sudo apt update && sudo apt upgrade
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#!/usr/bin/env python | |
# -*- coding:utf-8 -*- | |
""" | |
Wiener deconvolution study. | |
Copyright (C) 2021 aferro (ORCID: 0000-0003-3830-3595) | |
This program is free software: you can redistribute it and/or modify |
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FROM ubuntu:20.04 | |
RUN apt-get update && \ | |
apt-get install --no-install-recommends -y python3-pip python3.8-dev && \ | |
apt-get install vim && \ | |
apt-get install git |
Setting up a linter
can help detect odd or non-typical coding practices. The following will describe how to setup PyCharm for basic linting with the PyCharm PyLint plugin.
This assumes you have a venv
setup within your current project.
For pylint
for your current project venv
the following two commands should be run in your project root. The first will install pylint
and the second will create an rc
file which you can then adjust for your current project.
Este es un instructivo para un tutorial en Youtube https://youtu.be/pliGG1M87W8
- Descargar https://downloads.raspberrypi.org/raspbian_lite_latest
- Descargar a instalar Etcher (para instalar en la SD) https://etcher.io/
- Instalar imagen en la SD
- Cambiar password de usuario Pi (recomendado)
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from keras.callbacks import Callback | |
import keras.backend as K | |
import numpy as np | |
class SGDRScheduler(Callback): | |
'''Cosine annealing learning rate scheduler with periodic restarts. | |
# Usage | |
```python | |
schedule = SGDRScheduler(min_lr=1e-5, |
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## based on https://github.com/jacobgil/keras-grad-cam | |
## and on https://github.com/vense/keras-grad-cam/blob/master/grad-cam.py | |
import keras | |
from keras.layers import Input | |
from keras.layers import BatchNormalization | |
from keras.layers import Conv2D | |
from keras.layers import Activation | |
from keras.layers import MaxPooling2D | |
from keras.layers import GlobalAveragePooling2D |
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