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https://github.com/simleek/displayarray

A OpenCV interface to display tensors, multiple cameras, and so on.
https://github.com/simleek/displayarray

display-tensors numpy python pytorch tensorflow video webcam

Last synced: about 2 months ago
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A OpenCV interface to display tensors, multiple cameras, and so on.

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README

        

displayarray
============

A library for displaying arrays as video in Python.

Display arrays while updating them
----------------------------------

.. figure:: https://i.imgur.com/UEt6iR6.gif
:alt:

::

from displayarray import display
import numpy as np

arr = np.random.normal(0.5, 0.1, (100, 100, 3))

with display(arr) as d:
while d:
arr[:] += np.random.normal(0.001, 0.0005, (100, 100, 3))
arr %= 1.0

Run functions on 60fps webcam or video input
--------------------------------------------

|image0|

(Video Source: https://www.youtube.com/watch?v=WgXQ59rg0GM)

::

from displayarray import display
import math as m

def forest_color(arr):
forest_color.i += 1
arr[..., 0] = (m.sin(forest_color.i*(2*m.pi)*4/360)*255 + arr[..., 0]) % 255
arr[..., 1] = (m.sin((forest_color.i * (2 * m.pi) * 5 + 45) / 360) * 255 + arr[..., 1]) % 255
arr[..., 2] = (m.cos(forest_color.i*(2*m.pi)*3/360)*255 + arr[..., 2]) % 255

forest_color.i = 0

display("fractal test.mp4", callbacks=forest_color, blocking=True, fps_limit=120)

Display tensors as they're running through TensorFlow or PyTorch
----------------------------------------------------------------

.. figure:: https://i.imgur.com/TejCpIP.png
:alt:

::

# see test_display_tensorflow in test_simple_apy for full code.

...

autoencoder.compile(loss="mse", optimizer="adam")

while displayer:
grab = tf.convert_to_tensor(
displayer.FRAME_DICT["fractal test.mp4frame"][np.newaxis, ...].astype(np.float32)
/ 255.0
)
grab_noise = tf.convert_to_tensor(
(((displayer.FRAME_DICT["fractal test.mp4frame"][np.newaxis, ...].astype(
np.float32) + np.random.uniform(0, 255, grab.shape)) / 2) % 255)
/ 255.0
)
displayer.update((grab_noise.numpy()[0] * 255.0).astype(np.uint8), "uid for grab noise")
autoencoder.fit(grab_noise, grab, steps_per_epoch=1, epochs=1)
output_image = autoencoder.predict(grab, steps=1)
displayer.update((output_image[0] * 255.0).astype(np.uint8), "uid for autoencoder output")

Handle input events
-------------------

Mouse events captured whenever the mouse moves over the window:

::

event:0
x,y:133,387
flags:0
param:None

Code:

::

from displayarray.input import mouse_loop
from displayarray import display

@mouse_loop
def print_mouse_thread(mouse_event):
print(mouse_event)

display("fractal test.mp4", blocking=True)

Installation
------------

displayarray is distributed on `PyPI `__ as a
universal wheel in Python 3.6+ and PyPy.

::

$ pip install displayarray

Usage
-----

API has been generated `here `_.

See tests and examples for example usage.

License
-------

displayarray is distributed under the terms of both

- `MIT License `__
- `Apache License, Version
2.0 `__

at your option.

.. |image0| image:: https://thumbs.gfycat.com/AbsoluteEarnestEelelephant-size_restricted.gif
:target: https://gfycat.com/absoluteearnesteelelephant