1 files changed, 0 insertions, 100 deletions
diff --git a/megapixels/commands/cv/embeddings.py b/megapixels/commands/cv/embeddings.py
deleted file mode 100644
index 9cb26ae7..00000000
--- a/megapixels/commands/cv/embeddings.py
+++ /dev/null
@@ -1,100 +0,0 @@
-"""
-Crop images to prepare for training
-"""
-
-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('-i', '--input', 'opt_fp_in', required=True,
-  help='Input directory')
-@click.option('-r', '--records', 'opt_fp_records', required=True,
-  help='Input directory')
-@click.option('-m', '--media', 'opt_fp_media', required=True,
-  help='Image directory')
-@click.option('-o', '--output', 'opt_fp_out', required=True,
-  help='Output CSV')
-@click.option('--size', 'opt_size', 
-  type=(int, int), default=(300, 300),
-  help='Output image size')
-@click.option('-g', '--gpu', 'opt_gpu', default=0,
-  help='GPU index')
-@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('-j', '--jitters', 'opt_jitters', default=cfg.DLIB_FACEREC_JITTERS,
-  help='Number of jitters')
-@click.option('-p', '--padding', 'opt_padding', default=cfg.DLIB_FACEREC_PADDING,
-  help='Percentage padding')
-@click.pass_context
-def cli(ctx, opt_fp_in, opt_fp_records, opt_fp_out, opt_fp_media, opt_size, opt_gpu,
-  opt_slice, opt_jitters, opt_padding, opt_force):
-  """Converts frames with faces to CSV of rows"""
-  
-  import sys
-  import os
-  from os.path import join
-  from pathlib import Path
-  
-  from tqdm import tqdm
-  import numpy as np
-  import dlib  # must keep a local reference for dlib
-  import cv2 as cv
-  import dlib
-  import pandas as pd
-
-  from app.utils import logger_utils, file_utils, im_utils
-  from app.models.bbox import BBox
-  from app.processors import face_recognition
-
-  # -------------------------------------------------
-  # init here
-
-  log = logger_utils.Logger.getLogger()
-
-  if not opt_force and Path(opt_fp_out).exists():
-    log.error('File exists. Use "-f / --force" to overwite')
-    return
-  
-  # init dlib FR
-  facerec = face_recognition.RecognitionDLIB()
-
-  # load data
-  df_rois = pd.read_csv(opt_fp_in)
-  df_records = pd.read_csv(opt_fp_records)
-
-  if opt_slice:
-    df_rois = df_rois[opt_slice[0]:opt_slice[1]]
-  log.info('Processing {:,} rows'.format(len(df_rois)))
-  nrows = len(df_rois)
-
-  # face vecs
-  vecs = []
-
-  for roi_idx, row in tqdm(df_rois.iterrows(), total=nrows):
-    # make image path
-    record_id = int(row['id'])
-    df = df_records.iloc[record_id]
-    fp_im = join(opt_fp_media, df['subdir'], '{}.{}'.format(df['fn'], df['ext'])) 
-    # load image
-    im = cv.imread(fp_im)
-    # make bbox
-    xywh = [row['x'], row['y'], row['w'] , row['h']]
-    bbox = BBox.from_xywh(*xywh)
-    # scale to actual image size
-    dim = (row['image_width'], row['image_height'])
-    bbox_dim = bbox.to_dim(dim)
-    # compute vec
-    vec = facerec.vec(im, bbox_dim, jitters=opt_jitters, padding=opt_padding)
-    vec_str = ','.join([repr(x) for x in vec])
-    vecs.append( {'id': row['id'], 'vec': vec_str})
-  
-  # save data
-  file_utils.mkdirs(opt_fp_out)
-  df_vecs = pd.DataFrame.from_dict(vecs)
-  df_vecs.to_csv(opt_fp_out, index=False)
-  log.info('saved {:,} lines to {}'.format(len(df_vecs), opt_fp_out))
-\ No newline at end of file