feat(crafter): add resize crafters

jina/executors/crafters/image/__init__.py

@@ -17,12 +17,12 @@ def _load_image(self, blob: 'np.ndarray'):
         return Image.fromarray(blob.astype('uint8'))
 
     @staticmethod
-    def _resize_short(img, target_size):
-        from PIL.Image import LANCZOS
+    def _resize_short(img, target_size, how='LANCZOS'):
+        import PIL.Image as Image
         percent = float(target_size) / min(img.size[0], img.size[1])
         resized_width = int(round(img.size[0] * percent))
         resized_height = int(round(img.size[1] * percent))
-        img = img.resize((resized_width, resized_height), LANCZOS)
+        img = img.resize((resized_width, resized_height), getattr(Image, how))
         return img
 
     @staticmethod

jina/executors/crafters/image/normalize.py

@@ -36,7 +36,7 @@ def __init__(self,
         self.img_mean = np.array(img_mean).reshape((1, 1, 3))
         self.img_std = np.array(img_std).reshape((1, 1, 3))
 
-    def craft(self, blob, chunk_id, doc_id, *args, **kwargs) -> Dict:
+    def craft(self, blob: 'np.ndarray', chunk_id: int, doc_id: int, *args, **kwargs) -> Dict:
         """
 
         :param blob: the ndarray of the image with the color channel at the last axis

jina/executors/crafters/image/resize.py

@@ -0,0 +1,24 @@
+import numbers
+import numpy as np
+from . import ImageChunkCrafter
+from typing import Union, Tuple, List, Dict
+
+
+class ImageResizer(ImageChunkCrafter):
+    def __init__(self,
+                 output_dim: int,
+                 how='BILINEAR',
+                 *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if isinstance(output_dim, numbers.Number):
+            self.output_dim = output_dim
+        else:
+            raise ValueError('output_dim {} should be an integer'.format(output_dim))
+        self.how = how
+
+    def craft(self, blob: 'np.ndarray', chunk_id: int, doc_id: int, *args, **kwargs) -> Dict:
+        raw_img = self._load_image(blob)
+        processed_img = self._resize_short(raw_img, self.output_dim, self.how)
+        return dict(
+            doc_id=doc_id, offset=0, weight=1., blob=np.asarray(processed_img).astype('float32'))
+

tests/executors/crafters/image/test_normalize.py

@@ -6,7 +6,7 @@
 
 class MyTestCase(JinaImageTestCase):
     def test_transform_results(self):
-        img_size = 224
+        img_size = 217
         crafter = ImageNormalizer(output_dim=img_size)
         img_array = self.create_test_img_array(img_size, img_size)
         crafted_chunk = crafter.craft(img_array, chunk_id=0, doc_id=0)

tests/executors/crafters/image/test_resize.py

@@ -0,0 +1,19 @@
+import unittest
+
+from jina.executors.crafters.image.resize import ImageResizer
+from tests.executors.crafters.image import JinaImageTestCase
+
+
+class MyTestCase(JinaImageTestCase):
+    def test_resize(self):
+        img_width = 20
+        img_height = 17
+        output_dim = 71
+        crafter = ImageResizer(output_dim=output_dim)
+        img_array = self.create_test_img_array(img_width, img_height)
+        crafted_chunk = crafter.craft(img_array, chunk_id=0, doc_id=0)
+        self.assertEqual(min(crafted_chunk['blob'].shape[:-1]), output_dim)
+
+
+if __name__ == '__main__':
+    unittest.main()