num_classes,
-            ignore_index=ignore_index,
-            img_size=img_size,
-            bands=bands,
-            distribution=distribution,
-            data_mean=data_mean,
-            data_std=data_std,
-            data_min=data_min,
-            data_max=data_max,
-            download_url=download_url,
-            auto_download=auto_download,
-        )
-
-        self.root_path = root_path
-        self.classes = classes
-        self.split = split
-
-        self.data_mean = data_mean
-        self.data_std = data_std
-        self.data_min = data_min
-        self.data_max = data_max
-        self.classes = classes
-        self.img_size = img_size
-        self.distribution = distribution
-        self.num_classes = num_classes
-        self.ignore_index = ignore_index
-        self.download_url = download_url
-        self.auto_download = auto_download
+        super(Sen1Floods11, self).__init__(**kwargs)
+
 
         self.split_mapping = {'train': 'train', 'val': 'valid', 'test': 'test'}
 
-        split_file = os.path.join(self.root_path, "v1.1", f"splits/flood_handlabeled/flood_{self.split_mapping[split]}_data.csv")
+        split_file = os.path.join(self.root_path, "v1.1", f"splits/flood_handlabeled/flood_{self.split_mapping[self.split]}_data.csv")
         metadata_file = os.path.join(self.root_path, "v1.1", "Sen1Floods11_Metadata.geojson")
         data_root = os.path.join(self.root_path, "v1.1", "data/flood_events/HandLabeled/")
 
@@ -153,18 +104,19 @@ def __getitem__(self, index):
 
         s2_image = torch.from_numpy(s2_image).float()
         s1_image = torch.from_numpy(s1_image).float()   
-        target = torch.from_numpy(target)
+        target = torch.from_numpy(target).long()
 
         output = {
             'image': {
-                'optical': s2_image,
-                'sar' : s1_image,
+                'optical': s2_image.unsqueeze(1),
+                'sar' : s1_image.unsqueeze(1),
             },
             'target': target,
             'metadata': {
                 "timestamp": timestamp,
             }
         }
+
         return output
 
     @staticmethod

diff --git a/pangaea/engine/evaluator.py b/pangaea/engine/evaluator.py
@@ -110,7 +110,7 @@ def sliding_inference(model, img, input_size, output_shape=None, stride=None, ma
             pred_ = model.forward(img_, output_shape=(input_size, input_size))
             pred.append(pred_)
         pred = torch.cat(pred, dim=0)
-        pred = pred.view(b, num_crops_per_img, -1, input_size, input_size)
+        pred = pred.view(num_crops_per_img, b, -1, input_size, input_size).transpose(0, 1)
 
         merged_pred = torch.zeros((b, pred.shape[2], height, width), device=pred.device)
         pred_count = torch.zeros((b, height, width), dtype=torch.long, device=pred.device)
@@ -401,4 +401,4 @@ def log_metrics(self, metrics):
         self.logger.info(header + mse + rmse)
 
         if self.use_wandb:
-            wandb.log({f"{self.split}_MSE": metrics["MSE"], f"{self.split}_RMSE": metrics["RMSE"]})
+            wandb.log({f"{self.split}_MSE": metrics["MSE"], f"{self.split}_RMSE": metrics["RMSE"]})
diff --git a/pretrained_models b/pretrained_models
@@ -0,0 +1 @@
+../workspace/pangaea-bench/pretrained_models/