dnn_from_scratch VS Mask-RCNN-TF2

Compare dnn_from_scratch vs Mask-RCNN-TF2 and see what are their differences.

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dnn_from_scratch Mask-RCNN-TF2
1 1
29 299
- -
0.0 1.3
almost 3 years ago about 1 year ago
Python Python
- 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.
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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.

Mask-RCNN-TF2

Posts with mentions or reviews of Mask-RCNN-TF2. 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 Mask-RCNN-TF2 you can also consider the following projects:

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

albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

HyperGAN - Composable GAN framework with api and user interface

InvoiceNet - Deep neural network to extract intelligent information from invoice documents.

ALAE - [CVPR2020] Adversarial Latent Autoencoders

ssd_keras - A Keras port of Single Shot MultiBox Detector

guesslang - Detect the programming language of a source code

medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

open-lpr - Open Source and Free License Plate Recognition Software

These-People-Do-Not-Exist - AI that generates human faces which have never been seen before. The future is now 😁

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

FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.