semvec/pypi-packages huggingface dataset:
ocgan 1.0
Tensorflow implementation of OCGAN
License: MIT

# Tensorflow Implementation of OCGAN
This repository provides a [Tensorflow](https://www.tensorflow.org/) implementation of the *OCGAN* presented in
CVPR 2019 paper "[OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations](http://openaccess.thecvf.com/content_CVPR_2019/papers/Perera_OCGAN_One-Class_Novelty_Detection_Using_GANs_With_Constrained_Latent_Representations_CVPR_2019_paper.pdf)".

The author's implementation of *OCGAN* in MXNet is at [here](https://github.com/PramuPerera/OCGAN).


## Installation
This code is written in `Python 3.5` and tested with `Tensorflow 1.13`.

Install using pip or clone this repository.

1. Installation using pip:
```bash
pip install ocgan
```

and

```python
from ocgan import OCGAN
```

2. Clone this repository:

```bash
git clone https://github.com/nuclearboy95/Deep-SVDD-Tensorflow.git
```
get-video-properties 0.1.1
Get video properties
License: MIT
Keywords: ffprobe video audio

python-get-video-properties
===

Get video properties

Installation
---

```sh
pip install -U get-video-properties
```

Usage
---

```python
from videoprops import get_video_properties

props = get_video_properties('movie.mp4')

print(f'''
Codec: {props['codec_name']}
Resolution: {props['width']}×{props['height']}
Aspect ratio: {props['display_aspect_ratio']}
Frame rate: {props['avg_frame_rate']}
''')
```

**Sample output**

```text
Codec: h264
Resolution: 1920×1080
Aspect ratio: 16:9
Frame rate: 25/1
```

Usage (audio)
---

```python
from videoprops import get_audio_properties

props = get_audio_properties('movie.mp4')

print(f'''
Codec: {props['codec_name']}
Channels: {props['channels']}
Sample rate: {props['sample_rate']}
''')
```

**Sample output**

```text
Codec: opus
Channels: 2
Sample rate: 48000
```

Command-line usage
---

```sh
videoprops movie.mp4
audioprops movie.mp4
```