dnn_from_scratch VS open-lpr

Compare dnn_from_scratch vs open-lpr and see what are their differences.

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dnn_from_scratch open-lpr
1 1
29 149
- -
0.0 1.3
almost 3 years ago about 1 year ago
Python Python
- Apache License 2.0
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.

dnn_from_scratch

Posts with mentions or reviews of dnn_from_scratch. We have used some of these posts to build our list of alternatives and similar projects.

open-lpr

Posts with mentions or reviews of open-lpr. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing dnn_from_scratch and open-lpr you can also consider the following projects:

deepxde - A library for scientific machine learning and physics-informed learning

aimet - AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

HyperGAN - Composable GAN framework with api and user interface

crop - Character Recognition Of Plates using yolov5

ALAE - [CVPR2020] Adversarial Latent Autoencoders

Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.

guesslang - Detect the programming language of a source code

darkflow - Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0

fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:

t81_558_deep_learning - T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

license-plate-recognition - Github Template for EVA applications