ImageManip all operations

1import depthai as dai
2import cv2
3
4pipeline = dai.Pipeline()
5
6manip_input = pipeline.create(dai.node.ImageManip)
7manip_input.initialConfig.setFrameType(dai.ImgFrame.Type.BGR888p)
8inputQueue = manip_input.inputImage.createInputQueue()
9
10manip_ops = [
11    # Resize operations. If aspect ratio isn't the same, the image will be stretched/cropped/letterboxed (depending on resize mode)
12    # Docs here: https://docs.luxonis.com/software/depthai/resolution-techniques/
13    ('resize_stretch', lambda conf: conf.setOutputSize(256, 200, dai.ImageManipConfig.ResizeMode.STRETCH)),
14    ('resize_letterbox', lambda conf: conf.setOutputSize(256, 200, dai.ImageManipConfig.ResizeMode.LETTERBOX)),
15    ('resize_center_crop', lambda conf: conf.setOutputSize(256, 200, dai.ImageManipConfig.ResizeMode.CENTER_CROP)),
16    # Crop the image topLeft (10,40) to bottomRight (310,110)
17    ('crop', lambda conf: conf.addCrop(x=50, y=50, w=150, h=200)),
18    # Flip the frame vertically/horizontally
19    ('flip_vertical', lambda conf: conf.addFlipVertical()),
20    ('flip_horizontal', lambda conf: conf.addFlipHorizontal()),
21    # Scale the image by 0.7x in x and 0.5x in y
22    ('scale', lambda conf: conf.addScale(0.7, 0.5)),
23    # Rotate. If center isn't specified, it will rotate around center (0.5, 0.5)
24    ('rotate_90_deg', lambda conf: conf.addRotateDeg(90)),
25    ('rotate_90_deg_center', lambda conf: conf.addRotateDeg(90, center=dai.Point2f(0.2, 0.3)).setOutputCenter(False)),
26    ('transform_affine', lambda conf: conf.addTransformAffine( # Shearing
27        [1, 0.5,
28         0.2, 1])),
29    ('transform_perspective', lambda conf: conf.addTransformPerspective(
30        [1.0, 0.2, 0.0,  # First row
31        0.1, 1.0, 0.0,  # Second row
32        0.001, 0.002, 1.0])),  # Third row
33    ('frame_type', lambda conf: conf.setFrameType(dai.ImgFrame.Type.RAW8)), # to Grayscale
34]
35
36# Dynamically create ImageManip nodes, apply configurations, and set up queues
37queues = {}
38for name, config in manip_ops:
39    print(name, config)
40    manip = pipeline.create(dai.node.ImageManip)
41    config(manip.initialConfig)
42    manip_input.out.link(manip.inputImage)
43    queues[name] = manip.out.createOutputQueue(maxSize=4, blocking=False)
44
45
46imgFrame = dai.ImgFrame()
47
48input_frame = cv2.imread('../models/lenna.png') # 512x512
49# Send 256x256 image to the device
50imgFrame.setCvFrame(cv2.pyrDown(input_frame), dai.ImgFrame.Type.BGR888i)
51inputQueue.send(imgFrame)
52
53cv2.imshow('input_image', input_frame)
54
55
56pipeline.start()
57
58for name, queue in queues.items():
59    inFrame = queue.get()
60    cv2.imshow(name, inFrame.getCvFrame())
61
62key = cv2.waitKey(0)