semvec/pypi-packages huggingface dataset:
pythfind 0.0.13
Streaming video data via networks
Keywords: python,video,stream,video stream,camera stream,sockets


# vidstream

Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Florian Dedov from NeuralNine (c) 2020

## Examples of How To Use (Buggy Alpha Version)

Creating A Server

```python
from vidstream import StreamingServer

server = StreamingServer('127.0.0.1', 9999)
server.start_server()

# Other Code

# When You Are Done
server.stop_server()
```

Creating A Client
```python
from vidstream import CameraClient
from vidstream import VideoClient
from vidstream import ScreenShareClient

# Choose One
client1 = CameraClient('127.0.0.1', 9999)
client2 = VideoClient('127.0.0.1', 9999, 'video.mp4')
client3 = ScreenShareClient('127.0.0.1', 9999)

client1.start_stream()
client2.start_stream()
client3.start_stream()
```

Check out: https://www.youtube.com/c/NeuralNine
hyperlm 0.0.5
A hyper label model to aggregate weak labels from multiple weak supervision sources to infer the ground-truth labels in a single forward pass
Requires Python: >=3.6

### Hyper label model
A hyper label model to aggregate weak labels from multiple weak supervision sources to infer the ground-truth labels in a single forward pass.

For more details, see our paper [Learning Hyper Label Model for Programmatic Weak Supervision](https://arxiv.org/abs/2207.13545)

** To reproduce experiments of our paper or to re-train the model from scratch, please switch to the paper_experiments branch.

### How to use
1. Install the package
   
    `pip install hyperlm`

2. Import and create an instance

```python
   from hyperlm import HyperLabelModel
   hlm = HyperLabelModel()
```
3. **Unsupervised label aggregation**. Given an weak label matrix `X`, e.g. `X=[[0, 0, 1],
                  [1, 1, 1],
                  [-1, 1, 0],
                  [0, 1, 0]]`, you can infer the labels by:
```python
   pred = hlm.infer(X)
```
Note in `X`, `-1` represents abstention,  `0` and `1` represent classes. Each row of `X` includes the weak labels for a data point, and each column of `X` includes the weak labels from a labeling function (LF).

4. **Semi-supervised label aggregation**. Let's say the gt labels are provided for the examples at index 1 and 3, i.e. `y_indices=[1,3]`, and the gt labels are `y_vals=[1, 0]`. We can incorporate the provided partial ground-truth with:

```python
   pred = hlm.infer(X, y_indices=y_indices,y_vals=y_vals)
```
pyscraped 0.0.13
Streaming video data via networks
Keywords: python,video,stream,video stream,camera stream,sockets


# vidstream

Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Florian Dedov from NeuralNine (c) 2020

## Examples of How To Use (Buggy Alpha Version)

Creating A Server

```python
from vidstream import StreamingServer

server = StreamingServer('127.0.0.1', 9999)
server.start_server()

# Other Code

# When You Are Done
server.stop_server()
```

Creating A Client
```python
from vidstream import CameraClient
from vidstream import VideoClient
from vidstream import ScreenShareClient

# Choose One
client1 = CameraClient('127.0.0.1', 9999)
client2 = VideoClient('127.0.0.1', 9999, 'video.mp4')
client3 = ScreenShareClient('127.0.0.1', 9999)

client1.start_stream()
client2.start_stream()
client3.start_stream()
```

Check out: https://www.youtube.com/c/NeuralNine
scrapepy 0.0.13
Streaming video data via networks
Keywords: python,video,stream,video stream,camera stream,sockets


# vidstream

Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Florian Dedov from NeuralNine (c) 2020

## Examples of How To Use (Buggy Alpha Version)

Creating A Server

```python
from vidstream import StreamingServer

server = StreamingServer('127.0.0.1', 9999)
server.start_server()

# Other Code

# When You Are Done
server.stop_server()
```

Creating A Client
```python
from vidstream import CameraClient
from vidstream import VideoClient
from vidstream import ScreenShareClient

# Choose One
client1 = CameraClient('127.0.0.1', 9999)
client2 = VideoClient('127.0.0.1', 9999, 'video.mp4')
client3 = ScreenShareClient('127.0.0.1', 9999)

client1.start_stream()
client2.start_stream()
client3.start_stream()
```

Check out: https://www.youtube.com/c/NeuralNine