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1.2 KiB
Image Crop Implementation with CV2
author: David Wang
Description
An image crop operator implementation with OpenCV.
Code Example
Crop the face from 'einstein.jpg'.
import towhee
bboxes = towhee.glob['path']('einstein.jpg') \
.image_decode['path', 'img']() \
.face_detection.retinaface['img', ('box','score')]()\
.image_crop[('img', 'box'), 'crop'](clamp = True)\
.select['img','crop']()\
.show()
Factory Constructor
Create the operator via the following factory method
image_crop(clamp = True)
Parameters:
clamp: bool
If set True, coordinates of bounding boxes would be clamped into image size.
Interface
An image crop operator takes an image and bounding boxes as input. It cropes the image into ROIs(region of interest).
Parameters:
img: towhee.types.Image (a sub-class of numpy.ndarray)
The image need to be cropped.
bboxes: numpy.ndarray
The nx4 numpy tensor for n bounding boxes need to crop, each row is formatted as (x1, y1, x2, y2).
Returns: towhee.types.Image (a sub-class of numpy.ndarray)
The cropped image data as numpy.ndarray.
1.2 KiB
Image Crop Implementation with CV2
author: David Wang
Description
An image crop operator implementation with OpenCV.
Code Example
Crop the face from 'einstein.jpg'.
import towhee
bboxes = towhee.glob['path']('einstein.jpg') \
.image_decode['path', 'img']() \
.face_detection.retinaface['img', ('box','score')]()\
.image_crop[('img', 'box'), 'crop'](clamp = True)\
.select['img','crop']()\
.show()
Factory Constructor
Create the operator via the following factory method
image_crop(clamp = True)
Parameters:
clamp: bool
If set True, coordinates of bounding boxes would be clamped into image size.
Interface
An image crop operator takes an image and bounding boxes as input. It cropes the image into ROIs(region of interest).
Parameters:
img: towhee.types.Image (a sub-class of numpy.ndarray)
The image need to be cropped.
bboxes: numpy.ndarray
The nx4 numpy tensor for n bounding boxes need to crop, each row is formatted as (x1, y1, x2, y2).
Returns: towhee.types.Image (a sub-class of numpy.ndarray)
The cropped image data as numpy.ndarray.