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Black screen while recognizing

See original GitHub issue

I tried to recognise the face using the latest library build. But then , the mobile screen is black fully.

Im getting the following message in logcat.

06-10 16:28:58.578 8532-8542/ch.zhaw.facerecognition W/art: Suspending all threads took: 17.306ms
06-10 16:29:24.238 8532-8542/ch.zhaw.facerecognition W/art: Suspending all threads took: 8.277ms
06-10 16:29:35.658 8532-8548/ch.zhaw.facerecognition W/art: Suspending all threads took: 7.428ms
06-10 16:29:39.818 8532-8542/ch.zhaw.facerecognition W/art: Suspending all threads took: 9.988ms
06-10 16:29:40.508 8532-8548/ch.zhaw.facerecognition W/art: Suspending all threads took: 6.632ms
06-10 16:29:41.828 8532-8542/ch.zhaw.facerecognition W/art: Suspending all threads took: 15.030ms
06-10 16:29:49.358 8532-8542/ch.zhaw.facerecognition W/art: Suspending all threads took: 8.884ms

This occurs in most of my mobiles. May I know how to sort this out?

Issue Analytics

State:
Created 6 years ago
Reactions:1
Comments:23 (8 by maintainers)

Top GitHub Comments

3reactions

sladomiccommented, Jun 18, 2017

hehe…no I’m just applying the algorithms someone else found…the researchers are the brilliant people…for example these https://arxiv.org/pdf/1503.03832.pdf https://arxiv.org/pdf/1704.04861.pdf http://www.vision.caltech.edu/html-files/EE148-2005-Spring/pprs/viola04ijcv.pdf

3reactions

sladomiccommented, Jun 12, 2017

@Zumbalamambo with the facenet model it works 4 times faster for me (the model is also 5-6 times smaller). Also it allows you to include the model as an asset for your app (maximum app size is 100Mb, so this wouldn’t work with the vgg_faces model, which is 553Mb alone).

I used the frozen facenet model, thanks to the user apollo-time, then I just optimized it for inference on Android devices using graph_transforms with these parameters:

bazel build tensorflow/tools/graph_transforms:transform_graph
bazel-bin/tensorflow/tools/graph_transforms/transform_graph \
--in_graph=tmp/facenet.pb \
--out_graph=tmp/optimized_facenet.pb \
--inputs='input' \
--outputs='embeddings' \
--transforms='
  strip_unused_nodes(type=float, shape="1,160,160,3")
  fold_constants(ignore_errors=true)
  fold_batch_norms
  fold_old_batch_norms
  round_weights(num_steps=256)'