Update config.json

config.json

@@ -1,71 +1,71 @@
-{
-    "model_type": "unet_with_spatial_attention",
-    "input_shape": [4, 384, 384],
-    "num_classes": 1,
-    "architecture": {
-      "encoder": {
-        "downsample_blocks": [
-          {"in_channels": 4, "out_channels": 32},
-          {"in_channels": 32, "out_channels": 64},
-          {"in_channels": 64, "out_channels": 128}
-        ],
-        "bottleneck": {"in_channels": 128, "out_channels": 256}
-      },
-      "decoder": {
-        "upsample_blocks": [
-          {"in_channels": 256, "out_channels": 128},
-          {"in_channels": 128, "out_channels": 64},
-          {"in_channels": 64, "out_channels": 32}
-        ]
-      },
-      "spatial_attention": {
-        "conv": {"in_channels": 2, "out_channels": 1, "kernel_size": 3, "padding": 1}
-      },
-      "output": {"in_channels": 32, "out_channels": 1, "kernel_size": 1}
-    },
-    "training": {
-      "optimizer": "Adam",
-      "learning_rate": 0.0008,
-      "weight_decay": 1e-5,
-      "loss_function": "BCEWithLogitsLoss",
-      "batch_size": 8,
-      "epochs": 15,
-      "patience": 4,
-      "scheduler": "ReduceLROnPlateau",
-      "scheduler_params": {
-        "mode": "min",
-        "factor": 0.1,
-        "patience": 2
-      }
-    },
-    "metrics": {
-      "validation": {
-        "Jaccard_index": 0.8897,
-        "Precision": 0.9445,
-        "Recall": 0.9328,
-        "Specificity": 0.9797,
-        "Overall_Accuracy": 0.9706
-      }
-    },
-    "data": {
-      "dataset_path": "../input/38cloud-cloud-segmentation-in-satellite-images/38-Cloud_training",
-      "input_channels": ["red", "green", "blue", "nir"],
-      "target": "binary_cloud_mask",
-      "normalization": "divide_by_max_value_uint16",
-      "augmentation": false,
-      "train_val_split": 0.8,
-      "image_size": [384, 384]
-    },
-    "misc": {
-      "device": "cuda_if_available",
-      "grad_clip": 1.0,
-      "threshold": 0.5
-    },
-    "output": {
-      "model_file": "pytorch_model.bin",
-      "visualization": {
-        "samples": 5,
-        "types": ["original_image", "ground_truth_mask", "predicted_mask"]
-      }
-    }
+{
+    "model_type": "unet",
+    "input_shape": [4, 384, 384],
+    "num_classes": 1,
+    "architecture": {
+      "encoder": {
+        "downsample_blocks": [
+          {"in_channels": 4, "out_channels": 32},
+          {"in_channels": 32, "out_channels": 64},
+          {"in_channels": 64, "out_channels": 128}
+        ],
+        "bottleneck": {"in_channels": 128, "out_channels": 256}
+      },
+      "decoder": {
+        "upsample_blocks": [
+          {"in_channels": 256, "out_channels": 128},
+          {"in_channels": 128, "out_channels": 64},
+          {"in_channels": 64, "out_channels": 32}
+        ]
+      },
+      "spatial_attention": {
+        "conv": {"in_channels": 2, "out_channels": 1, "kernel_size": 3, "padding": 1}
+      },
+      "output": {"in_channels": 32, "out_channels": 1, "kernel_size": 1}
+    },
+    "training": {
+      "optimizer": "Adam",
+      "learning_rate": 0.0008,
+      "weight_decay": 1e-5,
+      "loss_function": "BCEWithLogitsLoss",
+      "batch_size": 8,
+      "epochs": 15,
+      "patience": 4,
+      "scheduler": "ReduceLROnPlateau",
+      "scheduler_params": {
+        "mode": "min",
+        "factor": 0.1,
+        "patience": 2
+      }
+    },
+    "metrics": {
+      "validation": {
+        "Jaccard_index": 0.8897,
+        "Precision": 0.9445,
+        "Recall": 0.9328,
+        "Specificity": 0.9797,
+        "Overall_Accuracy": 0.9706
+      }
+    },
+    "data": {
+      "dataset_path": "../input/38cloud-cloud-segmentation-in-satellite-images/38-Cloud_training",
+      "input_channels": ["red", "green", "blue", "nir"],
+      "target": "binary_cloud_mask",
+      "normalization": "divide_by_max_value_uint16",
+      "augmentation": false,
+      "train_val_split": 0.8,
+      "image_size": [384, 384]
+    },
+    "misc": {
+      "device": "cuda_if_available",
+      "grad_clip": 1.0,
+      "threshold": 0.5
+    },
+    "output": {
+      "model_file": "pytorch_model.bin",
+      "visualization": {
+        "samples": 5,
+        "types": ["original_image", "ground_truth_mask", "predicted_mask"]
+      }
+    }
 }