Skip to main content

Tool for displaying numpy arrays.

Project description

A library for displaying arrays as video in Python.

Display arrays while updating them

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

# 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

at your option.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

displayarray-1.3.0.tar.gz (22.3 kB view hashes)

Uploaded source

Built Distribution

displayarray-1.3.0-py3-none-any.whl (29.3 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page