DomesdayDuplicator
hls4ml
DomesdayDuplicator | hls4ml | |
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12 | 11 | |
132 | 1,115 | |
- | 3.9% | |
3.6 | 9.2 | |
4 months ago | 6 days ago | |
C++ | C++ | |
GNU General Public License v3.0 only | Apache License 2.0 |
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DomesdayDuplicator
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The LaserDisc – By Bradford Morgan White – Abort Retry Fail
I’m sure you’re aware of the Domesday Duplicator[0] and related projects.
There’s several MegaLD/LDROM² discs that need preservation that I hope I can help with one day.
0 - https://github.com/simoninns/DomesdayDuplicator/wiki/Overvie...
- The Domesday Duplicator
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LaserDiscs Are Dying—Here’s Why That Matters - Electric Literature
This is why the Domesday Duplicator project is so important; an effective 1:1 copy of LaserDiscs, and almost any other analog media you can tap RF maintenance points of (of the playback deck).
It can be done if you’re determined enough.
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Due to the positive reception of my last two posts, here's another rare film I digitized and got subtitled in English a while back: Hikari Hayakawa's Evil Heart (1985) (age-restricted video, sadly). Also includes a subtitled making-of documentary.
Also the rips you get from one aren't normal video files. It's like a raw RF log of what the laser is reading. You run the raw data through some code to get a playable video. But the quality is really unmatched, night and day difference. The time is ticking to get "perfect" rips of these LDs, as they've all started to degrade, I wish there were an easier way to do it..
- I want to get digital files of my laserdiscs. What is the best Laserdisc Transfer Service to send my LDs to? Who would you recommend? Who gave you really good results?
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donated to me today ..
I have some discs I'm keeping until I get a player and have a go at preserving them (https://github.com/simoninns/DomesdayDuplicator/wiki) but finding a unit where I live is a challenge on itself, nevermind a proper working and maintained one. I have no real interest on them as a collector but do surely appreciate the format.
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Thanks for everyone's kind words on the previous upload of Love Massacre (1981). I have corrected the footage to the correct aspect ratio, done some more corrections on subtitling, and it is now available on archive.org as well. Hope you enjoy.
Have you considered using a Domesday Duplicator to digitize your Laserdiscs?
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[Talk] possible lost media on lazerdisks?
Just a little bit of info - the Domesday Duplicator was created for this reason - it allows pit-perfect backups of the information contained on Laserdiscs.
hls4ml
- How to participate in open-source FPGA projects?
- Looking for HLS frameworks to start deploying DL algorithms on FPGAs
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Hi, What could be the best HLS tool for implementing neural networks on FPGA
I see that someone has already suggested hls4ml. I second that opinion. From my experience, it is extremely well documented. They have published papers which explain the scientific background. They have a really nice git page where they explain all the features of their tool. Additionally they also have an easy to follow tutorial of doing it from scratch using tensorflow networks. You can find all the information herehls4ml.
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5 layered CNN implementation on arduino/FPGAs [P]
Open source project that originated at Fermilab https://github.com/fastmachinelearning/hls4ml (based on Xilinx Vivado which has been replaced by Vitis)
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Help needed to build a Hardware accelerator for CNN's
You may check the hls4ml framework: it's a "translator" from the ML model (Keras, PyTorch) to a synthesizable High-Level Synthesis (HLS) IP Core.
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Sub ms - 3ms Latency Vision task on FPGA
It really depends on the type of data you are using. There may (or may not) be some trade offs and sacrifices. There are frameworks which can basically translate your neural network information from a high level python code into equivalent HLS code which is optimized for low latency when inferred on FPGAs. Some frameworks which might be useful for you to explore are hls4ml and finn. These are some frameworks which can achieve low latency inference of neural networks on FPGAs using Xilinx Vitis HLS. These are what I found when I did a similar experiment but with much lower latency target (a few hundred ns) and a very simple MLP with 1D signal as input which was a year ago. Not sure if there are better alternatives available as of 2023. But conceptually all these work on the primary principle of having a supporting framework/methodology to first quantize the network and limit the precision of data to fixed point. The HLS then produced will also be a result of the framework applying dataflow techniques such that the resulting HLS code will produce an RTL which has the best overall latency.
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looking for resources to design a basic deep learning feed forward accelerator
Check hls4ml. Developed by CERN for fast classification in FPGA for high-energy physics experiments.
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How to build FPGA-based ML accelerator?
I would check out hls4ml. It's an open source project made by/for people at CERN to convert neural networks created in Python using QKeras (a quantization extension of Keras) into HLS, with Vivado HLS being the most well supported. There are some caveats though, and a fellow student and I have had trouble getting the generated HLS to match the Keras model and be feasible to synthesize, but it seems to work well for smaller neural networks.
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How are TensorFlow Models implemented on PYNQ's PS & PL
Since you're looking for PL-only implementation, HLS4ML may fit your needs. It was developed to port TensorFlow models directly to FPGAs in particle physics experiments. Current development allows for implementation on SoC and MPSoC, though.
- Open source projects?
What are some alternatives?
vhs-decode - Software defined VHS decoder - Fork (maybe temporary) of the ld-decode Laserdisc rf decoder
qkeras - QKeras: a quantization deep learning library for Tensorflow Keras
cascade - A Just-In-Time Compiler for Verilog from VMware Research
Silice - Silice is an easy-to-learn, powerful hardware description language, that simplifies designing hardware algorithms with parallelism and pipelines.
v4l2rtspserver - RTSP Server for V4L2 device capture supporting HEVC/H264/JPEG/VP8/VP9
srs - SRS is a simple, high-efficiency, real-time video server supporting RTMP, WebRTC, HLS, HTTP-FLV, SRT, MPEG-DASH, and GB28181.
PipelineC - A C-like hardware description language (HDL) adding high level synthesis(HLS)-like automatic pipelining as a language construct/compiler feature.
fastocloud_com - Self-hosted IPTV/NVR/CCTV/Video service (Community version) [Moved to: https://github.com/fastogt/fastocloud]
fastocloud_mpart - Self-hosted IPTV/NVR/CCTV/Video service [Moved to: https://github.com/fastogt/fastocloud]
hlslib - A collection of extensions for Vitis and Intel FPGA OpenCL to improve developer quality of life.
corundum - Open source FPGA-based NIC and platform for in-network compute
fpga_floorplanning - NTHU CS5160 FPGA結構及設計自動化 麥偉基 Final Project