DQN TipZ

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Atari Game DQN

https://github.com/kuz/DeepMind-Atari-Deep-Q-Learner.git

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  1. 제갈식2017년 8월 10일 AM 12:20

    한글 사이트:
    http://solarisailab.com/?p=222&ckattempt=1

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  2. 제갈식2017년 8월 10일 AM 12:20

    Storing a .gif for a trained network

    Once you have a snapshot of a network you can run

    ./test_gpu
    to make it play one game and store the .gif under gifs. For example

    ./test_gpu breakout DQN3_0_1_breakout_FULL_Y.t7

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  3. 제갈식2017년 8월 10일 AM 12:21

    추가 롬 다운받는곳

    https://github.com/kristjankorjus/Replicating-DeepMind

    .bin 으로 끝나는 롬만 돌아

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  4. 제갈식2017년 8월 10일 AM 12:21

    post install !

    $ luarocks install cwrap
    $ luarocks install torch
    $ luarocks install optim
    $ luarocks install nn
    $ luarocks install image
    $ luarocks install cutorch
    $ luarocks install cunn
    $ luarocks install cudnn

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파이썬으로 Homomorphic Filtering 하기

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import cv2 # For OpenCV modules (For Image I/O and Contour Finding) import numpy as np # For general purpose array manipulation import scipy . fftpack # For FFT2 #### imclearborder definition def imclearborder ( imgBW , radius ): # Given a black and white image, first find all of its contours imgBWcopy = imgBW . copy () contours , hierarchy = cv2 . findContours ( imgBWcopy . copy (), cv2 . RETR_LIST , cv2 . CHAIN_APPROX_SIMPLE ) # Get dimensions of image imgRows = imgBW . shape [ 0 ] imgCols = imgBW . shape [ 1 ] contourList = [] # ID list of contours that touch the border # For each contour... for idx in np . arange ( len ( contours )): # Get the i'th contour cnt = contours [ idx ] # Look at each point in the contour for pt in cnt : rowCnt = pt [ 0 ][ 1 ] colCnt = pt [ 0 ][ 0 ] # If this is within the radius of th...
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파이썬으로 2D FFT/iFFT 하기: numpy 버전

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import cv2 import numpy as np from matplotlib import pyplot as plt img = cv2 . imread ( 'messi5.jpg' , 0 ) f = np . fft . fft2 ( img ) fshift = np . fft . fftshift ( f ) magnitude_spectrum = 20 * np . log ( np . abs ( fshift )) plt . subplot ( 121 ), plt . imshow ( img , cmap = 'gray' ) plt . title ( 'Input Image' ), plt . xticks ([]), plt . yticks ([]) plt . subplot ( 122 ), plt . imshow ( magnitude_spectrum , cmap = 'gray' ) plt . title ( 'Magnitude Spectrum' ), plt . xticks ([]), plt . yticks ([]) plt . show () rows , cols = img . shape crow , ccol = rows / 2 , cols / 2 fshift [ crow - 30 : crow + 30 , ccol - 30 : ccol + 30 ] = 0 f_ishift = np . fft . ifftshift ( fshift ) img_back = np . fft . ifft2 ( f_ishift ) img_back = np . abs ( img_back ) plt . subplot ( 131 ), plt . imshow ( img , cmap = 'gray' ) plt . title ( 'Input Image' ), plt . xticks ([]), ...
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