A library for displaying arrays as video in Python.
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
(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)
# 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")
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)
displayarray is distributed on PyPI as a universal wheel in Python 3.6+ and PyPy.
$ pip install displayarray
API has been generated here.
See tests and examples for example usage.
displayarray is distributed under the terms of both
at your option.