nhcalc
Compute NeuralHash for the given image (by KhaosT)
TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a lightweight and high-performance deep learning framework for mobile inference. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework. TNN：由腾讯优图实验室和光影实验室协同打造，移动端高性能、轻量级推理框架，同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化，同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地，欢迎大家参与协同共建，促进TNN推理框架进一步完善。 (by AsuharietYgvar)
| nhcalc | TNN | |
|---|---|---|
| 4 | 1 | |
| 127 | 8 | |
| - | - | |
| 3.2 | 0.0 | |
| over 2 years ago | over 2 years ago | |
| Swift | C++ | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nhcalc
Posts with mentions or reviews of nhcalc.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-17.
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[P] AppleNeuralHash2ONNX: Reverse-Engineered Apple NeuralHash, in ONNX and Python
The hidden APIs were found by someone else here. I'm not going to talk about the reverse-engineering process in too much detail. Basically what I did was to use Xcode debugger+Hopper disassembler+LLDB commands trying to understand how the function works under the hood in assembly code (which was very tedious). There were some parts that I didn't understand and by guessing I managed to get the same hash results from my script as what came from the function.
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"Having your device know you is cool. Having some cloud person know you is creepy." - Craig Federighi
not iOS, but macOS Monterey https://github.com/KhaosT/nhcalc
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Apple's New CSAM Protections May Make iCloud Photos Bruteforceable
This isn't really true in a world where it's trivial to reverse engineer and decompile binaries.
For example, we already now have a tool for generating NeuralHash hashes for arbitrary images, thanks to KhaosT:
https://github.com/khaost/nhcalc
- Compute Apple NeuralHash for a given image
TNN
Posts with mentions or reviews of TNN.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-17.
-
[P] AppleNeuralHash2ONNX: Reverse-Engineered Apple NeuralHash, in ONNX and Python
For what would they sue him tho? He didn't infringe any copyrights or anything, he only posted some instructions with 10 lines of code to support the model https://github.com/AsuharietYgvar/TNN/commit/1a637d88cc5e388f6fb31291e7df0d563238e785
What are some alternatives?
When comparing nhcalc and TNN you can also consider the following projects:
AppleNeuralHash2ONNX - Convert Apple NeuralHash model for CSAM Detection to ONNX.