Metadata-Version: 2.1
Name: cv2-tools
Version: 2.0.0
Summary: Library to help the drawing process with OpenCV. Thought to add labels to the images. Classification of images, etc.
Home-page: https://github.com/fernaper/opencv-draw-tools
Author: Fernando Pérez
Author-email: fernaperg@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: python-constraint

# cv2_tools
Library to help the drawing process with OpenCV. Thought to add labels to the images. Classification of images, etc.

![image](https://user-images.githubusercontent.com/18369529/53686731-3dba0500-3d2b-11e9-95e5-e4517c013d14.png)

**Image generated with Intel Openvino Toolkit and drawed with opencv-draw-tools v0.1.9**

## Installation

### Pre-requisites

You will need to install:

* opencv >= 3.6.2
* numpy >= 1.13.3
* python-constraint >= 1.4.0

You can simply execute:
`pip install -r requirements.txt`

Finally you can install the library with:

`pip install opencv-draw-tools-fernaperg`

When you install `opencv-draw-tools`, it will automatically download `numpy` but not opencv becouse in some cases you will need another version.

## Test

```
import cv2_tools

print('Name: {}\nVersion:{}\nHelp:{}'.format(cv2_tools.name,cv2_tools.__version__,cv2_tools.help))
webcam_test()
```

## Ussage and Important classes

### ManagerCV2

```
from cv2_tools.Management import ManagerCV2
```

If you want to work with video or stream, this class will help you mantain your code cleaner while you get more features.

For example:
 - Open a a stream (your webcam).
 - Reproduce it on real time with max FPS equals to 24.
 - Press `esc` to finish the program.
 - At the end print average FPS.

```
from cv2_tools.Managment import ManagerCV2
import cv2

# keystroke=27 is the button `esc`
manager_cv2 = ManagerCV2(cv2.VideoCapture(0), is_stream=True, keystroke=27, wait_key=1, fps_limit=60)

  # This for will manage file descriptor for you
  for frame in manager_cv2:
      cv2.imshow('Example easy manager', frame)
  cv2.destroyAllWindows()
  print(manager_cv2.get_fps())
```

If you want to use another button and you don't know the ID, you can check easily using the following code:

```
from cv2_tools.Managment import ManagerCV2
import cv2

# keystroke=27 is the button `esc`
manager_cv2 = ManagerCV2(cv2.VideoCapture(0), is_stream=True, keystroke=27, wait_key=1, fps_limit=60)

  # This for will manage file descriptor for you
  for frame in manager_cv2:
      # Each time you press a button, you will get its id in your terminal
      last_keystroke = manager_cv2.get_last_keystroke()
      if last_keystroke != -1:
        print(last_keystroke)
      cv2.imshow('Easy button checker', frame)
  cv2.destroyAllWindows()
```

### SelectorCV2

Firstly create a SelectorCV2 object. You can pass it optional parameters to configure the output.
```
from cv2_tools.Selection import SelectorCV2
selector = SelectorCV2(color=(200,90,0), filled=True)
```

Also you can configure it later using the method (all optional parameters):
```
selector.set_properties()
```

Now, each time you want to add a selected zone call the method:
```
"""
Coordinates:

(x1,y1)____(x2,y1)
   |          |
   |          |
(x1,y2)____(x2,y2)

Tags (optional parameter):
* It could be a normal string
* A string with '\n'
* A list of strings
* None / '' / [] / False
"""
selector.add_zone((x1,y1,x2,y2),tags=tag)
```

Finally, when you want to draw all the rectangles execute:
```
edited_frame = selector.draw(frame)
```

If you want to use the same object multiple times you can easily change the content inside it:
```
# This method could help change rectangles to
selector.set_range_valid_rectangles( origin, destination)

# This method could help if you know exactly the indexes that you want to keep
# Default = [], so if you just want to clean the buffer call this method without parameters
set_valid_rectangles(indexes)
```

If you want, you can see the example [detect_faces.py](examples/detect_faces.py), it also use an open source library called `face_recognition`.


