update apply to include mask

hooknet/inference/apply.py

@@ -11,7 +11,7 @@
 )
 from tqdm import tqdm
 from wholeslidedata.interoperability.asap.masks import MaskType
-# from hooknet.inference.writing import create_writers
+from hooknet.inference.writing import create_writers
 
 
 
@@ -24,24 +24,24 @@ def execute_inference_single(
     tmp_folder,
 ):
 
-    # print("Init writers...")
-    # writers = create_writers(
-    #     image_path=image_path,
-    #     files=files,
-    #     output_folder=output_folder,
-    #     tmp_folder=tmp_folder,
-    # )
+    print("Init writers...")
+    writers = create_writers(
+        image_path=image_path,
+        files=files,
+        output_folder=output_folder,
+        tmp_folder=tmp_folder,
+    )
 
-    # if not writers:
-    #     print(f"Nothing to process for image {image_path}")
-    #     return
+    if not writers:
+        print(f"Nothing to process for image {image_path}")
+        return
 
     prediction_times = []
     batch_times = []
     print("Applying...")
     index = 0
     batch_time = -1
-    for x_batch, info in tqdm(iterator):
+    for x_batch, y_batch, info in tqdm(iterator):
         if index > 0:
             batch_times.append(time.time()-batch_time)
             print("batch time", batch_times[-1])
@@ -58,23 +58,23 @@ def execute_inference_single(
                 info["y"] - model.output_shape[0] // 4,
             )
 
-            # for writer in writers:
-            #     writer.write_tile(
-            #         tile=prediction,
-            #         coordinates=(int(c), int(r)),
-            #         mask=y_batch[idx][0],
-            #     )
+            for writer in writers:
+                writer.write_tile(
+                    tile=prediction,
+                    coordinates=(int(c), int(r)),
+                    mask=y_batch[idx][0],
+                )
         index += 1
         batch_time = time.time()
 
 
     print(f"average batch time: {np.mean(batch_times)}")
     print(f"average prediction time: {np.mean(prediction_times)}")
 
-    # # save predictions
-    # print("Saving...")
-    # for writer in writers:
-    #     writer.save()
+    # save predictions
+    print("Saving...")
+    for writer in writers:
+        writer.save()