Esempio n. 1
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def check_transform(img_path, out_path):
    imgset = imgs.make_imgs(img_path, norm=False, transform=imgs.to_3D)
    dirs.make_dir(out_path)
    for i, img_i in enumerate(imgset):
        raw_i = img_i[0]  # imgs.unify_img(img_i)
        print(raw_i.shape)
        name_i = "img" + str(i) + ".jpg"
        new_img_i = imgs.Image(name_i, raw_i)
        new_img_i.save(out_path)
Esempio n. 2
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def reconstruction(ae_path, img_path, out_path):
    reader = deep.reader.NNReader()
    nn = reader.read(ae_path)  # autoconv.read_conv_ae(ae_path)
    imgset = imgs.make_imgs(img_path, norm=True)
    recon = [nn.reconstructed(img_i) for img_i in imgset]
    recon = imgs.unorm(recon)
    dirs.make_dir(out_path)
    for i, img_i in enumerate(recon):
        img_i.save(out_path, i)
Esempio n. 3
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def agum_data(action_path, out_path):
    old_actions = actions.read_actions(action_path)
    new_actions = [flip_action(action_i) for action_i in old_actions]
    all_actions = old_actions + new_actions
    dirs.make_dir(out_path)
    for action_i in all_actions:
        path_i = utils.paths.Path(out_path)
        path_i.add(action_i.cat)
        dirs.make_dir(path_i)
        action_i.save(str(path_i))
Esempio n. 4
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def select_frames(action_path,out_path,action_dict):
    print(action_dict.name)
    action_path=action_path.create(action_dict.name)
    out_path=out_path.create(action_dict.name)
    for in_path_i,cat_i in action_dict.categorize(action_path):
        #dst_path=out_path.create(action_dict.name)
        dirs.make_dir(out_path)
        dst_path_i=out_path.replace(in_path_i)
        print(str(in_path_i))
        print(str(dst_path_i))
        copyfile(str(in_path_i), str(dst_path_i))
Esempio n. 5
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def save_actions(actions,outpath):
    dirs.make_dir(outpath)
    print(dir(utils.data))
    extr_cats=utils.data.ExtractCat(parse_cat=lambda a:a.cat)
    for action_i in actions:
        extr_cats(action_i)
    for name_i in extr_cats.names():
        cat_dir_i=outpath.append(name_i,copy=True)
        dirs.make_dir(cat_dir_i)
    for action_i in actions:
        cat_path_i=outpath.append(action_i.cat,copy=True)
        action_i.save(cat_path_i)
Esempio n. 6
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def seg_action(action_path,out_path,action_dict):
    action_path=action_path.create(action_dict.name)
    out_path=out_path.create(action_dict.name)
    print(str(action_path))
    print(str(out_path))
    cats=action_dict.categorize(action_path)
    cat_dict={}
    for cat_i in action_dict.data.keys():
        cat_path=out_path.copy()
        cat_path.set_name(cat_i)
        dirs.make_dir(cat_path)
        cat_dict[cat_i]=cat_path 
    for frame_path,cat_i in cats:
        dst_path=cat_dict[cat_i]
        dst_path=dst_path.create(action_dict.name)
        dirs.make_dir(dst_path)
        dst_path=dst_path.replace(frame_path)
        print(frame_path)
        print(dst_path)
        copyfile(str(frame_path), str(dst_path))
Esempio n. 7
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import os

from utils.load_conf import parse_args, parse_conf
from utils.dirs import make_dir, clear_dirs
from run_main import run_timit

if __name__ == '__main__':
  # Locate the root directory of the project
  root = os.environ['VOICE_VAE']

  # parse command line arguments
  args = parse_args()

  if args is None:
      exit()

  # parse configuration file arguments
  config = parse_conf(root, args)

  # Setup the output directories of the program
  if config['clear']:
    clear_dirs()
  for n in ['results_path', 'results_dir', 'models_path', 'models_dir', 'tensorboard_dir', 'train_tb_dir', 'test_tb_dir']:
    d = config[n]
    make_dir(d)

  # main
  run_timit(config)
Esempio n. 8
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def extract_features(in_path,ext_path,seq_path='seq',short_names=True):
    out_path=in_path.copy().set_name(str(seq_path))
    dirs.make_dir(str(out_path))
    extractor=ext.read_external(str(ext_path),short_names)
    transform_seq(in_path,out_path,extractor)
Esempio n. 9
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 def save(self,outpath):
     full_outpath=outpath.append(self.name,copy=True)
     dirs.make_dir(full_outpath)
     [img_i.save(full_outpath) 
      for img_i in self.img_seq]
Esempio n. 10
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def extract(action_path,out_path,cat_path):
    dirs.make_dir(out_path)
    actions=parse_info(cat_path)
    print(str(actions[0]))   
    [select_frames(action_path,out_path,act_i) for act_i in actions]