Change from skimage.transform.resize to cv2.resize

To make the process of cropping and resizing images go faster, switch
from the resize function in skimage.transform to the resize function
in cv2 if cv2 is available on the system, otherwise stick with
skimage.transform.resize.

Author: krikru

README.md

@@ -92,7 +92,7 @@ The performance of each model variant using the pre-trained weights converted fr
 
 * `Keras >= 2.2.0` / `TensorFlow >= 1.12.0`
 * `keras_applications >= 1.0.7`
-* `scikit-image`
+* `opencv >= 3.4.2` or `scikit-image` (for resizing images; `opencv` seems to be faster)
 
 ### Installing from the source
 

efficientnet/preprocessing.py

@@ -13,19 +13,33 @@
 # limitations under the License.
 # ==============================================================================
 import numpy as np
-from skimage.transform import resize
+try:
+    import cv2
+except ModuleNotFoundError:
+    import skimage.transform
 
-MAP_INTERPOLATION_TO_ORDER = {
-    "nearest": 0,
-    "bilinear": 1,
-    "biquadratic": 2,
-    "bicubic": 3,
-}
+
+try:
+    # OpenCV: Map interpolation string to OpenCV interpolation enum value
+    INTERPOLATION_DICT = {
+        "nearest": cv2.INTER_NEAREST,
+        "bilinear": cv2.INTER_LINEAR,
+        "bicubic": cv2.INTER_CUBIC,
+        "laconzos": cv2.INTER_LANCZOS4,
+    }
+except NameError:
+    # scikit-image: Map interpolation string to interpolation order
+    INTERPOLATION_DICT = {
+        "nearest": 0,
+        "bilinear": 1,
+        "biquadratic": 2,
+        "bicubic": 3,
+    }
 
 
 def center_crop_and_resize(image, image_size, crop_padding=32, interpolation="bicubic"):
     assert image.ndim in {2, 3}
-    assert interpolation in MAP_INTERPOLATION_TO_ORDER.keys()
+    assert interpolation in INTERPOLATION_DICT.keys()
 
     in_h, in_w = image.shape[:2]
 
@@ -55,11 +69,19 @@ def center_crop_and_resize(image, image_size, crop_padding=32, interpolation="bi
                  offset_h : unpadded_center_crop_size_pre_scaling[0] + offset_h,
                  offset_w : unpadded_center_crop_size_pre_scaling[1] + offset_w,
                  ]
-    resized_image = resize(
-        image_crop,
-        (out_h, out_w),
-        order=MAP_INTERPOLATION_TO_ORDER[interpolation],
-        preserve_range=True,
-    )
+
+    try:
+        resized_image = cv2.resize(
+            image_crop,
+            (out_w, out_h),
+            interpolation=INTERPOLATION_DICT[interpolation] if inv_scale < 1 else cv2.INTER_AREA,
+        )
+    except NameError:
+        resized_image = skimage.transform.resize(
+            image_crop,
+            (out_h, out_w),
+            order=INTERPOLATION_DICT[interpolation],
+            preserve_range=True,
+        )
 
     return resized_image