semvec/pypi-packages huggingface dataset:
MahaPala 2023.12.16
Detection of fruits disease by using Machine learning

# MahaPala
Detection of fruits disease by using Machine learning


## Indentification Of Fruits

Create class to indentify the fruit names tested it for Guava & Mango fruits

* Deep learning algorithm 
* adam optimizer
* relu activation

## Reference

* https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4245116/


## Model: sequential
```
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 rescaling (Rescaling)       (None, 224, 224, 3)       0         
                                                                 
 conv2d (Conv2D)             (None, 224, 224, 16)      448       
                                                                 
 max_pooling2d (MaxPooling2  (None, 112, 112, 16)      0         
 D)                                                              
                                                                 
 conv2d_1 (Conv2D)           (None, 112, 112, 32)      4640      
                                                                 
 max_pooling2d_1 (MaxPoolin  (None, 56, 56, 32)        0         
 g2D)                                                            
                                                                 
 conv2d_2 (Conv2D)           (None, 56, 56, 64)        18496     
                                                                 
 max_pooling2d_2 (MaxPoolin  (None, 28, 28, 64)        0         
 g2D)                                                            
                                                                 
 flatten (Flatten)           (None, 50176)             0         
                                                                 
 dense (Dense)               (None, 128)               6422656   
                                                                 
 dense_1 (Dense)             (None, 5)                 645       
                                                                 
=================================================================
Total params: 6446885 (24.59 MB)
Trainable params: 6446885 (24.59 MB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________

```
# Dashboard 

![image](https://github.com/AbhimanyuHK/MahaPala/assets/32696360/59d1720c-316d-4f46-a5e8-17e93e6b70aa)

  
## Release Note

## 2023.12.16
* #9 Create a sample to identify the fruits name
* #11 Implement visualization dashboard

### 2021.11.01
* #9 Create a sample to identify the fruits name

### 2020.11.01.dev
* Initial setup and environments
* Added a templete matching algorithm
forgecloud 0.0.21
A package to connect and manage Forge apps with Google Cloud Functions
Requires Python: >=3.7
Keywords: forge google-cloud-functions integration

# forgecloud

pip install twine

(delete old dist folder before creating new one, else twine upload will fail)

Create wheel and dist:
python setup.py sdist bdist_wheel

upload with twine
twine upload dist/*

Set your username to __token__
Set your password to the token value:

API TOKEN
TRNGen 0.0.2
Truly Random Number Generator
Requires Python: >=3.7

# TRNGen: Truly Random Number Generator

TRNGen is a Python package that provides a secure and unpredictable random number generator by incorporating external entropy factors such as audio, disk and network I/O readings, events, display, mouse coordinates, and timer. These factors are combined using XOR, hashing algorithms, and linearity deviation to produce truly random values that avoid algorithmic prediction.

# Content:

- [Features](#features)
- [Requirements](#requirements)
- [How to install](#installation)
- [How to use](#how-to-use)

# Features

- **External Factors:** Utilizes various external entropy factors to enable true randomness.
  - `Audio`: Captures audio data.
  - `Disk` I/O Readings: Includes disk I/O readings.
  - `Network` I/O Readings: Incorporates network I/O readings for added entropy.
  - `Display`: Utilizes random display information for increased unpredictability.
  - `Mouse Coordinates`: Captures mouse coordinates.
  - `Timer`: Includes timer values in the randomization process.
- **Secure:** Employs cryptographic techniques on top of above values to ensure unpredictability.
  - `XOR` function
  - `Hashing` algorithms
  - `Linearity Deviation` method
- **Easy Integration:** Simple Python package use for easy integration into your projects.

# Requirements

- ```Python >= 3.7```
  - [Download the installer](https://www.python.org/downloads/), run it and follow the steps.
  - Make sure to check the box that says `Add Python to PATH` during installation.
  - Reboot computer.

# Installation

*You can install TRNGen using `pip`:*

```powershell
pip install TRNGen
```

# How to use
- ### Import
```python
from trngen import TRNGen
```
- ### Create an instance of the TRNGen generator
```python
generator = TRNGen()
```
  - ### Available parameters:
    - Check here on [TRNGen() parameters](parameter.md)

- ### Available functions:

  - ####  `trngen()`
    - Main function that generates and returns the random integer hash value
  - #### `hash(algorithm='sha3_256')`
    - Returns random cryptographic hash
  - #### `percentage(simple=False)`
    - Returns random percentage in decimal form
  - #### `integer(start, end)`
    - Returns random integer in range from start to end
  - #### `float(start, end)`
    - Returns random float in range from start to end
  - #### `alphanumeric(length=any)`
    - Returns random alphanumeric value, default of letters, digits and symbols
  - #### `choice(seq)`
    - Randomly chooses a element from an iterable sequence
  - #### `shuffle(seq, in_place=True)`
    - Randomly shuffles an iterable
  - #### `sample(seq, sample_size)`
    - Randomly samples a specified number of elements from an iterable

## License
This project is licensed under the MIT License - see the LICENSE file for details.

## Support
If you encounter any issues or have questions, feel free to open an issue.
eagleview 1.1
Easy Visualisation of Plots

`ongoing` 

`v1.0` | `v1.1`(current)

`v0.1` | `v0.2`



  <p align="left">
  Colab Preview for Code <br>
  <a href="https://colab.research.google.com/drive/1ZklXjCLbrZIACctPS4EKZ4ZnuqdjonO4?usp=sharing" target="_blank">
    <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab">
  </a>
    
  </p>

Website for eagleview
<br>
[![Package Website](https://img.shields.io/badge/eagleview-Home-blue)](https://hexronus.tech/eagleview/index.html)

# eagleview

A package for greatly increasing the visualisation of datasets, in minimal lines of code.

## Usage
```
It is advised to use `Method 1`, as the github repository is updated from time to time, it may occour that new changes are not still updated.
```
### Method 1
1. Clone the repository:

```bash
!git clone https://github.com/hexronuspi/eagleview
```
2. Upload the folder containing your images. If they are in a zip or any other file, extract them first.

3. Navigate to the cloned repository:

```
%cd eagleview
```

4. Install the package:

```
!pip install .
```

5. Use the package in your Python code:

### Method2

1. using pip install
```bash
!pip install eagleview
```
```python
import eagleview
```

<hr>


### Input:

```python
#v0.x
from eagleview.figshow import ImageMatrix

image_display = ImageMatrix('/content/path_to_folder_containing_images')
```


```python
#v1.x
from eagleview.figshow import ImageMatrix

im = ImageMatrix('/content/path_to_folder_containing_images', '/content/path_to_file_containing_label.csv')
#only .csv extension
```

### Output:
```python
#v1.0
im.rand((a, b)).display_image( # a,b is the size of matrix
    check_col='col_name', # replace 'col_name' with the name of column, which has image name
    display_label=True,  # by default this is False
    display_cols=['col1', 'col2'], # replace '', to the column name which you want to print as label
    display_name=True, # by default this is False
    print_all=False, # by default this is True
    x= , # X-coordinate of label
    y= , # Y-coordinate of label
    fig_size=(m, n) # by default this is set to max(image_size), maximum size of all the images which will be displayed
)

```
```python
#v0.2
(ImageMatrix('/content/path_to_folder_containing_images').rand()).display_image((2,2), print_all=False, display_name=True)
```
```python
# v0.1
(ImageMatrix('/content/path_to_folder_containing_images')).display_image((2,2), print_all=False)
```

## Releases: 
- `v0.1`
  - This will display the images in a grid with 3 columns and 2 rows, without printing the left out images. If you want to print all images, you can call `image_display.display_image((2, 3))` or `image_display.display_image((2, 3), True)`.
  
- `v0.2`
  - This will display the name of the images, as their titles. In v0.1, the images were printed starting from first and consecutive until upper bound is reached, this is an optional and random option is added.
 
- `v1.0`
   - Added capability to display label with a variey of options.
     
- `v1.1`
   - Added capability to change label display and visuals with a variey of options.
bdf2mcpack 0.1.1
Creates a resource pack for Minecraft from a BDF type file
Requires Python: >=3.7
Keywords: minecraft bdf

# BDF2MCPack

BDF2MCPack is a CLI application to convert a BDF type font file to a resource
pack for Minecraft.  
The application requires Python 3.7 or above.

## Installation

### Windows, Linux and MacOS

Use [pip](https://pip.pypa.io/en/stable/installation/) to install the module.
```sh
pip install bdf2mcpack
```

Make sure that the executable file (`bdf2mcpack.exe` or `bdf2mcpack`) is
installed under a directory which is set in the `PATH` environment variable.

## Usage

### Help Message
```
usage: bdf2mcpack [-h] [-o output] [--format FORMAT] [--description DESCRIPTION]
                  [--compresslevel {0,1,2,3,4,5,6,7,8,9}] [--range [RANGE ...]]
                  input

Creates a resource pack for Minecraftfrom a BDF type file.

positional arguments:
  input                 The filename of the BDF file to load

options:
  -h, --help            show this help message and exit
  -o output             The Filename of the resource pack to create (default:
                        pack.zip)
  --format FORMAT, -f FORMAT
                        The value to set as pack.pack_format in pack.mcmeta
                        (default: 18)
  --description DESCRIPTION, -d DESCRIPTION
                        The text to set as pack.description in pack.mcmeta
                        (default: "Generated by bdf2mcpack")
  --compresslevel {0,1,2,3,4,5,6,7,8,9}, -c {0,1,2,3,4,5,6,7,8,9}
                        The compression level used when writing the output file
                        (default: 6)
  --range [RANGE ...], -r [RANGE ...]
                        The Unicode codepoint range to use. Accepts decimal or
                        hexadecimal expressions of codepoints. Case insensitive.
                        e.g. 0-127 U+100000-U+10FFFF
```

### Example

This example downloads [Unifont](https://unifoundry.com/unifont/index.html)
Japanese BDF Version, and creates a resource pack to replace ideographic
Chinese Characters with Japanese Kanji.
```sh
curl -O https://unifoundry.com/pub/unifont/unifont-15.1.04/font-builds/unifont_jp-15.1.04.bdf.gz
gunzip unifont_jp-15.1.04.bdf.gz
bdf2mcpack unifont_jp-15.1.04.bdf -o kanji.zip -r U+4E00-U+9FFF
```

## Used Libraries

* [bdfparser](https://github.com/tomchen/bdfparser)
* [Pillow](https://github.com/python-pillow/Pillow)
* [tqdm](https://github.com/tqdm/tqdm)

## License

This program is distributed under Apache-2.0 license.