Introduction
yyimg is a high-level image-processing tool, written in Python and using OpenCV as backbend. This repo helps you with processing images for your deep learning projects.
Installation
Commands to install from pip or download the source code from our website https://pypi.org/project/yyimg
$ pip3 install yyimg==1.0.2
Example Useage
Take one image in Kitti dataset for example:
import yyimg
from PIL import Image
image, boxes, classes = yyimg.load_data()| Items | Description |
|---|---|
| image | a numpy array of shape (height, width, #channels) |
| boxes | a numpy array of shape (N, 5), representing N 2Dboxes of [class_index, xmin, ymin, xmax, ymax]
|
| classes | a list of class names |
print(classes)
['Car', 'Truck', 'Van', 'Pedestrian']visualize 2D boxes
draw_image = yyimg.draw_2Dbox(image, boxes, class_category=classes)
draw_image = cv2.cvtColor(draw_image, cv2.COLOR_BGR2RGB) # BGR -> RGB
Image.fromarray(draw_image).show()
create gif
frames = ["0.jpg", "1.jpg", "2.jpg"]
yyimg.create_gif("result.gif", image_list)data augmentation
- horizontal_flip
with 2D bounding boxes:
aug_image, boxes = yyimg.horizontal_flip(image, boxes)without 2D bounding boxes:
aug_image = yyimg.horizontal_flip(image)
- add_rain
aug_image = yyimg.add_rain(image)
- shift_gama
aug_image = yyimg.shift_gamma(image) 
- shift_brightness
aug_image = yyimg.shift_brightness(image)
- shift_color
aug_image = yyimg.shift_color(image)
