diff --git a/image_prediction/pipeline.py b/image_prediction/pipeline.py
index 6d29ac7..e8114b8 100644
--- a/image_prediction/pipeline.py
+++ b/image_prediction/pipeline.py
@@ -48,6 +48,7 @@ class Pipeline:
         split = compose(star(parallel(*map(lift, (first, first, second)))), rpartial(tee, 3))
         classify = compose(chain.from_iterable, lift(classifier), partial(chunks, batch_size))
         pairwise_apply = compose(star, parallel)
+        # TODO: use signal compress
         join = compose(starlift(lambda prd, rpr, mdt: {"classification": prd, **mdt, "representation": rpr}), star(zip))
 
         #                       />--classify--\
diff --git a/image_prediction/redai_adapter/model.py b/image_prediction/redai_adapter/model.py
index c5450f5..fabcb78 100644
--- a/image_prediction/redai_adapter/model.py
+++ b/image_prediction/redai_adapter/model.py
@@ -9,6 +9,7 @@ class PredictionModelHandle:
     """Simplifies usage of ModelHandle instances for prediction purposes."""
 
     def __init__(self, model_handle):
+        # TODO: extract signal
         self.__predict = rcompose(model_handle.prep_images, model_handle.model.predict)
 
     def predict(self, *args, **kwargs):
diff --git a/image_prediction/redai_adapter/model_wrapper.py b/image_prediction/redai_adapter/model_wrapper.py
index 776931e..89aa49b 100644
--- a/image_prediction/redai_adapter/model_wrapper.py
+++ b/image_prediction/redai_adapter/model_wrapper.py
@@ -32,6 +32,7 @@ class ModelWrapper(abc.ABC):
 
     def prep_images(self, images):
         images = map(self.__resize_and_convert, images)
+        # TODO: signal, images = ...
         tensor = self.__images_to_tensor(images)
         tensor = self.__preprocess_tensor(tensor)
 
diff --git a/image_prediction/stitching/merging.py b/image_prediction/stitching/merging.py
index 2c3fbc4..7f4442c 100644
--- a/image_prediction/stitching/merging.py
+++ b/image_prediction/stitching/merging.py
@@ -184,6 +184,7 @@ def concat_images(im1: Image, im2: Image, metadata: dict, axis):
 
     for im, offset in zip(images, offsets):
         box = (offset, 0) if not axis else (0, offset)
+        # TODO: replace image that cannot be opened with white image of same size
         im_aggr.paste(im, box=box)
 
     return im_aggr