EAST Alternatives
Similar projects and alternatives to EAST
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TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobilećdesktop and server. 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
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EAST
This is a pytorch re-implementation of EAST: An Efficient and Accurate Scene Text Detector. (by songdejia)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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deep-license-plate-recognition
Automatic License Plate Recognition (ALPR) or Automatic Number Plate Recognition (ANPR) software that works with any camera.
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ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
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EAST
PyTorch Re-Implementation of EAST: An Efficient and Accurate Scene Text Detector (by SakuraRiven)
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DeepSpeech
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
EAST reviews and mentions
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How the network architecture in EAST text detector translates to keras?
I'm not sure whether I'm among a few or many who struggle translating academic papers to code. I tried looking for EAST reliable implementation, and so far I only found this (TF 1.x), this (pytorch), this (pytorch), ... and a few others. The problem is that I cannot tell the differences between each and the paper's implementation. Here's the network architecture below, can someone explain how I should read and interpret / convert what is understood from the figure to a keras model. The parts I find tricky:
Stats
argman/EAST is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
The primary programming language of EAST is C++.
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