initial

presets.py

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+import transforms as T
+
+
+class DetectionPresetTrain:
+    def __init__(self, data_augmentation, hflip_prob=0.5, mean=(123., 117., 104.)):
+        if data_augmentation == 'hflip':
+            self.transforms = T.Compose([
+                T.RandomHorizontalFlip(p=hflip_prob),
+                T.ToTensor(),
+            ])
+        elif data_augmentation == 'ssd':
+            self.transforms = T.Compose([
+                T.RandomPhotometricDistort(),
+                T.RandomZoomOut(fill=list(mean)),
+                T.RandomIoUCrop(),
+                T.RandomHorizontalFlip(p=hflip_prob),
+                T.ToTensor(),
+            ])
+        elif data_augmentation == 'ssdlite':
+            self.transforms = T.Compose([
+                T.RandomIoUCrop(),
+                T.RandomHorizontalFlip(p=hflip_prob),
+                T.ToTensor(),
+            ])
+        else:
+            raise ValueError(f'Unknown data augmentation policy "{data_augmentation}"')
+
+    def __call__(self, img, target):
+        return self.transforms(img, target)
+
+
+class DetectionPresetEval:
+    def __init__(self):
+        self.transforms = T.ToTensor()
+
+    def __call__(self, img, target):
+        return self.transforms(img, target)