landmarks.append(landmark)
_prx_t = time.time() - _start_t
if len(bboxes):
for i, landmark in enumerate(landmarks):
for j, point in enumerate(landmark):
cv.circle(image, tuple(point), 3, (0, 255, 0), -1)
image = vis.plotBBoxes(image, bboxes, len(bboxes) * ['face'], scores)
image = vis.plotInfo(image, 'Raspberry Pi - FPS: {:.3f}'.format(1/_prx_t))
image = cv.cvtColor(np.asarray(image), cv.COLOR_BGR2RGB)
cv.imshow(image_path, image)
key = cv.waitKey(0)
cv.destroyAllWindows()
def main(args):
app(args.image)
if __name__ == '__main__':
LOG.info('Raspberry Pi: Face Detection\n')
args = helper.getArgs()
main(args)
LOG.info('Process done')
if record:
writer.write(frm)
if show:
cv.imshow(video_name, frm)
key = cv.waitKey(1)
if key in [27, ord('q')]:
LOG.info('Interrupted by Users')
break
if record:
writer.release()
cap.release()
cv.destroyAllWindows()
def main(args):
video_link = args.video if args.video else 0
app(video_link, args.name, args.show, args.record, args.flip_hor,
args.flip_ver)
if __name__ == '__main__':
LOG.info('Raspberry Pi: Object Detection')
args = helper.getArgs()
main(args)
LOG.info('Process done')
frm = cv.cvtColor(np.asarray(frm), cv.COLOR_BGR2RGB)
if record:
writer.write(frm)
if show:
cv.imshow(video_name, frm)
key = cv.waitKey(1)
if key in [27, ord('q')]:
LOG.info('Interrupted by Users')
break
if record:
writer.release()
cap.release()
cv.destroyAllWindows()
def main(args):
video_link = args.video if args.video else 0
app(video_link, args.name, args.show, args.record)
if __name__ == '__main__':
LOG.info('Raspberry Pi: Head Pose\n')
args = helper.getArgs()
main(args)
LOG.info('Process done')
face_image2 = image2[y1:y2, x1:x2]
lm2 = landmarker.getLandmark(face_image2)
aligned_face2 = aligner.align(face_image2, lm2)
# ================================================================
emb1 = embedder.getEmb(face_image1)
LOG.info('emb1 shape: {}'.format(emb1.shape))
emb2 = embedder.getEmb(face_image2)
LOG.info('emb2 shape: {}'.format(emb2.shape))
dist = getDistance(emb1, emb2)
LOG.info('distance: {:.4}'.format(dist))
# ================================================================
def main(args):
image1_path = args.image1
image2_path = args.image2
app(image1_path, image2_path)
if __name__ == '__main__':
LOG.info('Raspberry Pi: Face Identification\n')
args = helper.getArgs()
main(args)
LOG.info('Process done')
IDs_lst[i], i)
fw.write(line)
def app(data_path, data_name, verbal=True):
image_fnames, image_shapes, bboxes_lst, IDs_lst = \
processDataFolder(data_path)
train_cnt = int(cfg.TRAIN_RATIO * len(image_fnames))
val_cnt = len(image_fnames) - train_cnt
createLSTFile(image_fnames[:train_cnt], image_shapes[:train_cnt],
bboxes_lst[:train_cnt], IDs_lst[:train_cnt],
'train-' + data_name)
createLSTFile(image_fnames[train_cnt:], image_shapes[train_cnt:],
bboxes_lst[train_cnt:], IDs_lst[train_cnt:],
'val-' + data_name)
def main(args):
app(args.data, args.name, args.verbal)
if __name__ == '__main__':
LOG.info('Task: Generate REC data\n')
args = getArgs()
main(args)
LOG.info('Process done')
_prx_t = time.time() - _start_t
if len(bboxes):
for i, landmark in enumerate(landmarks):
for j, point in enumerate(landmark):
cv.circle(image, tuple(point), 3, (0, 255, 0), -1)
image = vis.plotBBoxes(image, bboxes, len(bboxes) * ['face'], scores)
image = vis.plotInfo(image,
'Raspberry Pi - FPS: {:.3f}'.format(1 / _prx_t))
image = cv.cvtColor(np.asarray(image), cv.COLOR_BGR2RGB)
cv.imshow(image_path, image)
key = cv.waitKey(0)
cv.destroyAllWindows()
def main(args):
app(args.image)
if __name__ == '__main__':
LOG.info('Raspberry Pi: Face Alignment\n')
args = helper.getArgs()
main(args)
LOG.info('Process done')
frm = cv.imread(image_path)
_start_t = time.time()
scores, bboxes = face_detector.getFaces(frm, def_score=0.5)
for i, bbox in enumerate(bboxes):
x1, y1, x2, y2 = bbox
face_img = frm[y1:y2, x1:x2]
emo_idx = emotioner.getEmotion(face_img)
LOG.info('emotion: {}'.format(emo_idx))
_prx_t = time.time() - _start_t
# if len(bboxes):
# frm = vis.plotBBoxes(frm, bboxes, len(bboxes) * ['face'], scores)
# frm = vis.plotInfo(frm, 'Raspberry Pi - FPS: {:.3f}'.format(1/_prx_t))
# frm = cv.cvtColor(np.asarray(frm), cv.COLOR_BGR2RGB)
cv.destroyAllWindows()
def main(args):
app(args.image)
if __name__ == '__main__':
LOG.info('Raspberry Pi: Emotion Recognition\n')
args = helper.getArgs()
main(args)
LOG.info('Process done')