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Author SHA1 Message Date
piv
188c55d1c8 Update for python 2.10, add general training algorithm step 2022-05-03 16:56:15 +09:30
Piv
aa423cc38a Start adding unsupervised train loop 2021-11-20 13:37:26 +10:30
Piv
2bb37b2722 Fix up generator to include intrinsics 2021-08-29 19:26:15 +09:30
Piv
90b73bf420 Start adding generators for unsupervised training 2021-08-29 18:06:37 +09:30
Piv
42fcf5554a Update warp test to verify output shape 2021-08-24 21:39:10 +09:30
Piv
c164c9720a Finish Projective Inverse Warp algorithm 2021-08-24 20:13:30 +09:30
Piv
b7917ec465 More warp implementation 2021-08-21 17:32:16 +09:30
Piv
df1ac89a81 Add euler to rotation matrix, grid flattening 2021-08-10 20:39:52 +09:30
Piv
8016f0f945 Add coordinates generation implementation 2021-08-08 22:11:50 +09:30
Piv
ece37843ce Merge branch 'main' into unsupervised 2021-08-08 18:58:39 +09:30
Michael Pivato
a72f04006f Merge branch 'packnet_small' into 'main' 
Add small option to packnet, fix docs and first/final conv layers (prev 32)

See merge request vato007/fast-depth-tf!8
 2021-08-08 09:25:56 +00:00
Michael Pivato
625ecba731 Add small option to packnet, fix docs and first/final conv layers (prev 32) 2021-08-08 09:25:55 +00:00
Michael Pivato
5373dc6b65 Merge branch 'packnet_fixes' into 'main' 
Fix packnet residual block and layers, refactor to support different amount of residual layers

See merge request vato007/fast-depth-tf!7
 2021-08-07 11:31:22 +00:00
Piv
58b8e53986 Fix packnet residual block and layers, refactor to support different amount of residual layers 
I noticed the number of parameters didn't match up to the paper (~128 million)
Fixed this by doing the following:
 - Kernel size of 1 for 3rd conv2d in residual block
 - Use add rather than concat in residual block
 - Fixed add/concat features in decode layers
 - Fixed final layers -> this also allows features_3d == 16 to work
 2021-08-07 21:00:17 +09:30
Piv
cd278e683f Start adding pose warp conversions 2021-08-07 17:18:06 +09:30
Michael Pivato
f56e663fca Merge branch 'unsupervised' into 'main' 
Smooth Loss

See merge request vato007/fast-depth-tf!6
 2021-08-05 08:20:31 +00:00
Michael Pivato
26dda68523 Add Smooth Loss 2021-08-05 08:20:31 +00:00
Piv
5996d6eaf0 Merge branch 'main' into unsupervised 2021-08-05 17:49:48 +09:30
Piv
8be4ce4e6d Add smooth loss 2021-08-05 17:48:44 +09:30
Michael Pivato
e96e6c2c2b Merge branch 'unsupervised' into 'main' 
PoseNet

See merge request vato007/fast-depth-tf!5
 2021-08-04 11:36:30 +00:00
Michael Pivato
5d0731b60f PoseNet 
Adds the nns required for unsupervised learning
 - PoseNet (based on ResNet18 like Monodepth)
 - Wrapper for fast depth to pull out intermediary layers to smooth out gradients during training
 2021-08-04 11:36:30 +00:00
Piv
b95442bb23 Finish off pose net 2021-08-04 20:51:46 +09:30
Piv
a111f89722 Start adding pose decoder 2021-08-03 20:25:19 +09:30
Piv
2372b906df Add resnet18 2021-08-01 10:44:33 +09:30
Michael Pivato
d3a63c6bcd Merge branch 'unsupervised' into 'main' 
Packnet

See merge request vato007/fast-depth-tf!4
 2021-07-31 01:31:25 +00:00
Piv
6514fb0e86 Add sample openvino inference 2021-07-29 20:52:14 +09:30
Piv
3254eef4bf Add compiling packnet model, refactor modules to not duplicate loaders and trainers 2021-07-23 22:41:46 +09:30
Piv
66cbc7faf6 Add pack layer tests, fix unpack_3d layer 2021-07-19 20:37:54 +09:30
Piv
38e7ad069e Refactor load/util, start fixing packnet to support NHWC format 2021-07-19 12:32:56 +09:30
Piv
d8bf493999 More packnet implementation 2021-07-18 19:54:28 +09:30
Piv
603de2bc9f Start adding packnet model 2021-07-18 18:59:25 +09:30
Piv
e372fe33ba Add per-pixel loss functions 2021-07-13 20:32:45 +09:30
Piv
b9457f17fe Add pixel loss functions, move warp 2021-07-13 19:20:24 +09:30
Piv
6f7da21977 Add spatial transformer network sampler 2021-07-12 18:19:59 +09:30
Piv
f501beb6f2 Start implementing unsupervised train loop, add sfmlearner train and utils files for reference 2021-07-05 20:50:12 +09:30
Piv
ba0ba609a3 Add utils from sfm learner, start adding sfm learner loss function to work with keras 2021-06-22 22:03:23 +09:30
Piv
101fe08924 Start adding stubs for unsupervised training 2021-06-16 21:55:13 +09:30
Piv
e5b07fb766 Fix loss function 2021-06-16 21:52:31 +09:30
Michael Pivato
0547509689 Merge branch 'kitti_depth_dataset' into 'main' 
Kitti depth dataset

See merge request vato007/fast-depth-tf!2
 2021-04-22 12:13:48 +00:00
Michael Pivato
070aec6eed Add Kitti depth dataset 
Warning: Using this requires >175gb of disk space (tensorflow will also generate examples that will take up space)
 2021-04-22 12:13:48 +00:00
Piv
02d8cd5810 Remove half-features from dense_depth 2021-04-22 12:30:30 +09:30
Piv
acdb58396c Remove usage of keras 2021-04-14 12:45:01 +09:30
Piv
cf7d2561ec Implement details of dense depth paper 2021-04-14 12:38:51 +09:30
Piv
f598005b73 Add basic coreml and mlkit conversion scripts 2021-03-29 19:08:55 +10:30
Piv
f3fc0f8fbb Add coreml conversion 2021-03-29 18:58:16 +10:30
Michael Pivato
f2a42cca4c Merge branch 'dense-depth' into 'main' 
Dense depth

See merge request vato007/fast-depth-tf!1
 2021-03-29 07:31:42 +00:00
Piv
d88e9d3f12 Add dense-depth and experimental dense-net-nnconv5 models 
Since dense-depth will use half labels by default, the nyu train/eval datasets can be loaded from here at half resolutions for labels
 2021-03-29 17:59:18 +10:30
Piv
870429c3ef Refactor fast-depth 
Addresses the following:
 - Rename nnconv5 block to nnconv5
 - Add skip connections directly to nnconv5 block
 - Allow custom metrics, loss and optimizer (keep defaults that reflect original paper) to train
 - Correctly use nyu evaluation dataset only when no dataset is provided
 2021-03-29 17:57:12 +10:30
Piv
3325ea0c0c Format pep8, include pass shaped to mobilenet 2021-03-25 21:56:50 +10:30
Piv
9449ddef01 Add notebook, gitignore 2021-03-25 21:50:19 +10:30