Merge branch 'master' of github.com:adamhrv/megapixels_dev

1 files changed, 60 insertions, 0 deletions

diff --git a/megapixels/commands/datasets/imdb_face_download.py b/megapixels/commands/datasets/imdb_face_download.py
new file mode 100644
index 00000000..4180fac0
--- /dev/null
+++ b/megapixels/commands/datasets/imdb_face_download.py
@@ -0,0 +1,60 @@
+import click
+
+fp_in = '/data_store/datasets/people/imdb_face/downloads/IMDb-Face.csv'
+fp_out = '/data_store_hdd/datasets/people/imdb_face/media/'
+
+@click.command()
+@click.option('-i', '--input', 'opt_fp_in', required=True, default=fp_in,
+  help='Input')
+@click.option('-o', '--output', 'opt_fp_out', required=True, default=fp_out,
+  help='Output')
+@click.option('-t', '--threads', 'opt_threads', default=8,
+  help='Number of threads')
+@click.pass_context
+def cli(ctx, opt_fp_in, opt_fp_out, opt_threads):
+  """Download IMDb-Face URLs"""
+  
+  from os.path import join
+  from functools import partial
+  from multiprocessing.dummy import Pool as ThreadPool
+  import urllib
+
+  import pandas as pd
+  from tqdm import tqdm
+  from app.utils import file_utils
+  from app.utils.logger_utils import Logger
+
+  log = Logger.getLogger()
+
+  # setup multithreading function
+  def pool_process(item):
+    # threaded function
+    try:
+      # download image
+      file_utils.mkdirs(item['fp'])
+      urllib.request.urlretrieve(item['url'], item['fp'], timeout=20)
+      item['status'] = True
+    except Exception as e:
+      log.debug(f'Error: {e}')
+      item['status'] = False
+    pbar.update(1)
+    return item
+
+  # setup multithreading data holds
+  log.debug(f'loading {opt_fp_in}')
+  records = pd.read_csv(opt_fp_in).to_dict('records')
+  pool_items = [{'url':x['url'], 'fp': join(opt_fp_out, x['index'], x['image'])} for x in records]
+  num_items = len(pool_items)
+  log.info(f'processing {num_items:,} items')
+  pool_results = []
+
+  # run the multithreading with progress bar
+  pbar = tqdm(total=num_items)
+  pool_process = partial(pool_process)
+  pool = ThreadPool(opt_threads) 
+  with tqdm(total=num_items) as pbar:
+    pool_results = pool.map(pool_process, pool_items)
+  
+  pbar.close()
+
+