RGB Encoding & MobilenetSSD
This example shows how to configure the depthai video encoder in h.265 format to encode the RGB camera input at Full-HD resolution at 30FPS, and transfers the encoded video over XLINK to the host, saving it to disk as a video file. In the same time, a MobileNetv2SSD network is ran on the frames from the same RGB camera that is used for encodingPressing Ctrl+C will stop the recording and then convert it using ffmpeg into an mp4 to make it playable. Note that ffmpeg will need to be installed and runnable for the conversion to mp4 to succeed.Be careful, this example saves encoded video to your host storage. So if you leave it running, you could fill up your storage on your host.It's a combination of RGB Encoding and RGB & MobilenetSSD.Similar samples:
- RGB Encoding
- RGB & Mono Encoding
- Encoding Max Limit
- RGB Encoding & Mono & MobilenetSSD
- RGB Encoding & Mono with MobilenetSSD & Depth
Demo
Setup
Please run the install script to download all required dependencies. Please note that this script must be ran from git context, so you have to download the depthai-python repository first and then run the scriptCommand Line
1git clone https://github.com/luxonis/depthai-python.git
2cd depthai-python/examples
3python3 install_requirements.py
Source code
Python
C++
Python
PythonGitHub
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_6shave.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)
27videoEncoder = pipeline.create(dai.node.VideoEncoder)
28nn = pipeline.create(dai.node.MobileNetDetectionNetwork)
29
30xoutRgb = pipeline.create(dai.node.XLinkOut)
31videoOut = pipeline.create(dai.node.XLinkOut)
32nnOut = pipeline.create(dai.node.XLinkOut)
33
34xoutRgb.setStreamName("rgb")
35videoOut.setStreamName("h265")
36nnOut.setStreamName("nn")
37
38# Properties
39camRgb.setBoardSocket(dai.CameraBoardSocket.CAM_A)
40camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P)
41camRgb.setPreviewSize(300, 300)
42camRgb.setInterleaved(False)
43
44videoEncoder.setDefaultProfilePreset(30, dai.VideoEncoderProperties.Profile.H265_MAIN)
45
46nn.setConfidenceThreshold(0.5)
47nn.setBlobPath(nnPath)
48nn.setNumInferenceThreads(2)
49nn.input.setBlocking(False)
50
51# Linking
52camRgb.video.link(videoEncoder.input)
53camRgb.preview.link(xoutRgb.input)
54camRgb.preview.link(nn.input)
55videoEncoder.bitstream.link(videoOut.input)
56nn.out.link(nnOut.input)
57
58# Connect to device and start pipeline
59with dai.Device(pipeline) as device, open('video.h265', 'wb') as videoFile:
60
61 # Queues
62 queue_size = 8
63 qRgb = device.getOutputQueue("rgb", queue_size)
64 qDet = device.getOutputQueue("nn", queue_size)
65 qRgbEnc = device.getOutputQueue('h265', maxSize=30, blocking=True)
66
67 frame = None
68 detections = []
69
70 def frameNorm(frame, bbox):
71 normVals = np.full(len(bbox), frame.shape[0])
72 normVals[::2] = frame.shape[1]
73 return (np.clip(np.array(bbox), 0, 1) * normVals).astype(int)
74
75 def displayFrame(name, frame):
76 color = (255, 0, 0)
77 for detection in detections:
78 bbox = frameNorm(frame, (detection.xmin, detection.ymin, detection.xmax, detection.ymax))
79 cv2.putText(frame, labelMap[detection.label], (bbox[0] + 10, bbox[1] + 20), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
80 cv2.putText(frame, f"{int(detection.confidence * 100)}%", (bbox[0] + 10, bbox[1] + 40), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
81 cv2.rectangle(frame, (bbox[0], bbox[1]), (bbox[2], bbox[3]), color, 2)
82 # Show the frame
83 cv2.imshow(name, frame)
84
85 while True:
86 inRgb = qRgb.tryGet()
87 inDet = qDet.tryGet()
88
89 while qRgbEnc.has():
90 qRgbEnc.get().getData().tofile(videoFile)
91
92 if inRgb is not None:
93 frame = inRgb.getCvFrame()
94
95 if inDet is not None:
96 detections = inDet.detections
97
98 if frame is not None:
99 displayFrame("rgb", frame)
100
101 if cv2.waitKey(1) == ord('q'):
102 break
103
104print("To view the encoded data, convert the stream file (.h265) into a video file (.mp4), using a command below:")
105print("ffmpeg -framerate 30 -i video.h265 -c copy video.mp4")
Pipeline
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