# obman

**Repository Path**: jackmacoder/obman

## Basic Information

- **Project Name**: obman
- **Description**: image for obman
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-04-27
- **Last Updated**: 2023-04-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Learning Joint Reconstruction of Hands and Manipulated Objects - ObMan dataset

Yana Hasson, Gül Varol, Dimitris Tzionas, Igor Kalevatykh, Michael J. Black,  Ivan Laptev, Cordelia Schmid, CVPR 2019

- [Project page](https://hassony2.github.io/obman)
- [Training code and model](https://github.com/hassony2/obman_train)
- [GraspIt grasps generation using MANO](https://github.com/ikalevatykh/mano_grasp)
- [Dataset generation](https://github.com/hassony2/obman_render)

# Download required files

## Download dataset images and data

- Request the dataset on the [ObMan webpage](https://www.di.ens.fr/willow/research/obman/data/). Note that the data falls under the following [license](https://www.di.ens.fr/willow/research/obman/data/license.html)
- unzip obman.zip to /path/to/obman
- Your dataset structure should look like

```
obman/
  test/
    rgb/
    rgb_obj/
    meta/
    ...
  val/
    rgb/
    rgb_obj/
    meta/
    ...
```

## Download object meshes

- Download object models from ShapeNet
  - Create an account on [shapenet.org](https://www.shapenet.org)
  - Download models from [download page](https://www.shapenet.org/download/shapenetcore)


# Download code

`git clone https://github.com/hassony2/obman`

`cd obman`

# Load samples

`python readataset --root /path/to/obman --shapenet_root /path/to/ShapeNetCore.v2 --split test --viz`

Options you might be interested in `--segment` which keeps only the foreground `--mini_factor 0.01` to load only 1% of the data (to speed-up loading)

# Preprocess shapenet objects for training

Sample points on the external surface of the object:

`python shapenet_samplepoints.py`

## Visualizations

### Hand object and mesh in camera coordinates

![image](assets/viz3d.png)

### Projected in pixel space

Hand vertices in blue, object vertices in red.

![image](assets/viz2d.png)


# Citations

If you find this dataset useful for your research, consider citing:

```
@INPROCEEDINGS{hasson19_obman,
  title     = {Learning joint reconstruction of hands and manipulated objects},
  author    = {Hasson, Yana and Varol, G{\"u}l and Tzionas, Dimitris and Kalevatykh, Igor and Black, Michael J. and Laptev, Ivan and Schmid, Cordelia},
  booktitle = {CVPR},
  year      = {2019}
}
```