From 2e955cfd0cb750526db2bc02363f42334fc88626 Mon Sep 17 00:00:00 2001
From: Ross Wightman <rwightman@gmail.com>
Date: Sun, 5 Jan 2020 14:31:48 -0800
Subject: [PATCH] Update RandomErasing with some improved arg names, tweak to
 aspect range

---
 timm/data/random_erasing.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/timm/data/random_erasing.py b/timm/data/random_erasing.py
index 5eed1387..2b6b61a5 100644
--- a/timm/data/random_erasing.py
+++ b/timm/data/random_erasing.py
@@ -23,13 +23,13 @@ class RandomErasing:
         This variant of RandomErasing is intended to be applied to either a batch
         or single image tensor after it has been normalized by dataset mean and std.
     Args:
-         probability: The probability that the Random Erasing operation will be performed.
-         sl: Minimum proportion of erased area against input image.
-         sh: Maximum proportion of erased area against input image.
+         probability: Probability that the Random Erasing operation will be performed.
+         min_area: Minimum percentage of erased area wrt input image area.
+         max_area: Maximum percentage of erased area wrt input image area.
          min_aspect: Minimum aspect ratio of erased area.
          mode: pixel color mode, one of 'const', 'rand', or 'pixel'
             'const' - erase block is constant color of 0 for all channels
-            'rand'  - erase block is same per-cannel random (normal) color
+            'rand'  - erase block is same per-channel random (normal) color
             'pixel' - erase block is per-pixel random (normal) color
         max_count: maximum number of erasing blocks per image, area per box is scaled by count.
             per-image count is randomly chosen between 1 and this value.
@@ -37,14 +37,15 @@ class RandomErasing:
 
     def __init__(
             self,
-            probability=0.5, sl=0.02, sh=1/3, min_aspect=0.3,
-            mode='const', max_count=1, device='cuda'):
+            probability=0.5, min_area=0.02, max_area=1/3, min_aspect=0.3, max_aspect=None,
+            mode='const', min_count=1, max_count=None, device='cuda'):
         self.probability = probability
-        self.sl = sl
-        self.sh = sh
-        self.min_aspect = min_aspect
-        self.min_count = 1
-        self.max_count = max_count
+        self.min_area = min_area
+        self.max_area = max_area
+        max_aspect = max_aspect or 1 / min_aspect
+        self.log_aspect_ratio = (math.log(min_aspect), math.log(max_aspect))
+        self.min_count = min_count
+        self.max_count = max_count or min_count
         mode = mode.lower()
         self.rand_color = False
         self.per_pixel = False
@@ -64,9 +65,8 @@ class RandomErasing:
             random.randint(self.min_count, self.max_count)
         for _ in range(count):
             for attempt in range(10):
-                target_area = random.uniform(self.sl, self.sh) * area / count
-                log_ratio = (math.log(self.min_aspect), math.log(1 / self.min_aspect))
-                aspect_ratio = math.exp(random.uniform(*log_ratio))
+                target_area = random.uniform(self.min_area, self.max_area) * area / count
+                aspect_ratio = math.exp(random.uniform(*self.log_aspect_ratio))
                 h = int(round(math.sqrt(target_area * aspect_ratio)))
                 w = int(round(math.sqrt(target_area / aspect_ratio)))
                 if w < img_w and h < img_h: