semvec/pypi-packages huggingface dataset:
aihttps 0.1.1
A high-level deep learning library build on top of PyTorch for classification problems...
License: MIT
Requires Python: >=3.6

<p align="center">
  <img src="images/logo.png" alt="tensornet" />
  <br />
  <br />
  <img src="https://img.shields.io/badge/version-0.1.1-blue.svg" alt="Version">
  <a href="https://github.com/shan18/TensorNet/blob/master/LICENSE"><img src="https://img.shields.io/apm/l/atomic-design-ui.svg?" alt="MIT License"></a>
  <br />
</p>

torch_soft is a high level implementatio of pytorch for some of claasification implementation with ease...

## features
TensorNet currently supports the following features
- Model architectures
  - ResNet18
  - A custom model called naiveresnet
- Model utilities
  - Loss functions
    - Cross entropy loss
    - nll_loss
  - Optimizers
    - Stochastic Gradient Descent
  - Regularizers
    - L1 regularization
    - L2 regularization
  - LR Schedulers
    - Step LR
    - Reduce LR on Plateau
    - One Cycle Policy
  - LR Range Test
- Model training and validation
- Datasets (data is is returned via data loaders)
  - MNIST
  - CIFAR10
  - TinyImageNet
- Data Augmentation
  - Resize
  - Padding
  - Random Crop
  - Horizontal Flip
  - Vertical Flip
  - Gaussian Blur
  - Random Rotation
  - CutOut
- GradCAM and GradCAM++ (Gradient-weighted Class Activation Map)
- Result Analysis Tools
  - Plotting changes in validation accuracy and loss during model training
  - Displaying correct and incorrect predictions of a trained model
  - Plotting images in a batch for visualization
  - Plotting gradcam outputs

## How to Use

For examples on how to use torch_soft, refer to the [examples](https://github.com/millermuttu/torch_soft/tree/master/examples) directory.

## Dependencies

torch_soft has the following third-party dependencies
- torch
- torchvision
- torchsummary
- tqdm
- matplotlib
- albumentations
- opencv-python
capsolver-python 1.0
CapSolver.com library for Python
License: MIT
Requires Python: >=3

CapSolver.com package for Python
=
![PyPI - Wheel](https://img.shields.io/pypi/wheel/capsolver_python?style=plastic) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/capsolver_python?style=flat) ![GitHub last commit](https://img.shields.io/github/last-commit/alperensert/capsolver_python?style=flat) ![GitHub release (latest by date)](https://img.shields.io/github/v/release/alperensert/capsolver_python?style=flat) ![PyPI - Downloads](https://img.shields.io/pypi/dm/capsolver_python?style=flat) ![GitHub code size in bytes](https://img.shields.io/github/languages/code-size/alperensert/capsolver_python?style=flat) ![GitHub Repo stars](https://img.shields.io/github/stars/alperensert/capsolver_python?style=social) 

[CapSolver.com](https://capsolver.com) package for Python3

Register now from [here](https://dashboard.capsolver.com/passport/register?inviteCode=kXa8cbNF-b2l).

If you have any problem with usage, [read the documentation](https://github.com/alperensert/capsolver_python/wiki) or [create an issue](https://github.com/alperensert/capsolver_python/issues/new)

### Installation
```
pip install capsolver_python
```

### Supported captcha types
- Image to Text
- Recaptcha V2
- Recaptcha V2 Enterprise
- Recaptcha V3
- FunCaptcha
- HCaptcha
- GeeTest
- AntiAkamaiBMP
- HCaptcha Classification
- DataDome Slider
- FunCaptcha Classification

Usage examples
-

#### ImageToText

```python
from capsolver_python import ImageToTextTask

capsolver = ImageToTextTask("API_KEY")
task_id = capsolver.create_task(image_path="img.png")
result = capsolver.join_task_result(task_id)
print(result.get("text"))
```

#### Recaptcha v2

```python
from capsolver_python import RecaptchaV2Task

capsolver = RecaptchaV2Task("API_KEY")
task_id = capsolver.create_task("website_url", "website_key")
result = capsolver.join_task_result(task_id)
print(result.get("gRecaptchaResponse"))
```

#### Recaptcha v2 enterprise

```python
from capsolver_python import RecaptchaV2EnterpriseTask

capsolver = RecaptchaV2EnterpriseTask("API_KEY")
task_id = capsolver.create_task("website_url", "website_key", {"s": "payload value"}, "api_domain")
result = capsolver.join_task_result(task_id)
print(result.get("gRecaptchaResponse"))
```

#### GeeTest

```python
from capsolver_python import GeeTestTask

capsolver = GeeTestTask("API_KEY")
task_id = capsolver.create_task("website_url", "gt", "challenge")
result= capsolver.join_task_result(task_id)
print(result.get("challenge"))
print(result.get("seccode"))
print(result.get("validate"))
```

For other examples and api documentation please visit [wiki](https://captchaai.atlassian.net/wiki/spaces/CAPTCHAAI/overview)