Neural Network Multi-input

1#!/usr/bin/env python3
2import cv2
3import depthai as dai
4import numpy as np
5from pathlib import Path
6
7# Get the absolute path of the current script's directory
8script_dir = Path(__file__).resolve().parent
9examplesRoot = (script_dir / Path('../')).resolve()  # This resolves the parent directory correctly
10models = examplesRoot / 'models'
11tagImage = models / 'lenna.png'
12
13# Decode the image using OpenCV
14lenaImage = cv2.imread(str(tagImage.resolve()))
15lenaImage = cv2.resize(lenaImage, (256, 256))
16lenaImage = np.array(lenaImage)
17
18device = dai.Device()
19platform = device.getPlatform()
20if(platform == dai.Platform.RVC2):
21    daiType = dai.ImgFrame.Type.RGB888p
22elif(platform == dai.Platform.RVC4):
23    daiType = dai.ImgFrame.Type.RGB888i
24else:
25    raise RuntimeError("Platform not supported")
26
27daiLenaImage = dai.ImgFrame()
28
29daiLenaImage.setCvFrame(lenaImage, daiType)
30
31with dai.Pipeline(device) as pipeline:
32    model = dai.NNModelDescription("depthai-test-models/simple-concatenate-model")
33    model.platform = platform.name
34
35    nnArchive = dai.NNArchive(dai.getModelFromZoo(model))
36    cam = pipeline.create(dai.node.Camera).build()
37    camOut = cam.requestOutput((256,256), daiType)
38
39    neuralNetwork = pipeline.create(dai.node.NeuralNetwork)
40    neuralNetwork.setNNArchive(nnArchive)
41    camOut.link(neuralNetwork.inputs["image1"])
42    lennaInputQueue = neuralNetwork.inputs["image2"].createInputQueue()
43    # No need to send the second image everytime
44    neuralNetwork.inputs["image2"].setReusePreviousMessage(True)
45    qNNData = neuralNetwork.out.createOutputQueue()
46    pipeline.start()
47    lennaInputQueue.send(daiLenaImage)
48    while pipeline.isRunning():
49        inNNData: dai.NNData = qNNData.get()
50        tensor : np.ndarray = inNNData.getFirstTensor()
51        # Drop the first dimension
52        tensor = tensor.squeeze().astype(np.uint8)
53        # Check the shape - in case 3 is not the last dimension, permute it to the last
54        if tensor.shape[0] == 3:
55            tensor = np.transpose(tensor, (1, 2, 0))
56        print(tensor.shape)
57        cv2.imshow("Combined", tensor)
58        key = cv2.waitKey(1)
59        if key == ord('q'):
60            break