a-PyTorch-Tutorial-to-Object-Detection
ssd_keras
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a-PyTorch-Tutorial-to-Object-Detection | ssd_keras | |
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3 | 4 | |
2,960 | 1,846 | |
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4.9 | 0.0 | |
6 months ago | about 2 years ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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a-PyTorch-Tutorial-to-Object-Detection
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Beginner : Object (shape) detection in binary images
I have also experimented with SSD300 models from this example : https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Object-Detection but again, I think the lack of RGB/greyscale data makes this largely useless ?
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Learning resources: multi-object localization
Also, this SSD walkthrough is pretty good as well and goes into a lot more depth on the concepts.
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What is an easy way to find an image within another image?
Something like this perhaps? https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Object-Detection
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?
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
SSD-pytorch - SSD: Single Shot MultiBox Detector pytorch implementation focusing on simplicity
cppflow - Run TensorFlow models in C++ without installation and without Bazel
mmdetection - OpenMMLab Detection Toolbox and Benchmark
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
efficientnet-lite-keras - Keras reimplementation of EfficientNet Lite.
CRAFT-pytorch - Official implementation of Character Region Awareness for Text Detection (CRAFT)
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
TensorFlow-object-detection-tutorial - The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch