Home | Tutorials | Wiki | Issues
Ask Your Question

Revision history [back]

click to hide/show revision 1
initial version

Camera plugin for model segmentation

Hi,

I would like to use Gazebo to produce a dataset to train an NN-based autoencoder to perform semantic segmentation (ex: https://www.cityscapes-dataset.com/).
The ideal output format for doing so would be that the resulting image is a mask where the pixel value is the "number of the model" in the scene, or eventually separate channels for each model.

Let's say my world is a room with 4 walls a door and a plant inside

So in the first case, the pixel value of the resulting image would range from 0 to 5 1- ground 2- walls 3- ceiling 4- door 5- plant 0- anything else

In the second case instead (multiple channels) the pixel value range will always be 0 or 1 but each of the 5 channel will only mask a specific model.

In case there is not such a plugin, does anyone have ideas or resources about to implement it?

Camera plugin for model segmentation

Hi,

I would like to use Gazebo to produce a dataset to train an NN-based autoencoder to perform semantic segmentation (ex: https://www.cityscapes-dataset.com/).
The ideal output format for doing so would be that the resulting image is a mask where the pixel value is the "number of the model" in the scene, or eventually separate channels for each model.

Let's say my world is a room with 4 walls a door and a plant inside

inside So in the first case, the pixel value of the resulting image would range from 0 to 5 1- ground ground
2- walls walls
3- ceiling ceiling
4- door door
5- plant plant
0- anything elseelse

In the second case instead (multiple channels) the pixel value range will always be 0 or 1 but each of the 5 channel will only mask a specific model.

In case there is not such a plugin, does anyone have ideas or resources about to implement it?

Camera plugin for model segmentation

Hi,

I would like to use Gazebo to produce a dataset to train an NN-based autoencoder to perform semantic segmentation (ex: https://www.cityscapes-dataset.com/).
The ideal output format for doing so would be that the resulting image is a mask where the pixel value is the "number of the model" in the scene, or eventually separate channels for each model.

semantic segmentation example

Let's say my world is a room with 4 walls a door and a plant inside So in the first case, the pixel value of the resulting image would range from 0 to 5 1- ground
2- walls
3- ceiling
4- door
5- plant
0- anything else

In the second case instead (multiple channels) the pixel value range will always be 0 or 1 but each of the 5 channel will only mask a specific model.

In case there is not such a plugin, does anyone have ideas or resources about to implement it?it?!

Camera plugin for model segmentation

Hi,

I would like to use Gazebo to produce a dataset to train an NN-based autoencoder to perform semantic segmentation (ex: https://www.cityscapes-dataset.com/).
The ideal output format for doing so would be that the resulting image is a mask where the pixel value is the "number of the model" in the scene, or eventually separate channels for each model.

semantic segmentation examplesemantic segmentation example

Let's say my world is a room with 4 walls a door and a plant inside So in the first case, the pixel value of the resulting image would range from 0 to 5 1- ground
2- walls
3- ceiling
4- door
5- plant
0- anything else

In the second case instead (multiple channels) the pixel value range will always be 0 or 1 but each of the 5 channel will only mask a specific model.

In case there is not such a plugin, does anyone have ideas or resources about to implement it?!it?