# Faster-RCNN-TensorFlow-Python3.5

**Repository Path**: EscapeReality846089495/Faster-RCNN-TensorFlow-Python3.5

## Basic Information

- **Project Name**: Faster-RCNN-TensorFlow-Python3.5
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-24
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# tf-faster-rcnn
Tensorflow Faster R-CNN for Windows and Linux by using Python 3.5

This is the branch to compile Faster R-CNN on Windows and Linux. It is heavily inspired by the great work done [here](https://github.com/smallcorgi/Faster-RCNN_TF) and [here](https://github.com/rbgirshick/py-faster-rcnn). I have not implemented anything new but I fixed the implementations for Windows and Python 3.5.

### PLEASE BE AWARE: I do not have time or intention to fix all the issues for this branch as I do not use it commercially. I created this branch just for fun. If you want to make any commitment, it is more than welcome. Tensorflow has already released an object detection api. Please refer to it. https://github.com/tensorflow/models/tree/master/research/object_detection

### If you find a solution to an existing issue in the code, please send a PR for it. 

### Also, instead of trying to deal with Tensorflow, use Chainer. It is ready to be used with all the common models https://github.com/chainer/chainercv & https://github.com/chainer/chainer . I can reply all of your questions about Chainer

# How To Use This Branch
1- Install tensorflow, preferably GPU version. Follow [instructions]( https://www.tensorflow.org/install/install_windows). If you do not install GPU version, you need to comment out all the GPU calls inside code and replace them with relavent CPU ones.

2- Install python packages (cython, python-opencv, easydict)

3- Checkout this branch

4- Go to  ./data/coco/PythonAPI

      Run `python setup.py build_ext --inplace`

      Run `python setup.py build_ext install`

Go to ./lib/utils and run `python setup.py build_ext --inplace`

5- Follow this instruction to download PyCoco database. [Link]( https://github.com/rbgirshick/py-faster-rcnn#beyond-the-demo-installation-for-training-and-testing-models)

I will be glad if you can contribute with a batch script to automatically download and fetch. The final structure has to look like

        "data/VOCDevkit2007/annotations_cache"
  
        "data/VOCDevkit2007/VOC2007"
  
 6- Download pre-trained VGG16 from [here](http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz) and place it as "data\imagenet_weights\vgg16.ckpt"
 
 For rest of the models, please check [here](https://github.com/tensorflow/models/tree/master/research/slim#pre-trained-models)
 
  7- Run train.py
  
  Notify me if there is any issue found. Please note that, I have compiled cython modules with sm61 architecture (GTX 1060, 1070 etc.). Compile support for other architectures will be added.