1 files changed, 79 insertions, 0 deletions
diff --git a/megapixels/commands/demo/face_vector.py b/megapixels/commands/demo/face_vector.py
new file mode 100644
index 00000000..1104f923
--- /dev/null
+++ b/megapixels/commands/demo/face_vector.py
@@ -0,0 +1,79 @@
+"""
+Crop images to prepare for training
+"""
+
+import click
+# from PIL import Image, ImageOps, ImageFilter, ImageDraw
+
+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', default=None, required=True,
+  help='Image filepath')
+@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('--display/--no-display', 'opt_display', is_flag=True, default=False,
+  help='Display detections to debug')
+@click.pass_context
+def cli(ctx, opt_fp_in, opt_gpu, opt_size, opt_display):
+  """Demo generating face vector"""
+  
+  import sys
+  import os
+  from os.path import join
+  from pathlib import Path
+  import time
+  
+  import numpy as np
+  import cv2 as cv
+  import dlib  # NB: keep a reference in main file if using dlib detector processors
+
+  from app.utils import logger_utils, file_utils, im_utils, display_utils, draw_utils
+  from app.utils import plot_utils
+  from app.processors import face_detector
+  from app.models.data_store import DataStore
+
+  # -------------------------------------------------
+  # init here
+
+  log = logger_utils.Logger.getLogger()
+
+  # ----------------------------------------------------------------------------
+  # load image
+
+  im = cv.imread(opt_fp_in)
+  im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1])
+
+  
+  # ----------------------------------------------------------------------------
+  # detect face
+
+  face_detector = face_detector.DetectorDLIBCNN(gpu=opt_gpu)  # -1 for CPU
+  bboxes = face_detector.detect(im_resized, largest=True)
+  bbox = bboxes[0]
+  dim = im_resized.shape[:2][::-1]
+  bbox_dim = bbox.to_dim(dim)
+  if not bbox:
+    log.error('no face detected')
+    return
+
+
+  # ----------------------------------------------------------------------------
+  # generate face vectors, only to test if feature extraction works
+  
+  from app.processors import face_recognition
+  face_rec = face_recognition.RecognitionDLIB()
+  vec = face_rec.vec(im_resized, bbox_dim)
+  log.info(f'generated vector. showing vec[0:10]:')
+  log.info(f'\n{vec[0:10]}')
+
+  if opt_display:
+    draw_utils.draw_bbox(im_resized, bbox_dim)
+    cv.imshow('Original', im_resized)
+    display_utils.handle_keyboard()
+\ No newline at end of file