RGB & MobileNetSSD @ 4K

1#!/usr/bin/env python3
2
3from pathlib import Path
4import sys
5import cv2
6import depthai as dai
7import numpy as np
8
9# Get argument first
10nnPath = str((Path(__file__).parent / Path('../models/mobilenet-ssd_openvino_2021.4_5shave.blob')).resolve().absolute())
11if len(sys.argv) > 1:
12    nnPath = sys.argv[1]
13
14if not Path(nnPath).exists():
15    import sys
16    raise FileNotFoundError(f'Required file/s not found, please run "{sys.executable} install_requirements.py"')
17
18# MobilenetSSD label texts
19labelMap = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow",
20            "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"]
21
22# Create pipeline
23pipeline = dai.Pipeline()
24
25# Define sources and outputs
26camRgb = pipeline.create(dai.node.ColorCamera)
27nn = pipeline.create(dai.node.MobileNetDetectionNetwork)
28
29xoutVideo = pipeline.create(dai.node.XLinkOut)
30xoutPreview = pipeline.create(dai.node.XLinkOut)
31nnOut = pipeline.create(dai.node.XLinkOut)
32
33xoutVideo.setStreamName("video")
34xoutPreview.setStreamName("preview")
35nnOut.setStreamName("nn")
36
37# Properties
38camRgb.setPreviewSize(300, 300)    # NN input
39camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_4_K)
40camRgb.setInterleaved(False)
41camRgb.setPreviewKeepAspectRatio(False)
42# Define a neural network that will make predictions based on the source frames
43nn.setConfidenceThreshold(0.5)
44nn.setBlobPath(nnPath)
45nn.setNumInferenceThreads(2)
46nn.input.setBlocking(False)
47
48# Linking
49camRgb.video.link(xoutVideo.input)
50camRgb.preview.link(xoutPreview.input)
51camRgb.preview.link(nn.input)
52nn.out.link(nnOut.input)
53
54# Connect to device and start pipeline
55with dai.Device(pipeline) as device:
56
57    # Output queues will be used to get the frames and nn data from the outputs defined above
58    qVideo = device.getOutputQueue(name="video", maxSize=4, blocking=False)
59    qPreview = device.getOutputQueue(name="preview", maxSize=4, blocking=False)
60    qDet = device.getOutputQueue(name="nn", maxSize=4, blocking=False)
61
62    previewFrame = None
63    videoFrame = None
64    detections = []
65
66    # nn data, being the bounding box locations, are in <0..1> range - they need to be normalized with frame width/height
67    def frameNorm(frame, bbox):
68        normVals = np.full(len(bbox), frame.shape[0])
69        normVals[::2] = frame.shape[1]
70        return (np.clip(np.array(bbox), 0, 1) * normVals).astype(int)
71
72    def displayFrame(name, frame):
73        color = (255, 0, 0)
74        for detection in detections:
75            bbox = frameNorm(frame, (detection.xmin, detection.ymin, detection.xmax, detection.ymax))
76            cv2.putText(frame, labelMap[detection.label], (bbox[0] + 10, bbox[1] + 20), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
77            cv2.putText(frame, f"{int(detection.confidence * 100)}%", (bbox[0] + 10, bbox[1] + 40), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
78            cv2.rectangle(frame, (bbox[0], bbox[1]), (bbox[2], bbox[3]), color, 2)
79        # Show the frame
80        cv2.imshow(name, frame)
81
82    cv2.namedWindow("video", cv2.WINDOW_NORMAL)
83    cv2.resizeWindow("video", 1280, 720)
84    print("Resize video window with mouse drag!")
85
86    while True:
87        # Instead of get (blocking), we use tryGet (non-blocking) which will return the available data or None otherwise
88        inVideo = qVideo.tryGet()
89        inPreview = qPreview.tryGet()
90        inDet = qDet.tryGet()
91
92        if inVideo is not None:
93            videoFrame = inVideo.getCvFrame()
94
95        if inPreview is not None:
96            previewFrame = inPreview.getCvFrame()
97
98        if inDet is not None:
99            detections = inDet.detections
100
101        if videoFrame is not None:
102            displayFrame("video", videoFrame)
103
104        if previewFrame is not None:
105            displayFrame("preview", previewFrame)
106
107        if cv2.waitKey(1) == ord('q'):
108            break