8.1.2.8. blueoil.pre_processor
¶
8.1.2.8.1. Module Contents¶
8.1.2.8.1.1. Classes¶
Linear quantize per image. |
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Standardization per image. |
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Resize image. |
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Resize image with gt boxes. |
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Resize image and mask. |
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Resize image and joints. |
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Divide image by 255. |
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Darknet’s letter boxes |
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Convert joints to gaussian heatmap which can be learned by networks. |
8.1.2.8.1.2. Functions¶
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Resize an image. |
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Square an image. |
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Resize an image and gt_boxes. |
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Resize keeping ratio an image and gt_boxes. |
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Resize image with joints to target image_size. |
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Image standardization per image. |
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Linear quantize per image. |
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|
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Convert joints to gaussian heatmap which can be learned by networks. |
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blueoil.pre_processor.
RESAMPLE_METHODS
¶
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blueoil.pre_processor.
resize
(image, size=[256, 256], resample='NEAREST')¶ Resize an image.
- Parameters
image (np.ndarray) – an image numpy array.
size – [height, width]
resample (str) – A name of resampling filter
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blueoil.pre_processor.
square
(image, gt_boxes, fill=127.5)¶ Square an image.
- Parameters
image – An image numpy array.
gt_boxes – Python list ground truth boxes in the image. shape is [num_boxes, 5(x, y, width, height)].
fill – Fill blank by this number. (Default value = 127.5)
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blueoil.pre_processor.
resize_with_gt_boxes
(image, gt_boxes, size=(256, 256), resample='NEAREST')¶ Resize an image and gt_boxes.
- Parameters
image (np.ndarray) – An image numpy array.
gt_boxes (np.ndarray) – Ground truth boxes in the image. shape is [num_boxes, 5(x, y, width, height, class_id)].
size – [height, width]
resample (str) – A name of resampling filter
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blueoil.pre_processor.
resize_keep_ratio_with_gt_boxes
(image, gt_boxes, size=(256, 256), resample='NEAREST')¶ Resize keeping ratio an image and gt_boxes.
- Parameters
image (np.ndarray) – An image numpy array.
gt_boxes (list) – Python list ground truth boxes in the image. shape is [num_boxes, 5(x, y, width, height)].
size – [height, width]
resample (str) – A name of resampling filter
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blueoil.pre_processor.
resize_with_joints
(image, joints, image_size, resample='NEAREST')¶ Resize image with joints to target image_size.
- Parameters
image – a numpy array of shape (height, width, 3).
joints – a numpy array of shape (num_joints, 3).
image_size – a tuple, (new_height, new_width).
resample (str) – A name of resampling filter
- Returns
a numpy array of shape (new_height, new_width, 3). new_joints: a numpy array of shape (num_joints, 3).
- Return type
resized_image
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blueoil.pre_processor.
per_image_standardization
(image)¶ Image standardization per image.
https://www.tensorflow.org/api_docs/python/image/image_adjustments#per_image_standardization
- Parameters
image – An image numpy array.
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blueoil.pre_processor.
per_image_linear_quantize
(image, bit)¶ Linear quantize per image.
\[\mathbf{Y} = \frac{\text{round}\big(\frac{\mathbf{X}}{max\_value} \cdot (2^{bit}-1)\big)}{2^{bit}-1} \cdot max\_value\]- Parameters
image – An image numpy array.
bit – Quantize bit.
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blueoil.pre_processor.
_linear_quantize
(x, bit, value_min, value_max)¶
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blueoil.pre_processor.
joints_to_gaussian_heatmap
(joints, image_size, num_joints=17, stride=1, sigma=2)¶ Convert joints to gaussian heatmap which can be learned by networks.
References
https://github.com/Microsoft/human-pose-estimation.pytorch
- Parameters
joints (np.ndarray) – a numpy array of shape (num_joints).
image_size (tuple) – a tuple, (height, width).
num_joints (int) – int. (Default value = 17)
stride (int) – int, stride = image_height / heatmap_height. (Default value = 1)
sigma (int) – int, used to compute gaussian heatmap. (Default value = 2)
- Returns
a numpy array of shape (height, width, num_joints).
- Return type
heatmap
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class
blueoil.pre_processor.
PerImageLinearQuantize
(bit)¶ Bases:
blueoil.data_processor.Processor
Linear quantize per image.
Use
per_image_linear_quantize()
inside.- Parameters
bit – Quantize bit.
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__call__
(self, image, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
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class
blueoil.pre_processor.
PerImageStandardization
¶ Bases:
blueoil.data_processor.Processor
Standardization per image.
Use
per_image_standardization()
inside.-
__call__
(self, image, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
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class
blueoil.pre_processor.
Resize
(size, resample='NEAREST')¶ Bases:
blueoil.data_processor.Processor
Resize image.
Use
resize()
inside.- Parameters
size – Target size.
resample (str) – A name of resampling filter
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__call__
(self, image, mask=None, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
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class
blueoil.pre_processor.
ResizeWithGtBoxes
(size, resample='NEAREST')¶ Bases:
blueoil.data_processor.Processor
Resize image with gt boxes.
Use
resize_with_gt_boxes()
inside.- Parameters
size – Target size.
resample (str) – A name of resampling filter
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__call__
(self, image, gt_boxes=None, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
-
class
blueoil.pre_processor.
ResizeWithMask
(size, resample='NEAREST')¶ Bases:
blueoil.data_processor.Processor
Resize image and mask.
Use
resize()
inside.- Parameters
size – Target size.
resample (str) – A name of resampling filter
-
__call__
(self, image, mask=None, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
-
class
blueoil.pre_processor.
ResizeWithJoints
(image_size, resample='NEAREST')¶ Bases:
blueoil.data_processor.Processor
Resize image and joints.
Use
resize_with_joints()
inside.- Parameters
image_size – Target size.
resample (str) – A name of resampling filter
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__call__
(self, image, joints=None, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
-
class
blueoil.pre_processor.
DivideBy255
¶ Bases:
blueoil.data_processor.Processor
Divide image by 255.
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__call__
(self, image, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
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class
blueoil.pre_processor.
LetterBoxes
(size, resample='NEAREST')¶ Bases:
blueoil.data_processor.Processor
Darknet’s letter boxes
Use
resize_keep_ratio_with_gt_boxes()
inside.- Parameters
size – Target size.
resample (str) – A name of resampling filter
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__call__
(self, image, gt_boxes=None, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.
-
class
blueoil.pre_processor.
JointsToGaussianHeatmap
(image_size, num_joints=17, stride=1, sigma=3)¶ Bases:
blueoil.data_processor.Processor
Convert joints to gaussian heatmap which can be learned by networks.
Use
joints_to_gaussian_heatmap()
inside.- Parameters
image_size (tuple) – a tuple, (height, width).
num_joints (int) – int.
stride (int) – int, stride = image_height / heatmap_height.
sigma (int) – int, used to compute gaussian heatmap.
- Returns
- Return type
dict
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__call__
(self, joints=None, **kwargs)¶ Call processor method for each a element of data.
Return image and labels etc.