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KnowYourPlates-0.1.1
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مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
Module that allows to recognize license plates from images basing on image processing algorithms.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | KnowYourPlates-0.1.1 |
| نام | KnowYourPlates |
| نسخه کتابخانه | 0.1.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Wojciech Sikora |
| ایمیل نویسنده | kontakt@sikorawojciech.pl |
| آدرس صفحه اصلی | https://github.com/SikoraWojciech/KnowYourPlates |
| آدرس اینترنتی | https://pypi.org/project/KnowYourPlates/ |
| مجوز | - |
# KnowYourPlates
Module that allows to recognize license plates from images basing on image processing algorithms.
## Getting started
### Requirements
Module uses several python packages:
* OpenCV - open source computer vision and machine learning software library
* pytesseract - optical character recognition (OCR) tool for python
* NumPy - fundamental package for scientific computing with Python
* imutils - series of convenience functions to make basic image processing functions
* Pillow - Python Image Library
* Matplotlib - Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms
Be sure to have them installed before using **know_your_plates** package:
```
pip install opencv-contrib-python
pip install pytesseract
pip install numpy
pip install imutils
pip install Pillow
pip install matplotlib
```
### Installation
Install this package with python package installer **pip**:
```
pip install know_your_plates
```
### Usage
To recognize license plate from the image, import this package to the project and use **license_plate_recognition** function with path to the image as an argument. Example code:
```python
# run.py
import argparse
from know_your_plates import alpr
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
help="Path to the image")
args = vars(ap.parse_args())
recognized_text = alpr.license_plate_recognition(args['image'])
print(recognized_text)
```
Call from the command line:
```
python run.py --image ./example.jpg
```
## API
- **license_plate_recognition(img_path: str, new_size: tuple, blurring_method: Callable, binarization_method: Callable)):**
```
Automatic license plate recognition algorithm.
Found license plate is stored in ./results/ directiory as license_plate.jpg
Parameters
----------
img_path : str
Path to the image
new_size : tuple of integers
First argument of the tuple is new width, second is the new height of the image
blurring_method : function
Function as an object. Suggested functions from this module: gaussian_blur, median_blur, bilateral_filter
binarization_method : function
Function as an object. Suggested functions from this module: threshold_otsu, adaptive_threshold, canny, auto_canny
Returns
-------
str
Text recognized on the image
```
---
*Blurring and filtering*
- **gaussian_blur(image: np.ndarray):**
```
Wrapper for OpenCV's Gaussian blur. Image is blurred with (3, 3) kernel.
Parameters
----------
image: numpy.ndarray
Image as numpy array. Should be converted into grayscale.
Returns
-------
numpy.ndarray
Blurred image using Gaussian blur
Contribute
----------
Source: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=gaussianblur#gaussianblur
```
- **median_blur(image: np.ndarray):**
```
Wrapper for OpenCV's median blur. Aperture linear size for medianBlur is 3.
Parameters
----------
image: numpy.ndarray
Image as numpy array. Should be converted into grayscale.
Returns
-------
numpy.ndarray
Blurred image using median blur
Contribute
----------
Source: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=medianblur#medianblur
```
- **bilateral_filter(image: np.ndarray):**
```
Wrapper for OpenCV's bilateral filter. Diameter of each pixel neighborhood is 11.
Both filter sigma in the color space and filter sigma in the coordinate space are 17.
Parameters
----------
image: numpy.ndarray
Image as numpy array. Should be converted into grayscale.
Returns
-------
numpy.ndarray
Blurred image using bilateral filter
Contribute
----------
Source: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html?highlight=bilateralfilter#bilateralfilter
```
---
*Tresholding images*
- **canny(image: np.ndarray, threshold1: int, threshold2: int):**
```
Wrapper for OpenCV's Canny algorithm.
Parameters
----------
image : numpy.ndarray
Image as numpy array
threshold1 : int
Lower value of the threshold
threshold2 : int
Upper value of the threshold
Returns
-------
numpy.ndarray
Binarized image using Canny's algorithm.
Contribute
----------
Source: https://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.html
```
- **auto_canny(image: np.ndarray, sigma: float = 0.33):**
```
Function automatically sets up lower and upper value of the threshold
based on sigma and median of the image
Parameters
----------
image : numpy.ndarray
Image as numpy array
sigma : float
Returns
-------
numpy.ndarray
Binarized image with Canny's algorithm
Contribute
----------
Source: https://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.html
```
- **threshold_otsu(image: np.ndarray):**
```
Wrapper for OpenCV's Otsu's threshold algorithm.
Parameters
----------
image : numpy.ndarray
Image as numpy array
Returns
-------
numpy.ndarray
Binarized image using Otsu's algorithm.
Contribute
----------
Source: https://docs.opencv.org/master/d7/d4d/tutorial_py_thresholding.html
```
- **adaptive_threshold(image: np.ndarray):**
```
Wrapper for OpenCV's adaptive threshold algorithm.
Parameters
----------
image : numpy.ndarray
Image as numpy array
Returns
-------
numpy.ndarray
Binarized image using adaptive threshold.
Contribute
----------
Source: https://docs.opencv.org/master/d7/d4d/tutorial_py_thresholding.html
```
---
*OCR functions*
- **ocr(img_path: str):**
```
Wrapper for Tesseract image_to_string function
Parameters
----------
img_path : str
Path to the image
Returns
-------
str
Text recognized on the image
Contribute
----------
PyTesseract: https://pypi.org/project/pytesseract/
```
---
*Image processing*
- **preprocess(image: np.ndarray, new_size: tuple, blurring_method: Callable, binarization_method: Callable):**
```
Resizing, converting into grayscale, blurring and binarizing
Parameters
----------
image : numpy.ndarray
Image as numpy array
new_size : tuple of integers
First argument of the tuple is new width, second is the new height of the image
blurring_method : function
Function as an object. Suggested functions from this module: gaussian_blur, median_blur, bilateral_filter
binarization_method : function
Function as an object. Suggested functions from this module: threshold_otsu, adaptive_threshold, canny, auto_canny
Returns
-------
numpy.ndarray
Preprocessed image.
Contribute
----------
Grayscale conversion: https://docs.opencv.org/2.4/modules/imgproc/doc/miscellaneous_transformations.html
Bilateral filter: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html
```
- **plate_contours(image: np.ndarray):**
```
Finding contours on the binarized image.
Returns only 10 (or less) the biggest rectangle contours found on the image.
Parameters
----------
image : numpy.ndarray
Binarized image as numpy array
Returns
-------
list of numpy.ndarray
List of found OpenCV's contours.
Contribute
----------
Finding contours: https://docs.opencv.org/2.4/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html?highlight=findcontours#findcontours
```
- **crop_image(original_img: np.ndarray, plate_cnt: np.ndarray):**
```
Wrapper for Tesseract image_to_string function
Parameters
----------
img_path : str
Path to the image
Returns
-------
str
Text recognized on the image
Contribute
----------
PyTesseract: https://pypi.org/project/pytesseract/
```
- **prepare_ocr(image: np.ndarray):**
```
Prepares image to the OCR process by resizing and filtering (for noise reduction)
Parameters
----------
image : numpy.ndarray
Image as numpy array
Returns
-------
numpy.ndarray
Image prepaired to the OCR process
Contribute
----------
Resizing: https://docs.opencv.org/2.4/modules/imgproc/doc/geometric_transformations.html#void%20resize(InputArray%20src,%20OutputArray%20dst,%20Size%20dsize,%20double%20fx,%20double%20fy,%20int%20interpolation)
Bilateral filter: https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html
```
## License
**know_your_plates** is released under the [MIT License](https://opensource.org/licenses/MIT).
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl KnowYourPlates-0.1.1:
pip install KnowYourPlates-0.1.1.whl
نصب پکیج tar.gz KnowYourPlates-0.1.1:
pip install KnowYourPlates-0.1.1.tar.gz