change to cli_proc

1 files changed, 0 insertions, 133 deletions

diff --git a/megapixels/commands/cv/face_vector.py b/megapixels/commands/cv/face_vector.py
deleted file mode 100644
index cb155d08..00000000
--- a/megapixels/commands/cv/face_vector.py
+++ /dev/null
@@ -1,133 +0,0 @@
-"""
-Converts ROIs to face vector
-NB: the VGG Face2 extractor should be used with MTCNN ROIs (not square)
-  the DLIB face extractor should be used with DLIB ROIs (square)
-see https://github.com/ox-vgg/vgg_face2 for TAR@FAR
-"""
-
-import click
-
-from app.settings import types
-from app.utils import click_utils
-from app.settings import app_cfg as cfg
-
-@click.command()
-@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('--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('--size', 'opt_size', 
-  type=(int, int), default=cfg.DEFAULT_SIZE_FACE_DETECT,
-  help='Output image size')
-@click.option('-e', '--extractor', 'opt_extractor',
-  default=click_utils.get_default(types.FaceExtractor.VGG),
-  type=cfg.FaceExtractorVar,
-  help='Type of extractor framework/network to use')
-@click.option('-j', '--jitters', 'opt_jitters', default=cfg.DLIB_FACEREC_JITTERS,
-  help='Number of jitters (only for dlib')
-@click.option('-p', '--padding', 'opt_padding', default=cfg.FACEREC_PADDING,
-  help='Percentage ROI padding')
-@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
-  help='Slice list of files')
-@click.option('-f', '--force', 'opt_force', is_flag=True,
-  help='Force overwrite file')
-@click.option('-g', '--gpu', 'opt_gpu', default=0,
-  help='GPU index')
-@click.pass_context
-def cli(ctx, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, opt_size, 
-  opt_extractor, opt_slice, opt_force, opt_gpu, opt_jitters, opt_padding):
-  """Converts face ROIs to vectors"""
-  
-  import sys
-  import os
-  from os.path import join
-  from pathlib import Path
-  from glob import glob
-  
-  from tqdm import tqdm
-  import numpy as np
-  import dlib  # must keep a local reference for dlib
-  import cv2 as cv
-  import pandas as pd
-
-  from app.models.bbox import BBox
-  from app.models.data_store import DataStore
-  from app.utils import logger_utils, file_utils, im_utils
-  from app.processors import face_extractor
-
-
-  # -------------------------------------------------
-  # init here
-
-  log = logger_utils.Logger.getLogger()
-  # set data_store
-  data_store = DataStore(opt_data_store, opt_dataset)
-
-  # get filepath out
-  fp_out = data_store.metadata(types.Metadata.FACE_VECTOR) if opt_fp_out is None else opt_fp_out
-  if not opt_force and Path(fp_out).exists():
-    log.error('File exists. Use "-f / --force" to overwite')
-    return
-
-  # init face processors
-  if opt_extractor == types.FaceExtractor.DLIB:
-    log.debug('set dlib')
-    extractor = face_extractor.ExtractorDLIB(gpu=opt_gpu, jitters=opt_jitters)
-  elif opt_extractor == types.FaceExtractor.VGG:
-    extractor = face_extractor.ExtractorVGG()
-
-  # load data
-  fp_record = data_store.metadata(types.Metadata.FILE_RECORD)
-  df_record = pd.read_csv(fp_record, dtype=cfg.FILE_RECORD_DTYPES).set_index('index')
-  fp_roi = data_store.metadata(types.Metadata.FACE_ROI)
-  df_roi = pd.read_csv(fp_roi).set_index('index')
-
-  if opt_slice:
-    df_roi = df_roi[opt_slice[0]:opt_slice[1]]
-  
-  # -------------------------------------------------
-  # process images
-
-  df_img_groups = df_roi.groupby('record_index')
-  log.debug('processing {:,} groups'.format(len(df_img_groups)))
-
-  vecs = []
-  for record_index, df_img_group in tqdm(df_img_groups):
-    # make fp
-    ds_record = df_record.iloc[record_index]
-    fp_im = data_store.face(ds_record.subdir, ds_record.fn, ds_record.ext)
-    im = cv.imread(fp_im)
-    im = im_utils.resize(im, width=opt_size[0], height=opt_size[1])
-    for roi_index, df_img in df_img_group.iterrows():
-      # get bbox
-      x, y, w, h = df_img.x, df_img.y, df_img.w, df_img.h
-      dim = (ds_record.width, ds_record.height)
-      # get face vector
-      bbox = BBox.from_xywh(x, y, w, h)  # norm
-      # compute vec
-      vec = extractor.extract(im, bbox)  # use normalized BBox
-      vec_str = extractor.to_str(vec)
-      vec_obj = {'vec':vec_str, 'roi_index': roi_index, 'record_index':record_index}
-      vecs.append(vec_obj)
-
-  # -------------------------------------------------
-  # save data
-
-  # create DataFrame and save to CSV
-  df = pd.DataFrame.from_dict(vecs)
-  df.index.name = 'index'
-  file_utils.mkdirs(fp_out)
-  df.to_csv(fp_out)
-
-  # save script
-  file_utils.write_text(' '.join(sys.argv), '{}.sh'.format(fp_out))
\ No newline at end of file