semvec/pypi-packages huggingface dataset:
autodistill-owlv2 0.1.1
OWLv2 base model for use with Autodistill.
Requires Python: >=3.7

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# Autodistill OWLv2 Module

This repository contains the code supporting the OWLv2 base model for use with [Autodistill](https://github.com/autodistill/autodistill).

OWLv2 is a zero-shot object detection model that follows from on the OWL-ViT architecture. OWLv2 has an open vocabulary, which means you can provide arbitrary text prompts for the model. You can use OWLv2 with autodistill for object detection.

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

Read the [OWLv2 Autodistill documentation](https://autodistill.github.io/autodistill/base_models/owlv2/).

## Installation

To use OWLv2 with autodistill, you need to install the following dependency:


```bash
pip3 install autodistill-owlv2
```

## Quickstart

```python
from autodistill_owlv2 import OWLv2
from autodistill.detection import CaptionOntology

# define an ontology to map class names to our OWLv2 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 = OWLv2(
    ontology=CaptionOntology(
        {
            "person": "person",
            "a forklift": "forklift"
        }
    )
)

# run inference on a single image
results = base_model.predict("./context_images/image.png")

base_model.label("./context_images", extension=".jpeg")
```


## License

This model is licensed under an [Apache 2.0](LICENSE) ([see original model implementation license](https://huggingface.co/docs/transformers/main/en/model_doc/owlv2), and the corresponding [HuggingFace Transformers documentation](https://huggingface.co/docs/transformers/main/en/model_doc/owlv2)).

## 🏆 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!
trader-core 1.0.0
A trading core which allows fundamental analysis of stocks
Requires Python: >=3.8

# Trader-Core

Trader-Core is a Python library designed for performing fundamental analysis on stock market data. It provides a set of tools and functionalities to analyze and extract insights from financial data, aiding in decision-making for trading and investment purposes.

## Features

- **Fundamental Analysis:** Conduct comprehensive fundamental analysis of stock market data.
- **Data Processing:** Efficiently process and clean financial data for analysis.
- **Key Financial Metrics:** Calculate and analyze key financial metrics.
- **Valuation Models:** Implement various valuation models to evaluate stocks.
- **Financial Ratios:** Compute and interpret essential financial ratios for investment analysis.
- **Data Visualization:** Visualize data and analysis results using charts and graphs.

## Installation

To install trader-core, simply use pip:

```bash
pip install trader-core
ChainExAPI 0.1.0
Python client library for interacting with the ChainEx cryptocurrency exchange API.
Requires Python: >=3.6
Keywords: chainex cryptocurrency exchange api

# ChainExAPI Python Client

## Overview

ChainExAPI is a Python client library for interacting with the ChainEx cryptocurrency exchange API. It provides a convenient way to integrate ChainEx's services into your Python applications.

## Features

- Easy to use methods for market, wallet, and trading operations.
- HMAC-SHA-256 authentication for secure API calls.
- Fetch market summaries, statistics, trades, and orders.
- Manage wallet balances, deposits, withdrawals, and addresses.
- Execute and manage trading orders and trades.

## Installation

You can install the ChainExAPI library via pip:

```bash
pip install chainexapi
```

## Quick Start

Here's a quick example to get you started:

```python
from chainex import ChainExAPI

# Initialize the API client
client = ChainExAPI('your_public_key', 'your_private_key')

# Fetch market summary
market_summary = client.get_market_summary('BTC_ETH')
print(market_summary)

# Fetch wallet balances
wallet_balances = client.get_wallet_balances()
print(wallet_balances)
```

## Usage

### Initializing the Client

First, import the `ChainExAPI` class and initialize it with your public and private API keys:

```python
from chainex import ChainExAPI

client = ChainExAPI('your_public_key', 'your_private_key')
```

### Market Methods

- `get_market_summary(exchange)`: Fetches market summary for a given exchange.
- `get_market_stats(coin, exchange)`: Fetches market statistics for a given coin and exchange.
- ... (and so on for other market methods)

### Wallet Methods

- `get_wallet_balances(coin=None)`: Fetches wallet balances.
- `get_wallet_deposits(coin="ALL", start=0, limit=25)`: Fetches wallet deposits.
- ... (and so on for other wallet methods)

### Trading Methods

- `get_trading_orders(coin="ALL", start=0, limit=25)`: Fetches trading orders.
- `add_order(coin, exchange, price, amount, order_type)`: Adds an order to a specified market.
- ... (and so on for other trading methods)

## Contributing

Contributions to the ChainExAPI library are welcome! Please feel free to submit issues and pull requests to the repository.

## License

This project is licensed under the [MIT License](LICENSE).
seadu 0.1.1
Seafile Downloader and Uploader

# Seadu

Seadu is a command-line tool used for uploading and downloading files from specific Seafile library.

# Usage

1. Install

```bash
apt install -y pipx && pipx install seadu
```

2. Initial

You need to add the library API Token manually. The configuration file will be saved in `~/.seadu/config.json`.

```bash
seadu init -s YOUT_SERVER -t YOUR_TOKEN
```

The `-s` option should be entered as a full URL containing `http://`/`https://` without a slash at the end, e.g. https://cloud.seafile.com

3. Download/Upload

```bash
seadu down DIR_TO_STORE
seadu up DIR_TO_UPLOAD
```