Mask-RCNN-TF2
ssd_keras
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Mask-RCNN-TF2 | ssd_keras | |
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1 | 4 | |
299 | 1,846 | |
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1.3 | 0.0 | |
about 1 year ago | about 2 years ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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Mask-RCNN-TF2
ssd_keras
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Failed to get convolution algorithm. This is probably because cuDNN failed to initialize,
In Tensorflow/ Keras when running the code from https://github.com/pierluigiferrari/ssd_keras, use the estimator: ssd300_evaluation. I received this error.
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Shared weights between different implementations
Yeah, the order of axes was different between those 2. Another guy used https://github.com/pierluigiferrari/ssd_keras https://github.com/uhfband/keras2caffe/blob/master/keras2caffe/convert.py probably not much actual use but maybe some more reassurance?
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Simplest way to deploy Keras NN model into C++?
Don't know about simplest, but we either used caffe or tensorrt, it is maybe a bit difficult to use but I'd actually say simple fast GPU inference is what it's geared towards. There is a keras -> caffe converter https://github.com/pierluigiferrari/ssd_keras here, I think. Caffe is a c++ lib, typical, with dependencies and all. I've never heard anything of tensorflow running on c++. But with tensorrt you should get an "artifact" that you'd load, no matter where it comes from
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ValueError: Layer model expects 1 input(s), but it received 2 input tensors. Help?
Tensorflow V1 Keras code (original repo): Github Repo
What are some alternatives?
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
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
InvoiceNet - Deep neural network to extract intelligent information from invoice documents.
cppflow - Run TensorFlow models in C++ without installation and without Bazel
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.
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
These-People-Do-Not-Exist - AI that generates human faces which have never been seen before. The future is now 😁
efficientnet-lite-keras - Keras reimplementation of EfficientNet Lite.
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
a-PyTorch-Tutorial-to-Object-Detection - SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.
SSD-pytorch - SSD: Single Shot MultiBox Detector pytorch implementation focusing on simplicity