simleek
100 lines
2.8 KiB
Markdown
100 lines
2.8 KiB
Markdown
# displayarray
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## Display arrays while updating them
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from displayarray import display
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import numpy as np
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arr = np.random.normal(0.5, 0.1, (100, 100, 3))
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with display(arr) as d:
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while d:
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arr[:] += np.random.normal(0.001, 0.0005, (100, 100, 3))
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arr %= 1.0
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## Run functions on 60fps webcam or video input
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[](https://gfycat.com/absoluteearnesteelelephant)
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from displayarray import display
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import math as m
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def forest_color(arr):
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forest_color.i += 1
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arr[..., 0] = (m.sin(forest_color.i*(2*m.pi)*4/360)*255 + arr[..., 0]) % 255
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arr[..., 1] = (m.sin((forest_color.i * (2 * m.pi) * 5 + 45) / 360) * 255 + arr[..., 1]) % 255
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arr[..., 2] = (m.cos(forest_color.i*(2*m.pi)*3/360)*255 + arr[..., 2]) % 255
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forest_color.i = 0
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display("fractal test.mp4", callbacks=forest_color, blocking=True, fps_limit=120)
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## Display tensors as they're running through TensorFlow or PyTorch
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# see test_display_tensorflow in test_simple_apy for full code.
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...
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autoencoder.compile(loss="mse", optimizer="adam")
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while displayer:
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grab = tf.convert_to_tensor(
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displayer.FRAME_DICT["fractal test.mp4frame"][np.newaxis, ...].astype(np.float32)
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/ 255.0
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)
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grab_noise = tf.convert_to_tensor(
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(((displayer.FRAME_DICT["fractal test.mp4frame"][np.newaxis, ...].astype(
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np.float32) + np.random.uniform(0, 255, grab.shape)) / 2) % 255)
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/ 255.0
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)
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displayer.update((grab_noise.numpy()[0] * 255.0).astype(np.uint8), "uid for grab noise")
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autoencoder.fit(grab_noise, grab, steps_per_epoch=1, epochs=1)
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output_image = autoencoder.predict(grab, steps=1)
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displayer.update((output_image[0] * 255.0).astype(np.uint8), "uid for autoencoder output")
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## Handle input events
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Mouse events captured whenever the mouse moves over the window:
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event:0
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x,y:133,387
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flags:0
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param:None
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Code:
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from displayarray.input import mouse_loop
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from displayarray import display
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@mouse_loop
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def print_mouse_thread(mouse_event):
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print(mouse_event)
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display("fractal test.mp4", blocking=True)
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## Installation
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displayarray is distributed on [PyPI] (https://pypi.org) as a universal
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wheel in Python 3.6+ and PyPy.
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$ pip install displayarray
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## Usage
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See tests for more example code. API will be generated soon.
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## License
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displayarray is distributed under the terms of both
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- [MIT License](https://choosealicense.com/licenses/mit)
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- [Apache License, Version 2.0](https://choosealicense.com/licenses/apache-2.0)
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at your option.
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