API tools faq
paste
Advertisement
Guest User

wav-ns.sh

a guest
Aug 7th, 2018
1,114
0
Never
Add comment
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
text 9.22 KB | None | 0 0
raw download clone embed print report
  1. #!/bin/bash
  2. #usage: ./wav-ns.sh "content image" "comma,separated,style,images"
  3. CONTENT_IMAGE=$1
  4. STYLE_IMAGE=$2
  5. content=$(basename ${1%.*})
  6. style=$(basename ${2%.*})
  7. OUT_DIR="out/$content-$style/"
  8. mkdir -p $OUT_DIR
  9.  
  10. SCALE_DOWN=128
  11. SCALE_UP=1448
  12.  
  13. STYLE_WEIGHT=10000
  14. CONTENT_WEIGHT=100
  15.  
  16. WIDTH=`identify $CONTENT_IMAGE | cut -f 3 -d " " | sed s/x.*//`
  17. HEIGHT=`identify $CONTENT_IMAGE | cut -f 3 -d " " | sed s/.*x//`
  18. MIN=$(( WIDTH < HEIGHT ? WIDTH : HEIGHT ))
  19. MAX=$(( WIDTH > HEIGHT ? WIDTH : HEIGHT ))
  20. SCALE=$(( (1000 * 512 / $MIN) * $MIN / 1000))
  21.  
  22. python3 ../Neural-Tools/linear-color-transfer.py \
  23. --target_image $CONTENT_IMAGE \
  24. --source_image ${STYLE_IMAGE##*,} \
  25. --output_image $OUT_DIR/content-hist.png
  26.  
  27. convert $OUT_DIR/content-hist.png -resize ${SCALE}x${SCALE} $OUT_DIR/in.png
  28.  
  29. PREV=$OUT_DIR/in.png
  30.  
  31. th neural_style_multires.lua \
  32. -style_image $STYLE_IMAGE \
  33. -content_image $PREV \
  34. -output_image $OUT_DIR/$content-$style \
  35. -num_iterations 1000 \
  36. -optimizer lbfgs \
  37. -normalize_gradients \
  38. -style_scale 1 \
  39. -content_weight $(( $CONTENT_WEIGHT )) \
  40. -style_weight $(( $STYLE_WEIGHT )) \
  41. -image_size 1024 \
  42. -init image \
  43. -init_image $PREV \
  44. -overlap_times 2 \
  45. -scale_down $( echo $SCALE_DOWN/512 | bc -l ) \
  46. -scale_up $( echo $SCALE_DOWN/512 | bc -l ) \
  47. -scale_steps 1
  48.  
  49. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  50.  
  51. python3 ../Neural-Tools/linear-color-transfer.py \
  52. --target_image $PREV \
  53. --source_image ${STYLE_IMAGE##*,} \
  54. --output_image "${PREV%.*}"-hist.png
  55.  
  56. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  57.  
  58. for ((n=0;n<$(echo "($( echo "l(512) / l(2) - l($SCALE_DOWN) / l(2)" | bc -l ) + 0.5) / 1" | bc);n++)) do
  59. th neural_style_multires.lua \
  60. -style_image $STYLE_IMAGE \
  61. -content_image $PREV \
  62. -output_image $OUT_DIR/$content-$style \
  63. -num_iterations 800 \
  64. -optimizer lbfgs \
  65. -normalize_gradients \
  66. -style_scale 1 \
  67. -content_weight $CONTENT_WEIGHT \
  68. -style_weight $STYLE_WEIGHT \
  69. -image_size 1024 \
  70. -init image \
  71. -init_image $PREV \
  72. -overlap_times 2 \
  73. -scale_down 2 \
  74. -scale_up 2 \
  75. -scale_steps 1
  76.  
  77. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  78.  
  79. python3 ../Neural-Tools/linear-color-transfer.py \
  80. --target_image $PREV \
  81. --source_image ${STYLE_IMAGE##*,} \
  82. --output_image "${PREV%.*}"-hist.png
  83.  
  84. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  85. done
  86.  
  87. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  88.  
  89. python3 ../Neural-Tools/linear-color-transfer.py \
  90. --target_image $PREV \
  91. --source_image ${STYLE_IMAGE##*,} \
  92. --output_image "${PREV%.*}"-hist.png
  93.  
  94. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  95.  
  96. for ((n=-1;n<=$(echo "($( echo "l($SCALE_UP) / l( sqrt(2) ) - l(1024) / l( sqrt(2) )" | bc -l ) + 0.5) / 1" | bc);n++)) do
  97. th neural_style_multires.lua \
  98. -style_image $STYLE_IMAGE \
  99. -content_image $PREV \
  100. -output_image $OUT_DIR/$content-$style \
  101. -num_iterations 600 \
  102. -optimizer lbfgs \
  103. -normalize_gradients \
  104. -style_scale 1 \
  105. -content_weight $CONTENT_WEIGHT \
  106. -style_weight $STYLE_WEIGHT \
  107. -image_size 1024 \
  108. -init image \
  109. -init_image $PREV \
  110. -overlap_times 2 \
  111. -scale_down 1.414 \
  112. -scale_up 1.414 \
  113. -scale_steps 1
  114.  
  115. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  116.  
  117. python3 ../Neural-Tools/linear-color-transfer.py \
  118. --target_image $PREV \
  119. --source_image ${STYLE_IMAGE##*,} \
  120. --output_image "${PREV%.*}"-hist.png
  121.  
  122. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  123. done
  124.  
  125. STYLE_WEIGHT=1000
  126. STYLE_SCALE=1
  127. CONTENT_WEIGHT=0
  128.  
  129. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  130.  
  131. python3 ../Neural-Tools/linear-color-transfer.py \
  132. --target_image $PREV \
  133. --source_image ${STYLE_IMAGE##*,} \
  134. --output_image "${PREV%.*}"-hist.png
  135.  
  136. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  137.  
  138.  
  139. th neural_style.lua \
  140. -style_image $STYLE_IMAGE \
  141. -style_weight $STYLE_WEIGHT \
  142. -style_scale $STYLE_SCALE \
  143. -content_image $CONTENT_IMAGE \
  144. -content_weight $CONTENT_WEIGHT \
  145. -output_image $OUT_DIR/X4.png \
  146. -num_iterations 600 \
  147. -model_file models/channel_pruning.caffemodel \
  148. -proto_file models/channel_pruning.prototxt \
  149. -optimizer adam \
  150. -print_iter 300 \
  151. -tv_weight 0 \
  152. -backend cudnn \
  153. -init image \
  154. -init_image $PREV \
  155. -learning_rate 1 \
  156. -image_size 1600 \
  157. -original_colors 0 \
  158. -normalize_gradients
  159.  
  160.  
  161. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  162.  
  163. python3 ../Neural-Tools/linear-color-transfer.py \
  164. --target_image $PREV \
  165. --source_image ${STYLE_IMAGE##*,} \
  166. --output_image "${PREV%.*}"-hist.png
  167.  
  168. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  169.  
  170.  
  171. th neural_style.lua \
  172. -style_image $STYLE_IMAGE \
  173. -style_weight $STYLE_WEIGHT \
  174. -style_scale $STYLE_SCALE \
  175. -content_image $CONTENT_IMAGE \
  176. -content_weight $CONTENT_WEIGHT \
  177. -output_image $OUT_DIR/X5.png \
  178. -model_file models/nin_imagenet_conv.caffemodel \
  179. -proto_file models/train_val.prototxt \
  180. -num_iterations 200 \
  181. -content_layers relu0,relu1,relu2,relu3,relu5,relu6,relu7,relu8 \
  182. -style_layers relu0,relu1,relu2,relu3,relu5,relu6,relu7,relu8 \
  183. -optimizer adam \
  184. -print_iter 100 \
  185. -tv_weight 0 \
  186. -backend cudnn \
  187. -init image \
  188. -init_image $PREV \
  189. -learning_rate 1 \
  190. -image_size 2550 \
  191. -original_colors 0 \
  192. -normalize_gradients
  193.  
  194.  
  195. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  196.  
  197. python3 ../Neural-Tools/linear-color-transfer.py \
  198. --target_image $PREV \
  199. --source_image ${STYLE_IMAGE##*,} \
  200. --output_image "${PREV%.*}"-hist.png
  201.  
  202. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  203.  
  204. STYLE_WEIGHT=1000
  205. STYLE_SCALE=1
  206. CONTENT_WEIGHT=0
  207.  
  208.  
  209. th neural_style.lua \
  210. -style_image $STYLE_IMAGE \
  211. -style_weight $STYLE_WEIGHT \
  212. -style_scale $STYLE_SCALE \
  213. -content_image $CONTENT_IMAGE \
  214. -content_weight $CONTENT_WEIGHT \
  215. -output_image $OUT_DIR/X6.png \
  216. -model_file models/nin_imagenet_conv.caffemodel \
  217. -proto_file models/train_val.prototxt \
  218. -num_iterations 200 \
  219. -content_layers relu0,relu1,relu2,relu3,relu5,relu6 \
  220. -style_layers relu0,relu1,relu2,relu3,relu5,relu6 \
  221. -optimizer adam \
  222. -print_iter 100 \
  223. -tv_weight 0 \
  224. -backend cudnn \
  225. -init image \
  226. -init_image $PREV \
  227. -learning_rate 1 \
  228. -image_size 2700 \
  229. -original_colors 0 \
  230. -normalize_gradients
  231.  
  232.  
  233. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  234.  
  235. python3 ../Neural-Tools/linear-color-transfer.py \
  236. --target_image $PREV \
  237. --source_image ${STYLE_IMAGE##*,} \
  238. --output_image "${PREV%.*}"-hist.png
  239.  
  240. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  241.  
  242.  
  243. th neural_style.lua \
  244. -style_image $STYLE_IMAGE \
  245. -style_weight $STYLE_WEIGHT \
  246. -style_scale $STYLE_SCALE \
  247. -content_image $CONTENT_IMAGE \
  248. -content_weight $CONTENT_WEIGHT \
  249. -output_image $OUT_DIR/X7.png \
  250. -model_file models/nin_imagenet_conv.caffemodel \
  251. -proto_file models/train_val.prototxt \
  252. -num_iterations 200 \
  253. -content_layers relu0,relu1,relu2,relu3,relu5,relu6,relu7,relu8 \
  254. -style_layers relu0,relu1,relu2,relu3,relu5,relu6,relu7,relu8 \
  255. -optimizer adam \
  256. -print_iter 100 \
  257. -tv_weight 0 \
  258. -backend cudnn \
  259. -init image \
  260. -init_image $PREV \
  261. -learning_rate 1 \
  262. -image_size 2900 \
  263. -original_colors 0 \
  264. -normalize_gradients
  265.  
  266.  
  267. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  268.  
  269. python3 ../Neural-Tools/linear-color-transfer.py \
  270. --target_image $PREV \
  271. --source_image ${STYLE_IMAGE##*,} \
  272. --output_image "${PREV%.*}"-hist.png
  273.  
  274. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  275.  
  276.  
  277. th neural_style.lua \
  278. -style_image $STYLE_IMAGE \
  279. -style_weight $STYLE_WEIGHT \
  280. -style_scale $STYLE_SCALE \
  281. -content_image $CONTENT_IMAGE \
  282. -content_weight $CONTENT_WEIGHT \
  283. -output_image $OUT_DIR/X8.png \
  284. -model_file models/nin_imagenet_conv.caffemodel \
  285. -proto_file models/train_val.prototxt \
  286. -num_iterations 200 \
  287. -content_layers relu0,relu1 \
  288. -style_layers relu0,relu1 \
  289. -optimizer adam \
  290. -print_iter 100 \
  291. -tv_weight 0 \
  292. -backend cudnn \
  293. -init image \
  294. -init_image $PREV \
  295. -learning_rate 1 \
  296. -image_size 4000 \
  297. -original_colors 0 \
  298. -normalize_gradients
  299.  
  300.  
  301. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  302.  
  303. python3 ../Neural-Tools/linear-color-transfer.py \
  304. --target_image $PREV \
  305. --source_image ${STYLE_IMAGE##*,} \
  306. --output_image "${PREV%.*}"-hist.png
  307.  
  308. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  309.  
  310. STYLE_SCALE=0.5
  311.  
  312.  
  313. th neural_style.lua \
  314. -style_image $STYLE_IMAGE \
  315. -content_image $CONTENT_IMAGE \
  316. -output_image $OUT_DIR/$content-$style.png \
  317. -model_file models/nin_imagenet_conv.caffemodel \
  318. -proto_file models/train_val.prototxt \
  319. -num_iterations 20 \
  320. -content_layers relu0,relu1 \
  321. -style_layers relu0,relu1 \
  322. -optimizer adam \
  323. -print_iter 50 \
  324. -tv_weight 0 \
  325. -style_scale $STYLE_SCALE \
  326. -backend cudnn \
  327. -content_weight $CONTENT_WEIGHT \
  328. -style_weight $STYLE_WEIGHT \
  329. -init image \
  330. -init_image $PREV \
  331. -learning_rate 1 \
  332. -image_size 5000 \
  333. -original_colors 0
  334.  
  335.  
  336. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  337.  
  338. python3 ../Neural-Tools/linear-color-transfer.py \
  339. --target_image $PREV \
  340. --source_image ${STYLE_IMAGE##*,} \
  341. --output_image "${PREV%.*}"-hist.png
  342.  
  343. PREV=$OUT_DIR/$(ls -t $OUT_DIR | head -n1)
  344.  
  345.  
  346. python ../Neural-Tools/lum-transfer.py \
  347. --output_lum2 $PREV \
  348. --org_content $OUT_DIR/content-hist.png \
  349. --cp_mode lum2 \
  350. --output_image "${PREV%-hist.*}"-lum1.png
  351.  
  352. python ../Neural-Tools/lum-transfer.py \
  353. --output_lum2 $PREV \
  354. --org_content $CONTENT_IMAGE \
  355. --cp_mode lum2 \
  356. --output_image "${PREV%-hist.*}"-lum2.png
  357.  
  358. python ../Neural-Tools/lum-transfer.py \
  359. --output_lum2 $PREV \
  360. --org_content "$OUT_DIR/$content-$style-1024.png" \
  361. --cp_mode lum2 \
  362. --output_image "${PREV%-hist.*}"-match.png
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement
Public Pastes
Advertisement
We use cookies for various purposes including analytics. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy.  OK, I Understand
Not a member of Pastebin yet?
Sign Up, it unlocks many cool features!