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Faster R-CNN guide

Faster R-CNN is a really classical two-stage framework for object detection. Common tensorflow versions are often in complicated class implementation. For beginner or fresher, reading those codes is very hard. So I build this repo reproducing the Faster R-CNN by tensorflow without any complicated class, just functions and sufficient comments. It is easy to read and understand. The project can guide you to build your own Faster R-CNN framework. Hope you like this. You also can give any advise for this repo, welcome to technical exchange (as well as my English mistakes). :)

Features

  • No class implementations
  • Sufficient comments
  • Easy to read and understand
  • Tensorboard shows rpn and rcnn results
  • Training in a toy dataset, no download large datasets
  • Training in large dataset(late support)

Requires

Tensorflow >= 1.11 opencv >= 3.4.0

Usage

Training toy dataset

  1. Batch size == 1 python train.py
  2. Batch size > 1 python train_batch.py
  • COCO is not available.

Testing

python test.py

Use Tensorboard

tensorboard --logdir=./logs

Next

  • Add references.
  • Add MobileNet.
  • Training with other datasets as COCO or VOC.

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Reproduction of Faster R-CNN by tensorflow.

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