what.models.detection.ssd.ssd.preprocessing

 1from ..transforms.transforms import *
 2
 3class TrainAugmentation:
 4    def __init__(self, size, mean=0, std=1.0):
 5        """
 6        Args:
 7            size: the size the of final image.
 8            mean: mean pixel value per channel.
 9        """
10        self.mean = mean
11        self.size = size
12        self.augment = Compose([
13            ConvertFromInts(),
14            PhotometricDistort(),
15            Expand(self.mean),
16            RandomSampleCrop(),
17            RandomMirror(),
18            ToPercentCoords(),
19            Resize(self.size),
20            SubtractMeans(self.mean),
21            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
22            ToTensor(),
23        ])
24
25    def __call__(self, img, boxes, labels):
26        """
27        Args:
28            img: the output of cv.imread in RGB layout.
29            boxes: boundding boxes in the form of (x1, y1, x2, y2).
30            labels: labels of boxes.
31        """
32        return self.augment(img, boxes, labels)
33
34class TestTransform:
35    def __init__(self, size, mean=0.0, std=1.0):
36        self.transform = Compose([
37            ToPercentCoords(),
38            Resize(size),
39            SubtractMeans(mean),
40            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
41            ToTensor(),
42        ])
43
44    def __call__(self, image, boxes, labels):
45        return self.transform(image, boxes, labels)
46
47class PredictionTransform:
48    def __init__(self, size, mean=0.0, std=1.0):
49        self.transform = Compose([
50            Resize(size),
51            SubtractMeans(mean),
52            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
53            ToTensor()
54        ])
55
56    def __call__(self, image):
57        image, _, _ = self.transform(image)
58        return image
class TrainAugmentation:
 4class TrainAugmentation:
 5    def __init__(self, size, mean=0, std=1.0):
 6        """
 7        Args:
 8            size: the size the of final image.
 9            mean: mean pixel value per channel.
10        """
11        self.mean = mean
12        self.size = size
13        self.augment = Compose([
14            ConvertFromInts(),
15            PhotometricDistort(),
16            Expand(self.mean),
17            RandomSampleCrop(),
18            RandomMirror(),
19            ToPercentCoords(),
20            Resize(self.size),
21            SubtractMeans(self.mean),
22            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
23            ToTensor(),
24        ])
25
26    def __call__(self, img, boxes, labels):
27        """
28        Args:
29            img: the output of cv.imread in RGB layout.
30            boxes: boundding boxes in the form of (x1, y1, x2, y2).
31            labels: labels of boxes.
32        """
33        return self.augment(img, boxes, labels)
TrainAugmentation(size, mean=0, std=1.0)
 5    def __init__(self, size, mean=0, std=1.0):
 6        """
 7        Args:
 8            size: the size the of final image.
 9            mean: mean pixel value per channel.
10        """
11        self.mean = mean
12        self.size = size
13        self.augment = Compose([
14            ConvertFromInts(),
15            PhotometricDistort(),
16            Expand(self.mean),
17            RandomSampleCrop(),
18            RandomMirror(),
19            ToPercentCoords(),
20            Resize(self.size),
21            SubtractMeans(self.mean),
22            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
23            ToTensor(),
24        ])

Args: size: the size the of final image. mean: mean pixel value per channel.

class TestTransform:
35class TestTransform:
36    def __init__(self, size, mean=0.0, std=1.0):
37        self.transform = Compose([
38            ToPercentCoords(),
39            Resize(size),
40            SubtractMeans(mean),
41            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
42            ToTensor(),
43        ])
44
45    def __call__(self, image, boxes, labels):
46        return self.transform(image, boxes, labels)
TestTransform(size, mean=0.0, std=1.0)
36    def __init__(self, size, mean=0.0, std=1.0):
37        self.transform = Compose([
38            ToPercentCoords(),
39            Resize(size),
40            SubtractMeans(mean),
41            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
42            ToTensor(),
43        ])
class PredictionTransform:
48class PredictionTransform:
49    def __init__(self, size, mean=0.0, std=1.0):
50        self.transform = Compose([
51            Resize(size),
52            SubtractMeans(mean),
53            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
54            ToTensor()
55        ])
56
57    def __call__(self, image):
58        image, _, _ = self.transform(image)
59        return image
PredictionTransform(size, mean=0.0, std=1.0)
49    def __init__(self, size, mean=0.0, std=1.0):
50        self.transform = Compose([
51            Resize(size),
52            SubtractMeans(mean),
53            lambda img, boxes=None, labels=None: (img / std, boxes, labels),
54            ToTensor()
55        ])