feat: display binary mask on top of prediction

Former-commit-id: a81b30919c6ef0998617822fd57e54209dcb2cfa [formerly 9f9cf75289c5f731dc6c93f86dff237aed88722c]
Former-commit-id: d7272aefcf16e2e22081811c0452d7cb7e0980f3

src/train.py

@@ -13,6 +13,10 @@ from unet import UNet
 from utils.dice import dice_coeff
 from utils.paste import RandomPaste
 
+class_labels = {
+    1: "sphere",
+}
+
 
 def main():
     # setup logging
@@ -215,14 +219,28 @@ def main():
 
                 # save the last validation batch to table
                 table = wandb.Table(columns=["ID", "image", "ground truth", "prediction"])
-                for i, (img, mask, pred) in enumerate(
+                for i, (img, mask, pred, pred_bin) in enumerate(
                     zip(
                         images.to("cpu"),
                         masks_true.to("cpu"),
                         masks_pred.to("cpu"),
+                        masks_pred_bin.to("cpu").squeeze().int().numpy(),
                     )
                 ):
-                    table.add_data(i, wandb.Image(img), wandb.Image(mask), wandb.Image(pred))
+                    table.add_data(
+                        i,
+                        wandb.Image(img),
+                        wandb.Image(mask),
+                        wandb.Image(
+                            pred,
+                            masks={
+                                "predictions": {
+                                    "mask_data": pred_bin,
+                                    "class_labels": class_labels,
+                                },
+                            },
+                        ),
+                    )
 
                 # log validation metrics
                 wandb.log(