refactoring

image_prediction/classifier/image_classifier.py

@@ -1,7 +1,8 @@
 from itertools import chain
-from typing import List
+from typing import Iterable
 
 from PIL.Image import Image
+from funcy import rcompose
 
 from image_prediction.classifier.classifier import Classifier
 from image_prediction.estimator.preprocessor.preprocessor import Preprocessor
@@ -10,11 +11,14 @@ from image_prediction.utils import chunk_iterable
 
 
 class ImageClassifier:
-    def __init__(self, estimator: Classifier, preprocessor: Preprocessor = None):
-        self.estimator = estimator
+    """Combines a classifier with a preprocessing pipeline: Receives images, chunks into batches, converts to tensors,
+    applies transformations and finally sends to internal classifier.
+    """
+    def __init__(self, classifier: Classifier, preprocessor: Preprocessor = None):
+        self.estimator = classifier
         self.preprocessor = preprocessor if preprocessor else BasicPreprocessor()
-        self.pipe = lambda batch: self.estimator(self.preprocessor(batch))
+        self.pipe = rcompose(self.preprocessor, self.estimator)
 
-    def predict(self, images: List[Image], batch_size=16):
+    def predict(self, images: Iterable[Image], batch_size=16):
         batches = chunk_iterable(images, chunk_size=batch_size)
         return chain(*map(self.pipe, batches))

image_prediction/utils.py

@@ -1,6 +1,7 @@
 import logging
 import tempfile
 from contextlib import contextmanager
+from functools import reduce
 from itertools import takewhile, starmap, islice, repeat
 from operator import truth
 
@@ -74,3 +75,8 @@ def show_banner():
 @export
 def chunk_iterable(iterable, chunk_size):
     return takewhile(truth, map(tuple, starmap(islice, repeat((iter(iterable), chunk_size)))))
+
+
+def compose(func, *funcs):
+    funcs = [func, *funcs]
+    return lambda x: reduce(lambda acc, f: f(acc), funcs, x)

requirements.txt

@@ -19,5 +19,5 @@ PDFNetPython3~=9.1.0
 Pillow~=8.3.2
 PyYAML~=5.4.1
 scikit_learn~=0.24.2
-
-pytest~=7.1.0
+pytest~=7.1.0
+funcy==1.17

test/unit_tests/utils_test.py

@@ -0,0 +1,6 @@
+from funcy import rcompose
+
+
+def test_rcompose():
+    f = rcompose(lambda x: x ** 2, str, lambda x: x * 2)
+    assert f(3) == "99"