semvec/pypi-packages huggingface dataset:
dnnlab 2.2.5
DnnLab

# DnnLab
Dnnlab is a small framework for deep learning models based on TensorFlow.



It provides custom training loops for:
* Generative Models (GAN, cGan, cycleGAN)
* Image Detection (custom YOLO)


Additonaly custom Keras Layer:
* Non-Local-Blocks (Self-Attention)
* Squeeze and Excitation Blocks (SEBlocks)
* YOLO-Decoding Layer

Input pipeline functionality:
* YOLO (Tfrecords to Datasets)
* YOLO data augmentation
* Generative Models (Tfrecords to Datasets)

TensorBoard output:
* YOLO coco metrics (Precision (mAP) & Recall)
* YOLO loss (loss_class, loss_conf, loss_xywh, total_loss)
* YOLO bounding boxes
* Generative Models (Loss & Images)


## Requirements
TensorFlow 2.3.0

## Installation
Run the following to install:
```python
pip install dnnlab
```
roomor 0.3.1
A Python framework for generating and deploying random room for Gazebo
Keywords: gazebo ros simulation robotics randomized-environment reinforcement-learning-environments pcg_gazebo randoor

# roomor: A framework for autogenerating and deploying random room simulation for Gazebo

[![MIT License](https://img.shields.io/badge/license-MIT-green)](https://github.com/wwwshwww/roomor/blob/master/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/roomor)](https://pypi.org/project/roomor/)
![PyPI - Python Version](https://shields.io/pypi/pyversions/roomor)

## Installation

Install using pip:

```bash
pip install roomor
```

If using python2.7, install numpy-quaternion below version before run above command.

```bash
pip install numpy-quaternion==2019.12.11.22.25.52
```

## Implemented generator

 `CubeRoomGenerator`

<img src='https://user-images.githubusercontent.com/41321650/121756680-f059ae80-cb55-11eb-92ac-95700c779590.png' width=50%>
<img src='https://user-images.githubusercontent.com/41321650/121756698-fbacda00-cb55-11eb-939f-fc542fae5e51.png' width=50%>

## Usage

See example ipynb in `example/`.