semvec/pypi-packages huggingface dataset:
autodistill-mobileclip 0.1.0
Model for use with Autodistill
Requires Python: >=3.7

<div align="center">
  <p>
    <a align="center" href="" target="_blank">
      <img
        width="850"
        src="https://media.roboflow.com/open-source/autodistill/autodistill-banner.png"
      >
    </a>
  </p>
</div>

# Autodistill MobileCLIP Module

This repository contains the code supporting the MobileCLIP base model for use with [Autodistill](https://github.com/autodistill/autodistill).

[MobileCLIP](https://github.com/openai/MobileCLIP), developed by OpenAI, is a computer vision model trained using pairs of images and text. You can use MobileCLIP with autodistill for image classification.

Read the full [Autodistill documentation](https://autodistill.github.io/autodistill/).

Read the [MobileCLIP Autodistill documentation](https://autodistill.github.io/autodistill/base_models/mobileclip/).

## Installation

To use MobileCLIP with autodistill, you need to install the following dependency:


```bash
pip3 install autodistill-mobileclip
```

## Quickstart

```python
from autodistill_mobileclip import MobileCLIP
from autodistill.detection import CaptionOntology

# define an ontology to map class names to our MobileCLIP prompt
# the ontology dictionary has the format {caption: class}
# where caption is the prompt sent to the base model, and class is the label that will
# be saved for that caption in the generated annotations
# then, load the model
base_model = MobileCLIP(
    ontology=CaptionOntology(
        {
            "person": "person",
            "a forklift": "forklift"
        }
    )
)
base_model.label("./context_images", extension=".jpeg")
```

## License

MobileCLIP licensed under an [Apple license](LICENSE).

## 🏆 Contributing

We love your input! Please see the core Autodistill [contributing guide](https://github.com/autodistill/autodistill/blob/main/CONTRIBUTING.md) to get started. Thank you 🙏 to all our contributors!
glworia 0.0.0
A package for wave-optics lensing calculations
Requires Python: <3.12,>=3.8

<h1 align="center">
    glworia
</h1>

<h4 align="center"> A python package for gravitational-wave lensing computations including wave-optics effects. </h4>

<p align="center">
    <a href = "https://arxiv.org/abs/0000.00000"><img src="https://img.shields.io/badge/arXiv-0000.00000-b31b1b.svg"></a>
    <a href="https://badge.fury.io/py/glworia"><img src="https://badge.fury.io/py/glworia.svg"></a>
    <a href="https://github.com/mhycheung/glworia/actions/workflows/pytest.yml "><img src="https://github.com/mhycheung/glworia/actions/workflows/pytest.yml/badge.svg"></a>
    <a href="https://github.com/mhycheung/glworia/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg"></a>
    <a href="https://pypi.org/project/glworia/"><img src="https://img.shields.io/pypi/pyversions/glworia"></a>
    <a href="https://mhycheung.github.io/glworia/"><img src="https://badgen.net/badge/Read/the doc/blue" alt="doc"/></a>
</p>

## Key Features

* Compute the frequency-dependent lensing amplification factor
* Use your custom lens model, any spherically symmetry lens is supported
* The only function you need to provide is the Fermat potential - `jax` will take care of the rest with auto differentiation!
* Build interpolation tables for your lens model
* Perform Bayesian parameter estimation with `bilby`
* Runs on GPUs

## Installation

```shell
pip install glworia
```

## Usage

Checkout the 'Tutorial' section on the documentation website.

## Parameter estimation results

The full corner plots for the parameter estimation runs shown in the companion paper can be found in the `plots/` directory.

## How to Cite
Please cite the methods paper if you used our package to produce results in your publication.
Here is the BibTeX entry:
```
Coming soon!
```

## License

MIT

---

> GitHub [@mhycheung](https://github.com/mhycheung)
py-ecp 1.5.0
ECP programming language
Requires Python: >=3.6

# pseudocode-interpreter

CC BY-SA 2021 Alfred Taylor & Conqu3red

# **(AQA) Exam Compatible Psuedocode V1 ALPHA (A.E.C.P/E.C.P)**

## `PLEASE EXPECT LIMITED FUNCTIONALITY.`

## Introduction:

This is an adaptation of the pseudocode used by the AQA GCSE testing body (found [here](https://filestore.aqa.org.uk/resources/computing/AQA-8525-NG-PC.PDF)) that has had its syntax tweaked for use in a compiler and had some additional functionality added. The language will be fully Turing complete. Pseudocode found in tests is compatible with AECP/ECP. It is procedurally based, and shares similarities with python (It is programmed on python, after all.) It is intended as a scripting language, that is separate from python, but has the same basic functionality, whilst maintaining some resemblance of simplicity. Considering it is entirely written in python, it is not for use in situations where speed is a priority.

**Interpreters**

Currently we only have a python based interpreter, altough we have a C++ based interpreter coming soon.

**How it works**

AECP/ECP code is analysed and then parsed into a python AST (Abstract Syntax Tree). This can then be executed by the python interpreter. This allows near seamless integration with python and almost identical speed and behaviour.

# Usage

## Command Line arguments

```
usage: python -m ecp [-h] [--debug] [--trace [TRACE [TRACE ...]]] [--tracecompact] [--pause] [--version] [inputfile]

ECP interpreter

positional arguments:
  inputfile

optional arguments:
  -h, --help            show this help message and exit
  --debug               show debug information like token list
  --trace [TRACE [TRACE ...]]
                        space seperated names of the variables to be traced
  --tracecompact        trace compactly
  --pause               pause on completion
  --version             show program's version number and exit
```

# Installation

```
pip install py-ecp
```

## Running

```
python -m ecp path/to/ecp/file.ecp
```

## Embedding ecp code in python files

```python
from ecp import ecp

ecp("""
SUBROUTINE TotalOut(a, b)
    c ← a + b
    WHILE a < c
        a ← a + 1
        b ← b - a
    ENDWHILE
    RETURN b
ENDSUBROUTINE
""", scope=globals())

print(TotalOut(3, 4))
```

## Converting ECp to python source code

```
python -m ecp path/to/ecp/file.ecp --topython
```

or:

```python
from ecp import to_py_source
text = """
SUBROUTINE DoSomething(a, b)
    RETURN a + b
ENDSUBROUTINE
"""

print(to_py_source(text))
```

# MORE COMING SOON!