236 lines
1.6 MiB
Plaintext
236 lines
1.6 MiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"using FileIO\n",
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"using Images, ImageView\n",
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"using Colors\n",
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"using Formatting\n",
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"using FFTW\n",
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"using Plots"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"filterFactory (generic function with 1 method)"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"function idealFilter(r, isLow, threshold)\n",
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" if isLow\n",
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" r .<= threshold\n",
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" else\n",
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" r .> threshold\n",
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" end\n",
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"end\n",
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"\n",
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"function gaussianFilter(r, isLow, threshold)\n",
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" if isLow\n",
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" exp.(-(r.^2) ./ 2*(threshold^2))\n",
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" else\n",
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" 1 .- exp.(-(r.^2) ./ 2*(threshold^2))\n",
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" end\n",
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"end\n",
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"\n",
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"function butterworthFilter(r, isLow, threshold, n)\n",
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" if isLow\n",
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" 1 ./ (1 .+ (r ./ threshold) .^ (2 * n))\n",
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" else\n",
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" 1 ./ (1 .+ (threshold ./ r) .^ (2 * n))\n",
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" end\n",
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"end\n",
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"\n",
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"function laplacianFilter(r, isLow, threshold)\n",
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" -r.^2\n",
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"end\n",
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"\n",
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"function filterFactory(name, shape, isLow, threshold, other)\n",
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" n, m = shape\n",
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" r = sqrt.([i^2 + j^2 for i=-n/2:n/2-1, j=-m/2:m/2-1])\n",
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"\n",
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" if name == \"Ideal\"\n",
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" idealFilter(r, isLow, threshold)\n",
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" elseif name == \"Gaussian\"\n",
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" gaussianFilter(r, isLow, threshold)\n",
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" elseif name == \"Butterworth\"\n",
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" butterworthFilter(r, isLow, threshold, other)\n",
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" elseif name == \"Laplacian\"\n",
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" laplacianFilter(r, isLow, threshold)\n",
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" else\n",
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" error(\"Filter not found\")\n",
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" end\n",
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"end"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"720×1280 Array{Float32,2}:\n",
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" 0.125623 0.133808 0.142699 … 0.105667 0.111525 0.118184 \n",
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" 0.120721 0.127849 0.135616 0.103504 0.108524 0.114269 \n",
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" 0.115489 0.121567 0.12822 0.100998 0.105183 0.110019 \n",
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" 0.110158 0.115214 0.120783 0.0983235 0.101694 0.105643 \n",
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" 0.104962 0.109044 0.113579 0.0956583 0.0982531 0.101358 \n",
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" 0.100126 0.103299 0.10687 … 0.0931787 0.0950526 0.0973715\n",
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" 0.0958562 0.0982011 0.10089 0.0910495 0.0922702 0.0938749\n",
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" 0.092331 0.0939393 0.0958441 0.0894156 0.0900616 0.091035 \n",
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" 0.0896915 0.0906639 0.0918893 0.0883944 0.0885514 0.0889848\n",
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" 0.0880352 0.0884776 0.0891341 0.0880694 0.0878278 0.0878168\n",
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" 0.0874112 0.0874311 0.0876312 … 0.0884856 0.0879368 0.0875786\n",
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" 0.0878176 0.0875212 0.0873754 0.0896464 0.0888801 0.0882699\n",
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" 0.0892011 0.0886895 0.0883038 0.0915127 0.0906137 0.0898423\n",
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" ⋮ ⋱ \n",
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" 0.11068 0.12517 0.141065 0.07604 0.0860907 0.0976428\n",
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" 0.117359 0.132047 0.148102 0.0819347 0.0922755 0.10409 \n",
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" 0.123356 0.138094 0.154157 … 0.0875451 0.0980505 0.109995 \n",
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" 0.128509 0.143149 0.159066 0.0927211 0.103262 0.115199 \n",
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" 0.132679 0.147073 0.16269 0.097326 0.107771 0.119565 \n",
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" 0.135758 0.149761 0.164929 0.101242 0.111463 0.122978 \n",
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" 0.13767 0.151144 0.165722 0.104376 0.114251 0.125358 \n",
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" 0.13838 0.151197 0.165056 … 0.106666 0.116079 0.12666 \n",
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" 0.137893 0.14994 0.162963 0.108082 0.116929 0.126876 \n",
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" 0.136261 0.14744 0.159528 0.10863 0.116822 0.126042 \n",
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" 0.133577 0.143809 0.154883 0.108353 0.115817 0.124233 \n",
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" 0.129974 0.139202 0.149202 0.107329 0.114008 0.121565 "
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"imagePath = \"../images/f124074.jpg\"\n",
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"filterName = \"Ideal\"\n",
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"filterLow = true\n",
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"filterThreshold = 30\n",
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"filterOther = 0\n",
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"\n",
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"img = load(imagePath)\n",
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"img_gray = Float32.(Gray.(img))\n",
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"filter = filterFactory(filterName, size(img_gray), filterLow, filterThreshold, filterOther)\n",
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"img_fft = fftshift(fft(img_gray))\n",
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"out = abs.(real.(ifft(img_fft .* filter)))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"720×1280 Array{RGB{N0f8},2} with eltype RGB{Normed{UInt8,8}}:\n",
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" RGB{N0f8}(0.027,0.125,0.212) … RGB{N0f8}(0.02,0.114,0.224) \n",
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" RGB{N0f8}(0.024,0.129,0.212) RGB{N0f8}(0.02,0.114,0.224) \n",
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" RGB{N0f8}(0.024,0.129,0.212) RGB{N0f8}(0.02,0.114,0.224) \n",
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" RGB{N0f8}(0.024,0.125,0.216) RGB{N0f8}(0.02,0.114,0.224) \n",
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|
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" RGB{N0f8}(0.024,0.125,0.216) RGB{N0f8}(0.02,0.114,0.224) \n",
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" RGB{N0f8}(0.027,0.129,0.22) … RGB{N0f8}(0.02,0.114,0.224) \n",
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|
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" RGB{N0f8}(0.027,0.129,0.22) RGB{N0f8}(0.02,0.114,0.224) \n",
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" RGB{N0f8}(0.027,0.129,0.22) RGB{N0f8}(0.02,0.114,0.224) \n",
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" RGB{N0f8}(0.024,0.129,0.212) RGB{N0f8}(0.031,0.114,0.235)\n",
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" RGB{N0f8}(0.024,0.129,0.212) RGB{N0f8}(0.031,0.114,0.235)\n",
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" RGB{N0f8}(0.024,0.129,0.212) … RGB{N0f8}(0.024,0.114,0.235)\n",
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" RGB{N0f8}(0.024,0.129,0.212) RGB{N0f8}(0.024,0.114,0.235)\n",
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" RGB{N0f8}(0.024,0.125,0.216) RGB{N0f8}(0.02,0.122,0.227) \n",
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" ⋮ ⋱ \n",
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" RGB{N0f8}(0.067,0.063,0.086) RGB{N0f8}(0.016,0.125,0.18) \n",
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" RGB{N0f8}(0.075,0.063,0.098) RGB{N0f8}(0.016,0.129,0.192)\n",
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" RGB{N0f8}(0.071,0.067,0.098) … RGB{N0f8}(0.02,0.133,0.196) \n",
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" RGB{N0f8}(0.059,0.071,0.098) RGB{N0f8}(0.02,0.133,0.196) \n",
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" RGB{N0f8}(0.043,0.063,0.075) RGB{N0f8}(0.02,0.133,0.196) \n",
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" RGB{N0f8}(0.059,0.051,0.106) RGB{N0f8}(0.016,0.129,0.192)\n",
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" RGB{N0f8}(0.063,0.055,0.098) RGB{N0f8}(0.02,0.125,0.192) \n",
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" RGB{N0f8}(0.047,0.067,0.082) … RGB{N0f8}(0.016,0.125,0.18) \n",
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|
|
" RGB{N0f8}(0.043,0.059,0.094) RGB{N0f8}(0.016,0.125,0.18) \n",
|
|||
|
|
" RGB{N0f8}(0.071,0.075,0.094) RGB{N0f8}(0.016,0.125,0.18) \n",
|
|||
|
|
" RGB{N0f8}(0.059,0.063,0.078) RGB{N0f8}(0.016,0.122,0.188)\n",
|
|||
|
|
" RGB{N0f8}(0.067,0.063,0.125) RGB{N0f8}(0.016,0.122,0.188)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"720×1280 Array{Gray{Float32},2} with eltype Gray{Float32}:\n",
|
|||
|
|
" Gray{Float32}(0.125623) … Gray{Float32}(0.118184) \n",
|
|||
|
|
" Gray{Float32}(0.120721) Gray{Float32}(0.114269) \n",
|
|||
|
|
" Gray{Float32}(0.115489) Gray{Float32}(0.110019) \n",
|
|||
|
|
" Gray{Float32}(0.110158) Gray{Float32}(0.105643) \n",
|
|||
|
|
" Gray{Float32}(0.104962) Gray{Float32}(0.101358) \n",
|
|||
|
|
" Gray{Float32}(0.100126) … Gray{Float32}(0.0973715)\n",
|
|||
|
|
" Gray{Float32}(0.0958562) Gray{Float32}(0.0938749)\n",
|
|||
|
|
" Gray{Float32}(0.092331) Gray{Float32}(0.091035) \n",
|
|||
|
|
" Gray{Float32}(0.0896915) Gray{Float32}(0.0889848)\n",
|
|||
|
|
" Gray{Float32}(0.0880352) Gray{Float32}(0.0878168)\n",
|
|||
|
|
" Gray{Float32}(0.0874112) … Gray{Float32}(0.0875786)\n",
|
|||
|
|
" Gray{Float32}(0.0878176) Gray{Float32}(0.0882699)\n",
|
|||
|
|
" Gray{Float32}(0.0892011) Gray{Float32}(0.0898423)\n",
|
|||
|
|
" ⋮ ⋱ \n",
|
|||
|
|
" Gray{Float32}(0.11068) Gray{Float32}(0.0976428)\n",
|
|||
|
|
" Gray{Float32}(0.117359) Gray{Float32}(0.10409) \n",
|
|||
|
|
" Gray{Float32}(0.123356) … Gray{Float32}(0.109995) \n",
|
|||
|
|
" Gray{Float32}(0.128509) Gray{Float32}(0.115199) \n",
|
|||
|
|
" Gray{Float32}(0.132679) Gray{Float32}(0.119565) \n",
|
|||
|
|
" Gray{Float32}(0.135758) Gray{Float32}(0.122978) \n",
|
|||
|
|
" Gray{Float32}(0.13767) Gray{Float32}(0.125358) \n",
|
|||
|
|
" Gray{Float32}(0.13838) … Gray{Float32}(0.12666) \n",
|
|||
|
|
" Gray{Float32}(0.137893) Gray{Float32}(0.126876) \n",
|
|||
|
|
" Gray{Float32}(0.136261) Gray{Float32}(0.126042) \n",
|
|||
|
|
" Gray{Float32}(0.133577) Gray{Float32}(0.124233) \n",
|
|||
|
|
" Gray{Float32}(0.129974) Gray{Float32}(0.121565) "
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"display(img)\n",
|
|||
|
|
"display(Gray.(out))"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"metadata": {
|
|||
|
|
"kernelspec": {
|
|||
|
|
"display_name": "Julia 1.2.0-DEV",
|
|||
|
|
"language": "julia",
|
|||
|
|
"name": "julia-1.2"
|
|||
|
|
},
|
|||
|
|
"language_info": {
|
|||
|
|
"file_extension": ".jl",
|
|||
|
|
"mimetype": "application/julia",
|
|||
|
|
"name": "julia",
|
|||
|
|
"version": "1.2.0"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 2
|
|||
|
|
}
|