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https://github.com/ZhijianJiang/DispNet-TensorFlow
TensorFlow implementation of DispNet by Zhijian Jiang.
https://github.com/ZhijianJiang/DispNet-TensorFlow
convolutional-networks dispnet-tensorflow stereo-vision tensorflow
Last synced: about 2 months ago
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TensorFlow implementation of DispNet by Zhijian Jiang.
- Host: GitHub
- URL: https://github.com/ZhijianJiang/DispNet-TensorFlow
- Owner: ZhijianJiang
- Created: 2017-07-18T13:26:40.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2024-02-24T05:59:50.000Z (7 months ago)
- Last Synced: 2024-04-12T02:25:50.841Z (5 months ago)
- Topics: convolutional-networks, dispnet-tensorflow, stereo-vision, tensorflow
- Language: Python
- Size: 9.77 KB
- Stars: 58
- Watchers: 5
- Forks: 24
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# DispNet-TensorFlow
This project is no longer under active development, so please exercise caution when using it and I hope it can still be helpful to you :)
TensorFlow implementation of [A Large Dataset to Train Convolutional Networks
for Disparity, Optical Flow, and Scene Flow Estimation](http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Mayer_A_Large_Dataset_CVPR_2016_paper.pdf) by Zhijian Jiang.
## Dataset
* [Scene Flow Datasets: FlyingThings3D, Driving, Monkaa](https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html)
## Tutorials
### TensorFlow
* [Tensorflow tutorials (Eng Sub) 神经网络 教学 教程](https://www.youtube.com/watch?v=RSRkp8VAavQ&list=PLXO45tsB95cKI5AIlf5TxxFPzb-0zeVZ8)
## Network
### Convolutional Network
|Name | Kernel | Strides | Channels I/O | Input Resolution | Output Resolution | Input |
|--- | --- | --- | --- | --- | --- | --- |
|conv1 | 7 * 7 | 1 | 6/64 | 1536 * 768 | 768 * 384 | Images |
|max_pool1 | 2 * 2 | 2 | 64/64 | 1536 * 768 | 768 * 384 | conv1 |
|conv2 | 5 * 5 | 1 | 64/128 | 768 * 384 | 384 * 192 | max_pool1 |
|max_pool2 | 2 * 2 | 2 | 128/128 | 768 * 384 | 384 * 192 | conv2|
|conv3a | 5 * 5 | 1 | 128/256 | 384 * 192 | 192 * 96 | max_pool2|
|max_pool3 | 2 * 2 | 2 | 256/256 | 384 * 192 | 192 * 96 | conv3a|
|conv3b | 3 * 3 | 1 | 256/256 | 192 * 96 | 192 * 96 | max_pool3|
|conv4a | 5 * 5 | 1 | 256/512 | 192 * 96 | 96 * 48 | conv3b|
|max_pool4 | 2 * 2 | 2 | 512/512 | 96 * 48 | 96 * 48 | conv4a|
|conv4b | 3 * 3 | 1 | 512/512 | 96 * 48 | 96 * 48 | max_pool4|
|conv5a | 5 * 5 | 1 | 512/512 | 96 * 48 | 48 * 24 | conv4b|
|max_pool5 | 2 * 2 | 2 | 512/512 | 48 * 24 | 48 * 24 | conv5a|
|conv5b | 3 * 3 | 1 | 512/512 | 48 * 24 | 48 * 24 | max_pool5|
|conv6a | 5 * 5 | 1 | 512/512 | 48 * 24 | 24 * 12 | conv5b|
|max_pool6 | 2 * 2 | 2 | 1024/1024 | 24 * 12 | 24 * 12 | conv6a|
|conv6b | 3 * 3 | 1 | 1024/1024 | 24 * 12 | 24 * 12 | max_pool6|
|pr6 + loss6 | 3 * 3 | 1 | 1024/1 | 24 * 12 | 24 * 12 | conv6b|
### Upconvolutional Network
|Name | Kernel | Strides | Channels I/O | Input Resolution | Output Resolution | Input |
|--- | --- | --- | --- | --- | --- | ---|
|upconv5 | 4 * 4 | 2 | 1024/512 | 24 * 12 | 48 * 24 | conv6b|
|iconv5 | 3 * 3 | 1 | 1024/512 | 48 * 24 | 48 * 24 | upconv5 + conv5b|
|pr5+loss5 | 3 * 3 | 1 | 512/1 | 48 * 24 | 48 * 24 | iconv5|
|upconv4 | 4 * 4 | 2 | 512/256 | 48 * 24 | 96 * 48 | iconv5|
|iconv4 | 3 * 3 | 1 | 768/256 | 96 * 48 | 96 * 48 | upconv4 + conv4b|
|pr4+loss4 | 3 * 3 | 1 | 512/1 | 96 * 48 | 96 * 48 | iconv4|
|upconv3 | 4 * 4 | 2 | 256/128 | 96 * 48 | 192 * 96 | iconv4|
|iconv3 | 3 * 3 | 1 | 384/128 | 192 * 96 | 192 * 96 | upconv3 + conv3b|
|pr3+loss3 | 3 * 3 | 1 | 128/1 | 192 * 96 | 192 * 96 | iconv3|
|upconv2 | 4 * 4 | 2 | 128/64 | 192 * 96 | 384 * 192 | iconv3|
|iconv2 | 3 * 3 | 1 | 192/64 | 384 * 192 | 384 * 192 | upconv2 + conv2|
|pr2+loss2 | 3 * 3 | 1 | 64/1 | 384 * 192 | 384 * 192 | iconv2|
|upconv1 | 4 * 4 | 2 | 64/32 | 384 * 192 | 768 * 384 | iconv2|
|iconv1 | 3 * 3 | 1 | 96/32 | 768 * 384 | 768 * 384 | upconv1 + conv1|
|pr1+loss1 | 3 * 3 | 1 | 32/1 | 768 * 384 | 768 * 384 | iconv1|
## Issues
* How to input png images:
* [Solution 1 -- FAIL](https://github.com/tensorflow/models/issues/564):
```
contents = ''
with open('path/to/image.jpeg') as f:
contents = f.read()
tf.image.decode_jpeg(contents)
```
* [Solution 2 -- FAIL](http://stackoverflow.com/questions/34340489/tensorflow-read-images-with-labels)
```
reader = tf.WholeFileReader(http://stackoverflow.com/questions/34340489/tensorflow-read-images-with-labels)
key, value = reader.read(filename_queue)
example = tf.image.decode_png(value)
```
* [Solution 3 -- Success](http://stackoverflow.com/questions/34340489/tensorflow-read-images-with-labels)
```
file_contents = tf.read_file(input_queue[0])
example = tf.image.decode_png(file_contents, channels=3)