p2p tasks

1 files changed, 89 insertions, 38 deletions

diff --git a/app/relay/modules/pix2pix.js b/app/relay/modules/pix2pix.js
index 3727964..d7b9478 100644
--- a/app/relay/modules/pix2pix.js
+++ b/app/relay/modules/pix2pix.js
@@ -3,69 +3,120 @@ import path from 'path'
 const name = 'pix2pix'
 const cwd = process.env.PIX2PIX_CWD || path.join(process.env.HOME, 'code/' + name + '/')
 
-const dataset = {
+/*
+  what are all the tasks that pix2pix has to do?
+    - fetch url
+    - fetch youtube
+  - ffmpeg movie into frames
+  - unzip zip file into sequence
+    - list sequences
+  - 
+*/
+
+const fetch = {
+  type: 'perl',
+  script: 'get.pl',
+  params: (task) => {
+    console.log(task)
+    return [ task.opt.url ]
+  },
+  listen: (task, line, i) => {
+    // here i need to bridge again... get the filename that comes back from youtube-dl
+    // and tell the cortex that URL -> fn and add the filename!
+    if ( line.match(/^youtube-dl got fn, /) ) {
+      let filename = line.split(' => ')[1].trim()
+      task.dataset = filename.split('.')[0]
+      task.opt.filename = filename
+      return { type: 'progress', action: 'resolve_dataset', task, }
+    }
+    return null
+  }
+}
+
+const combine_folds = {
   type: 'pytorch',
   script: 'datasets/combine_A_and_B.py',
   params: (task) => {
+    return [
+      '--fold_A', task.module + '/a_b/' + task.dataset + '/A',
+      '--fold_B', task.module + '/a_b/' + task.dataset + '/B',
+      '--fold_AB', task.module + '/datasets/' + task.dataset,
+    ]
   }
-// python datasets/combine_A_and_B.py \
-//   --fold_A /home/lens/Desktop/thumbs/woodscaled_4/A \
-//   --fold_B /home/lens/Desktop/thumbs/woodscaled_4/B \
-//   --fold_AB datasets/woodscaled_4/
 }
 const train = {
   type: 'pytorch',
   script: 'train.py',
   params: (task) => {
+    return [
+      '--dataroot', './datasets/' + task.dataset,
+      '--name', task.dataset,
+      '--model', 'pix2pix',
+      '--loadSize', opt.load_size || 264,
+      '--fineSize', 256,
+      '--which_model_netG', 'unet_256',
+      '--which_direction', 'AtoB',
+      '--lambda_B', 100,
+      '--dataset_mode', 'aligned',
+      '--epoch_count', task.epochs,
+      '--which_epoch', 'latest',
+      '--continue_train',
+      '--no_lsgan',
+      '--norm', 'batch',
+      '--pool_size', '0',
+    ]
   },
-// python train.py \
-//    --dataroot "./datasets/$dataset" \
-//    --name "$dataset" \
-//    --model pix2pix  \
-//    --loadSize 264 \
-//    --fineSize 256 \
-//    --which_model_netG unet_256  \
-//    --which_direction AtoB  \
-//    --lambda_B 100  \
-//    --dataset_mode aligned  \
-//    --epoch_count $epochs \
-//    --which_epoch latest \
-//    --continue_train \
-//    --no_lsgan --norm batch --pool_size 0
 }
 const generate = {
   type: 'pytorch',
-  script: 'generate.py',
+  script: 'test.py',
   params: (task) => {
+    return [
+      '--dataroot'
+      '--name', task.dataset,
+      '--start_img', task.module + '/sequences/' + task.dataset,
+      '--how_many', 1000,
+      '--model', 'test',
+      '--aspect_ratio', 1.777777,
+      '--which_model_netG', 'unet_256',
+      '--which_direction', 'AtoB',
+      '--dataset_mode', 'test',
+      '--loadSize', 256,
+      '--fineSize', 256,
+      '--norm', 'batch'
+    ]
   },
 }
 const live = {
   type: 'pytorch',
   script: 'live-mogrify.py',
   params: (task) => {
+    return [
+      '--dataroot', task.module + '/sequences/' + task.dataset,
+      '--start_img', task.module + '/sequences/' + task.dataset + '/frame_00001.png',
+      '--experiment', task.checkpoint,
+      '--name', task.checkpoint,
+      '--recursive', '--recursive-frac', 0.1,
+      '--sequence', '--sequence-frac', 0.3,
+      '--process-frac', 0.5,
+      '--transition',
+      '--transition-min', 0.05,
+      '--how_many', 1000000, '--transition-period', 1000,
+      '--loadSize', 256, '--fineSize', 256,
+      '--just-copy', '--poll_delay', 0.09,
+      '--model', 'test',
+      '--which_model_netG', 'unet_256',
+      '--which_direction', 'AtoB',
+      '--dataset_mode', 'recursive',
+      '--which_epoch', 'latest',
+      '--norm', 'batch',
+    ]
   },
-  // python live-mogrify.py \
-  //   --dataroot "./sequences/$sequence" \
-  //   --start_img "./sequences/$sequence/frame_00001.png" \
-  //   --experiment "$checkpoint" \
-  //   --name "$checkpoint" \
-  //   --recursive --recursive-frac 0.1 \
-  //   --sequence --sequence-frac 0.3 \
-  //   --process-frac 0.5 \
-  //   --transition \
-  //   --transition-min 0.05 \
-  //   --how_many 100000 --transition-period 1000 \
-  //   --loadSize 256 --fineSize 256 \
-  //   --just-copy --poll_delay 0.09 \
-  //   --model test --which_model_netG unet_256  \
-  //   --which_direction AtoB --dataset_mode recursive  \
-  //   --which_epoch latest \
-  //   --norm batch
 }
 
 export default {
   name, cwd,
   activities: {
-    dataset, train, generate, live,
+    combine_folds, train, generate, live,
   }
 }