fix croppad to mimic RandomResizedCrop in validation

.vscode/launch.json

@@ -0,0 +1,17 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: Debug Tests",
+            "type": "python",
+            "request": "launch",
+            "program": "${file}",
+            "purpose": ["debug-test"],
+            "console": "integratedTerminal",
+            "justMyCode": false
+        }
+    ]
+}

deployment/transforms.py

@@ -1,3 +1,4 @@
+import math
 from typing import Literal, Union, Tuple
 
 import torch
@@ -70,9 +71,28 @@ def pad(image, size: Tuple[int, int]) -> Image:
     return tvf.pad(image, [pad_top, pad_left, height, width], padding_mode="constant")
 
 
-def CenterCropPad(size: tuple[Literal[460], Literal[460]]):
+def CenterCropPad(size: tuple[Literal[460], Literal[460]], val_xtra: float = 0.14):
+    """
+    Args:
+        image (`PIL.Image`):
+            An image to perform padding on
+        size (`tuple` of integers):
+            A size to pad to, should be in the form
+            of (width, height)
+        val_xtra: The ratio of size at the edge cropped out in the validation set
+    """
     # return tvtfms.CenterCrop(size)
     def _crop_pad(img):
-        return pad(center_crop(img, size), size)
+        orig_sz = img.shape
+        xtra = math.ceil(max(*size[:2]) * val_xtra / 8) * 8
+        final_size = (size[0] + xtra, size[1] + xtra)
+
+        res = pad(center_crop(img, orig_sz), orig_sz).resize(
+            final_size, resample=Image.Resampling.BILINEAR
+        )
+        if final_size != size:
+            res = pad(center_crop(res, size), size)
+
+        return res
 
     return _crop_pad

tests/test_transforms.py

@@ -46,8 +46,8 @@ class TestTransforms:
         crop_fastai = fastai_aug.CropPad((460, 460))
         crop_rrc = fastai_aug.RandomResizedCrop((460, 460))
 
-        cropped_fastai = crop_rrc(im_fastai, split_idx=1)
-        cropped_rrc = crop_fastai(im_fastai, split_idx=1)
+        cropped_rrc = crop_rrc(im_fastai, split_idx=1)
+        cropped_fastai = crop_fastai(im_fastai, split_idx=1)
 
         assert (np.array(cropped_rrc) == np.array(cropped_fastai)).all()
 
@@ -56,3 +56,14 @@ class TestTransforms:
         crop_torch = CenterCropPad((460, 460))
 
         assert (np.array(crop_fastai(im_fastai)) == np.array(crop_torch(im_pil))).all()
+
+    def testRandomResizedCropInValidationEqualsCustomCenterCropPad(
+        self, im_fastai: PILImage, im_pil: Image
+    ):
+        crop_rrc = fastai_aug.RandomResizedCrop((460, 460))
+        crop_custom = CenterCropPad((460, 460))
+
+        cropped_rrc = crop_rrc(im_fastai, split_idx=1)
+        cropped_custom = crop_custom(im_fastai)
+
+        assert (np.array(cropped_rrc) == np.array(cropped_custom)).all()