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Unverified Commit 9b6b95a8 authored by Reza Mahjourian's avatar Reza Mahjourian Committed by GitHub
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Update vid2depth README.md. (#10198)

Update bike video dataset path.

Add link to TF2 port with build file for compiling the ICP op.
parent b2d3a05c
...@@ -21,6 +21,11 @@ ArXiv: [https://arxiv.org/pdf/1802.05522.pdf](https://arxiv.org/pdf/1802.05522.p ...@@ -21,6 +21,11 @@ ArXiv: [https://arxiv.org/pdf/1802.05522.pdf](https://arxiv.org/pdf/1802.05522.p
<a href="https://sites.google.com/view/vid2depth"><img src='https://storage.googleapis.com/vid2depth/media/approach.png' width=400></a> <a href="https://sites.google.com/view/vid2depth"><img src='https://storage.googleapis.com/vid2depth/media/approach.png' width=400></a>
</p> </p>
## Update: TF2 version.
Please see [https://github.com/IAMAl/vid2depth_tf2](https://github.com/IAMAl/vid2depth_tf2)
for a TF2 implementation of vid2depth.
## 1. Installation ## 1. Installation
### Requirements ### Requirements
...@@ -36,10 +41,6 @@ pip install scipy ...@@ -36,10 +41,6 @@ pip install scipy
pip install tensorflow pip install tensorflow
``` ```
#### For building the ICP op (work in progress)
* Bazel: https://bazel.build/
### Download vid2depth ### Download vid2depth
```shell ```shell
...@@ -60,11 +61,27 @@ unzip "*.zip" ...@@ -60,11 +61,27 @@ unzip "*.zip"
### Download Cityscapes dataset (110GB) (optional) ### Download Cityscapes dataset (110GB) (optional)
You will need to register in order to download the data. Download the following files: You will need to register in order to download the data. Download the following
files:
* leftImg8bit_sequence_trainvaltest.zip * leftImg8bit_sequence_trainvaltest.zip
* camera_trainvaltest.zip * camera_trainvaltest.zip
### Download Bike dataset (34GB) (optional)
Please see [https://research.google/tools/datasets/bike-video/](https://research.google/tools/datasets/bike-video/)
for info on the bike video dataset.
Special thanks to [Guangming Wang](https://guangmingw.github.io/) for helping us
restore this dataset after it was accidentally deleted.
```shell
mkdir -p ~/vid2depth/bike-uncompressed
cd ~/vid2depth/bike-uncompressed
wget https://storage.googleapis.com/vid2depth/dataset/BikeVideoDataset.tar
tar xvf BikeVideoDataset.tar
```
## 3. Inference ## 3. Inference
### Download trained model ### Download trained model
...@@ -113,23 +130,28 @@ python dataset/gen_data.py \ ...@@ -113,23 +130,28 @@ python dataset/gen_data.py \
--seq_length 3 --seq_length 3
``` ```
### Compile the ICP op (work in progress) ### Prepare Bike training sequences (optional)
The ICP op depends on multiple software packages (TensorFlow, Point Cloud
Library, FLANN, Boost, HDF5). The Bazel build system requires individual BUILD
files for each of these packages. We have included a partial implementation of
these BUILD files inside the third_party directory. But they are not ready for
compiling the op. If you manage to build the op, please let us know so we can
include your contribution.
```shell ```shell
# Prepare training sequences.
cd tensorflow/models/research/vid2depth cd tensorflow/models/research/vid2depth
bazel build ops:pcl_demo # Build test program using PCL only. python dataset/gen_data.py \
bazel build ops:icp_op.so --dataset_name bike \
--dataset_dir ~/vid2depth/bike-uncompressed \
--data_dir ~/vid2depth/data/bike \
--seq_length 3
``` ```
For the time being, it is possible to run inference on the pre-trained model and ### Compile the ICP op
run training without the icp loss.
The pre-trained model is trained using the ICP loss. It is possible to run
inference on this pre-trained model without compiling the ICP op. It is also
possible to train a new model from scratch without compiling the ICP op by
setting the icp loss to zero.
If you would like to compile the op and run a new training job using it, please
use the CMakeLists.txt file at
[https://github.com/IAMAl/vid2depth_tf2/tree/master/ops](https://github.com/IAMAl/vid2depth_tf2/tree/master/ops).
### Run training ### Run training
......
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