Participants: Zhang Qian, Egg Sauce, Xiao Zhou
About two weeks ago, the Raspberry Pi 4 announced its latest upgrade: a new 8GB memory version, priced at $75. Is this new Raspberry Pi really worth it? To answer this question, a YouTuber named Jeff Geerling had a bold idea: on a workday, unplug his MacBook Pro and plug in the newly purchased 8GB Raspberry Pi 4 as his main work computer to see what it feels like after a day.
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Using specialized apps to browse Twitter;
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Using Slack (the memory used by Slack is more than most other applications that Jeff Geerling runs combined at any given time);
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Recording and editing audio and video;
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Using Docker, Ansible, and Kubernetes for some infrastructure automation.
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A Kensington 240GB SSD in an Inateck USB 3.0 SATA enclosure.
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Apple Magic Keyboard.
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Apple Magic Trackpad.
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Behringer U-Phoria USB 3.0 audio interface.
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Logitech C920 webcam.
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Reduce the load on the Raspberry Pi’s GPU (thus reducing tearing);
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Allow the Raspberry Pi’s GPU to apply anti-aliasing;
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Allow for a 60Hz refresh rate, making it more comfortable for my eyes when watching 60fps videos.
$ arecord --list-devices
**** List of CAPTURE Hardware Devices ****
card 2: U192k [UMC202HD 192k], device 0: USB Audio [USB Audio]
Subdevices: 1/1
Subdevice #0: subdevice #0
card 3: C920 [HD Pro Webcam C920], device 0: USB Audio [USB Audio]
Subdevices: 1/1
Subdevice #0: subdevice #0
# Gets sound and video from the webcam:
$ ffmpeg -ar 44100 -ac 2 -f alsa -i hw:3,0 -f v4l2 -codec:v h264 -framerate 30 -video_size 1920x1080 -itsoffset 0.5 -i /dev/video0 -copyinkf -codec:v copy -codec:a aac -ab 128k -g 10 -f mp4 test.mp4
# Sound from Behringer, video from webcam:
ffmpeg -ar 44100 -ac 2 -f alsa -acodec pcm_s32le -i hw:2,0 -f v4l2 -codec:v h264 -framerate 30 -video_size 1920x1080 -itsoffset 0.5 -i /dev/video0 -copyinkf -codec:v copy -codec:a aac -ab 128k -g 10 -f mp4 test-webcam-audio.mp4
Paddle Lite, the lightweight inference engine from PaddlePaddle, supports multiple hardware and platforms, providing efficient inference capabilities for mobile terminals, and widely integrates cross-platform hardware to meet the needs for edge deployment and application implementation.
On June 16 at 19:00, a senior R&D engineer from Baidu’s deep learning technology platform department will provide more details. Welcome to sign up for learning.
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