Merge branch 'master' of asdf.us:megapixels_dev

2 files changed, 62 insertions, 234 deletions

diff --git a/megapixels/commands/datasets/file_record.py b/megapixels/commands/datasets/file_record.py
deleted file mode 100644
index 41a5df28..00000000
--- a/megapixels/commands/datasets/file_record.py
+++ /dev/null
@@ -1,234 +0,0 @@
-'''
-
-'''
-import click
-
-from app.settings import types
-from app.utils import click_utils
-from app.settings import app_cfg as cfg
-from app.utils.logger_utils import Logger
-
-log = Logger.getLogger()
-
-# Choose part of the filepath that will be used for the person identity
-# eg subdirectory "lfw/media/original/batch_1/train/barack_obama/001.jpg" --> [subdir_tail] --> "barack_obama"
-# eg subdirectory "lfw/media/original/batch_1/train/barack_obama/001.jpg" --> [subdir_head] --> "batch_1"
-# eg subdirectory "lfw/media/original/batch_1/train/barack_obama/001.jpg" --> [subdir] --> "barack_obama"
-
-identity_sources = ['subdir', 'numeric']
-
-@click.command()
-@click.option('-i', '--input', 'opt_fp_in', default=None,
-  help='Override enum input filename CSV')
-@click.option('-o', '--output', 'opt_fp_out', default=None,
-  help='Override enum output filename CSV')
-@click.option('-m', '--media', 'opt_dir_media', default=None,
-  help='Override enum media directory')
-@click.option('--data_store', 'opt_data_store',
-  type=cfg.DataStoreVar,
-  default=click_utils.get_default(types.DataStore.HDD),
-  show_default=True,
-  help=click_utils.show_help(types.Dataset))
-@click.option('--dataset', 'opt_dataset',
-  type=cfg.DatasetVar,
-  required=True,
-  show_default=True,
-  help=click_utils.show_help(types.Dataset))
-@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
-  help='Slice list of files')
-@click.option('-t', '--threads', 'opt_threads', default=12,
-  help='Number of threads')
-@click.option('-f', '--force', 'opt_force', is_flag=True,
-  help='Force overwrite file')
-@click.option('--identity', 'opt_identity', type=click.Choice(identity_sources),
-  required=True,
-  help='Identity source key')
-@click.option('--recursive/--no-recursive', 'opt_recursive', is_flag=True, default=False,
-  help='Use glob recursion (slower)')
-@click.option('--max-depth', 'opt_max_depth', default=None, type=int,
-  help='Max number of images per subdirectory')
-@click.pass_context
-def cli(ctx, opt_fp_in, opt_fp_out, opt_dataset, opt_data_store, opt_dir_media, opt_slice, opt_threads,
-  opt_identity, opt_force, opt_recursive, opt_max_depth):
-  """Generates sha256, uuid, and identity index CSV file"""
-  
-  import sys, os
-  from glob import glob
-  from os.path import join
-  from pathlib import Path
-  import time
-  from multiprocessing.dummy import Pool as ThreadPool 
-  import random
-  import uuid
-
-  from PIL import Image
-  import cv2 as cv
-  import pandas as pd
-  from tqdm import tqdm
-  from glob import glob
-  from operator import itemgetter
-
-  from app.models.data_store import DataStore
-  from app.utils import file_utils, im_utils
-
-
-  # set data_store
-  data_store = DataStore(opt_data_store, opt_dataset)
-  # get filepath out
-  fp_out = data_store.metadata(types.Metadata.FILE_RECORD) if opt_fp_out is None else opt_fp_out
-  # exit if exists
-  if not opt_force and Path(fp_out).exists():
-    log.error('File exists. Use "-f / --force" to overwite')
-    return
-  
-  # ----------------------------------------------------------------
-  # glob files
-
-  fp_in = opt_fp_in if opt_fp_in is not None else data_store.media_images_original()
-  log.info(f'Globbing {fp_in}')
-  fp_ims = file_utils.glob_multi(fp_in, ['jpg', 'png'], recursive=opt_recursive)
-
-  log.info('Found {:,} images'.format(len(fp_ims)))
-  subdir_groups = {}
-  if opt_max_depth:
-    log.debug(f'using max depth: {opt_max_depth}')
-    for fp_im in fp_ims:
-      fpp_im = Path(fp_im)
-
-      subdir = fp_im.split('/')[-2]
-      if not subdir in subdir_groups.keys():
-        subdir_groups[subdir] = []
-      else:
-        subdir_groups[subdir].append(fp_im)
-    # for each subgroup, limit number of files
-    fp_ims = []
-    for subdir_name, items in subdir_groups.items():
-      ims = items[0:opt_max_depth]
-      fp_ims += ims
-
-  log.debug(f'num subdirs: {len(subdir_groups.keys())}')
-  # fail if none
-  if not fp_ims:
-    log.error('No images. Try with "--recursive"')
-    return
-  # slice to reduce
-  if opt_slice:
-    fp_ims = fp_ims[opt_slice[0]:opt_slice[1]]
-  log.info('Found {:,} images'.format(len(fp_ims)))
-
-  # ----------------------------------------------------------------
-  # multithread process into SHA256
-
-  pbar = tqdm(total=len(fp_ims))
-
-  def pool_mapper(fp_im):
-    pbar.update(1)
-    try:
-      sha256 = file_utils.sha256(fp_im)
-      im = Image.open(fp_im)
-      im.verify()  # throws error if bad file
-      assert(im.size[0] > 60 and im.size[1] > 60)
-    except Exception as e:
-      log.warn(f'skipping file: {fp_im}')
-      return None
-    im = cv.imread(fp_im)
-    w, h = im.shape[:2][::-1]
-    file_size_kb = os.stat(fp_im).st_size // 1000
-    num_channels = im_utils.num_channels(im)
-    return {
-      'width': w, 
-      'height': h, 
-      'sha256': sha256,
-      'file_size_kb': file_size_kb, 
-      'num_channels': num_channels
-      }
-
-  # convert to thread pool
-  pool_maps = []  # ?
-  pool = ThreadPool(opt_threads) 
-  with tqdm(total=len(fp_ims)) as pbar:
-    pool_maps = pool.map(pool_mapper, fp_ims)
-  pbar.close()
-
-
-  # ----------------------------------------------------------------
-  # convert data to dict
-  
-  data = []
-  indentity_count = 0
-  for pool_map, fp_im in zip(pool_maps, fp_ims):
-    if pool_map is None:
-      log.warn(f'skipping file: {fp_im}')
-      continue  # skip error files
-    fpp_im = Path(fp_im)
-    subdir = str(fpp_im.parent.relative_to(fp_in))
-    
-    if opt_identity:
-      subdirs = subdir.split('/')
-      if not len(subdirs) > 0:
-        log.error(f'Could not split subdir: "{subdir}. Try different option for "--identity"')
-        log.error('exiting')
-        return
-      if opt_identity == 'subdir':
-        identity = subdirs[-1]  # use last part of subdir path
-      elif opt_identity == 'numeric':
-        identity = indentity_count  # use incrementing number
-        indentity_count += 1
-    else:
-      identity = ''
-
-    data.append({
-      'subdir': subdir,
-      'num_channels': pool_map['num_channels'],
-      'fn': fpp_im.stem,
-      'ext': fpp_im.suffix.replace('.',''),
-      'sha256': pool_map['sha256'],
-      'uuid': uuid.uuid4(),
-      'identity_key': identity,
-      'width': pool_map['width'],
-      'height': pool_map['height']
-      })
-
-  # create dataframe
-  df_records = pd.DataFrame.from_dict(data)
-
-  df_records.index.name = 'index'  # reassign 'index' as primary key column
-  # write to CSV
-  file_utils.mkdirs(fp_out)
-  df_records.to_csv(fp_out)
-  # done
-  log.info(f'wrote {len(df_records)} rows to "{fp_out}"')
-  # save script
-  cmd_line = ' '.join(sys.argv)
-  file_utils.write_text(cmd_line, '{}.sh'.format(fp_out))
-
-
-'''
-# create dataframe
-  df_records = pd.DataFrame.from_dict(data)
-
-  # add identity key (used for associating identity)
-  if opt_identity:
-    log.info(f'adding identity index using: "{opt_identity}" subdirectory')
-    # convert dict to DataFrame
-    # sort based on identity_key
-    df_records = df_records.sort_values(by=['identity_key'], ascending=True)
-    # add new column for identity
-    df_records['identity_index'] = [-1] * len(df_records)
-    # populate the identity_index
-    df_records_identity_groups = df_records.groupby('identity_key')
-    # enumerate groups to create identity indices
-    log.info(f'updating records with identity_key. This may take a while...')
-    st = time.time()
-    for identity_index, df_records_identity_group_tuple in enumerate(df_records_identity_groups):
-      identity_key, df_records_identity_group = df_records_identity_group_tuple
-      for ds_record in df_records_identity_group.itertuples():
-        df_records.at[ds_record.Index, 'identity_index'] = identity_index
-    # reset index after being sorted
-    df_records = df_records.reset_index(drop=True)
-    log.debug('update time: {:.2f}s'.format(time.time() - st))
-  else:
-    # name everyone person 1, 2, 3...
-    df_records = df_records.sort_values(by=['subdir'], ascending=True)
-    pass
-'''
\ No newline at end of file
diff --git a/megapixels/commands/datasets/megaface_age_from_orig.py b/megapixels/commands/datasets/megaface_age_from_orig.py
new file mode 100644
index 00000000..489bebf3
--- /dev/null
+++ b/megapixels/commands/datasets/megaface_age_from_orig.py
@@ -0,0 +1,62 @@
+import click
+
+@click.command()
+@click.option('-i', '--input', 'opt_fp_in', required=True,
+  help='Input path to metadata directory')
+@click.option('-o', '--output', 'opt_fp_out',
+  help='Output path to age CSV')
+@click.pass_context
+def cli(ctx, opt_fp_in, opt_fp_out):
+  """Creates CSV of MegaFace ages from original BBoxes"""
+  
+  import os
+  from os.path import join
+  from pathlib import Path
+  from glob import glob
+
+  import dlib
+  import pandas as pd
+  from tqdm import tqdm
+
+  from app.settings import types
+  from app.utils import click_utils
+  from app.settings import app_cfg
+
+  from PIL import Image, ImageOps, ImageFilter
+  from app.utils import file_utils, im_utils, logger_utils
+
+  log = logger_utils.Logger.getLogger()
+
+  # -------------------------------------------------
+  # process  
+  fp_im_dirs = glob(join(opt_fp_in, '**/'), recursive=True)
+  
+  log.info('Found {} directories'.format(len(fp_im_dirs)))
+
+  identities = {}
+
+  for fp_im_dir in tqdm(fp_im_dirs):
+    # 1234567@N05_identity_1
+    try:
+      dir_id_name = Path(fp_im_dir).name
+      nsid = dir_id_name.split('_')[0]
+      identity_num = dir_id_name.split('_')[2]
+      id_key = '{}_{}'.format(nsid, identity_num)
+      num_images = len(glob(join(fp_im_dir, '*.jpg')))
+      if not id_key in identities.keys():
+        identities[id_key] = {'nsid': nsid, 'identity': identity_num, 'images': num_images}
+      else:
+        identities[id_key]['images'] += num_images
+    except Exception as e:
+      continue  
+
+  # convert to dict 
+  identities_list = [v for k, v in identities.items()]
+  df = pd.DataFrame.from_dict(identities_list)
+
+  file_utils.mkdirs(opt_fp_out)
+
+  log.info('Wrote {} lines to {}'.format(len(df), opt_fp_out))
+  df.to_csv(opt_fp_out, index=False)
+
+