Jiading Fang commited on
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fc16538
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1 Parent(s): a916a0c

add define

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  1. .gitattributes +2 -0
  2. .gitignore +8 -0
  3. .gitmodules +3 -0
  4. LICENSE.md +409 -0
  5. Makefile +56 -0
  6. configs/overfit/ddad_tiny.yaml +31 -0
  7. configs/overfit/generic.yaml +27 -0
  8. configs/overfit/kitti_tiny.yaml +31 -0
  9. configs/papers/define/scannet_temporal_test.yaml +79 -0
  10. configs/papers/define/scannet_temporal_test_context_1.yaml +79 -0
  11. configs/papers/depthformer/inference_kitti.yaml +31 -0
  12. configs/papers/fsm/inference_ddad.yaml +19 -0
  13. configs/papers/packnet/inference_packnet.yaml +20 -0
  14. configs/papers/packnet/inference_resnet.yaml +20 -0
  15. configs/papers/selfcalib/ds_euroc.yaml +40 -0
  16. configs/papers/selfcalib/eucm_euroc.yaml +40 -0
  17. configs/papers/selfcalib/ucm_euroc.yaml +40 -0
  18. configs/papers/selfcalib/ucm_kitti.yaml +44 -0
  19. configs/recipes/checkpoint.yaml +8 -0
  20. configs/recipes/datasets/ddad.yaml +32 -0
  21. configs/recipes/datasets/ddad_tiny.yaml +32 -0
  22. configs/recipes/datasets/euroc.yaml +30 -0
  23. configs/recipes/datasets/generic.yaml +30 -0
  24. configs/recipes/datasets/kitti.yaml +31 -0
  25. configs/recipes/datasets/kitti_tiny.yaml +32 -0
  26. configs/recipes/datasets/vkitti2.yaml +16 -0
  27. configs/recipes/evaluation/depth.yaml +21 -0
  28. configs/recipes/losses/reprojection.yaml +9 -0
  29. configs/recipes/losses/smoothness.yaml +5 -0
  30. configs/recipes/losses/supervised_depth.yaml +40 -0
  31. configs/recipes/networks/conv_pose_net.yaml +5 -0
  32. configs/recipes/networks/focal_depth_res_net.yaml +12 -0
  33. configs/recipes/networks/mono_depth_res_net.yaml +10 -0
  34. configs/recipes/networks/multi_depth_res_net.yaml +17 -0
  35. configs/recipes/networks/packnet.yaml +10 -0
  36. configs/recipes/networks/pose_net.yaml +5 -0
  37. configs/recipes/networks/transformer.yaml +12 -0
  38. configs/recipes/optimizers.yaml +7 -0
  39. configs/recipes/save.yaml +5 -0
  40. configs/recipes/wandb.yaml +5 -0
  41. configs/recipes/wrapper.yaml +10 -0
  42. data/generic/scene1/15616458296936490.jpg +0 -0
  43. data/generic/scene1/15616458297936490.jpg +0 -0
  44. data/generic/scene1/15616458298936492.jpg +0 -0
  45. data/generic/scene1/15616458299936482.jpg +0 -0
  46. data/generic/scene1/15616458300936480.jpg +0 -0
  47. data/masks/ddad/01.png +3 -0
  48. data/masks/ddad/05.png +3 -0
  49. data/masks/ddad/06.png +3 -0
  50. data/masks/ddad/07.png +3 -0
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  *.zst filter=lfs diff=lfs merge=lfs -text
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+ **/*.gif filter=lfs diff=lfs merge=lfs -text
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+ **/*.png filter=lfs diff=lfs merge=lfs -text
.gitignore ADDED
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+ *.pyc
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+ .idea
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+ *ZZZ*
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+ sandbox
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+ __pycache__
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+ wandb
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+ temp
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+ code
.gitmodules ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ [submodule "externals/camviz"]
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+ path = externals/camviz
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+ url = [email protected]:TRI-ML/camviz.git
LICENSE.md ADDED
@@ -0,0 +1,409 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Makefile ADDED
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+ PROJECT ?= vidar
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+ WORKSPACE ?= /workspace/$(PROJECT)
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+ DOCKER_IMAGE ?= ${PROJECT}:latest
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+
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+ SHMSIZE ?= 444G
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+ WANDB_MODE ?= run
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+ DOCKER_OPTS := \
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+ --name ${PROJECT} \
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+ --rm -it \
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+ --shm-size=${SHMSIZE} \
11
+ -e AWS_DEFAULT_REGION \
12
+ -e AWS_ACCESS_KEY_ID \
13
+ -e AWS_SECRET_ACCESS_KEY \
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+ -e WANDB_API_KEY \
15
+ -e WANDB_ENTITY \
16
+ -e WANDB_MODE \
17
+ -e HOST_HOSTNAME= \
18
+ -e OMP_NUM_THREADS=1 -e KMP_AFFINITY="granularity=fine,compact,1,0" \
19
+ -e OMPI_ALLOW_RUN_AS_ROOT=1 \
20
+ -e OMPI_ALLOW_RUN_AS_ROOT_CONFIRM=1 \
21
+ -e NCCL_DEBUG=VERSION \
22
+ -e DISPLAY=${DISPLAY} \
23
+ -e XAUTHORITY \
24
+ -e NVIDIA_DRIVER_CAPABILITIES=all \
25
+ -v ~/.aws:/root/.aws \
26
+ -v /root/.ssh:/root/.ssh \
27
+ -v ~/.cache:/root/.cache \
28
+ -v /dev/null:/dev/raw1394 \
29
+ -v /mnt/fsx/tmp:/tmp \
30
+ -v /tmp/.X11-unix/X0:/tmp/.X11-unix/X0 \
31
+ -v /var/run/docker.sock:/var/run/docker.sock \
32
+ -v /home/jiadingfang/datasets:/data \
33
+ -v ${PWD}:${WORKSPACE} \
34
+ -w ${WORKSPACE} \
35
+ --privileged \
36
+ --ipc=host \
37
+ --network=host
38
+
39
+ NGPUS=$(shell nvidia-smi -L | wc -l)
40
+
41
+ all: clean
42
+
43
+ clean:
44
+ find . -name "*.pyc" | xargs rm -f && \
45
+ find . -name "__pycache__" | xargs rm -rf
46
+
47
+ docker-build:
48
+ docker build \
49
+ -f docker/Dockerfile \
50
+ -t ${DOCKER_IMAGE} .
51
+
52
+ docker-interactive: docker-build
53
+ nvidia-docker run ${DOCKER_OPTS} ${DOCKER_IMAGE} bash
54
+
55
+ docker-run: docker-build
56
+ nvidia-docker run ${DOCKER_OPTS} ${DOCKER_IMAGE} bash -c "${COMMAND}"
configs/overfit/ddad_tiny.yaml ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ max_epochs: 1
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ networks:
8
+ depth:
9
+ recipe: networks/mono_depth_res_net|default
10
+ depth_range: [0.1,100.0]
11
+ pose:
12
+ recipe: networks/pose_net|default
13
+ losses:
14
+ reprojection:
15
+ recipe: losses/reprojection|default
16
+ smoothness:
17
+ recipe: losses/smoothness|default
18
+ evaluation:
19
+ depth:
20
+ recipe: evaluation/depth|ddad_resize
21
+ optimizers:
22
+ depth:
23
+ recipe: optimizers|adam_20_05
24
+ pose:
25
+ recipe: optimizers|adam_20_05
26
+ datasets:
27
+ train:
28
+ recipe: datasets/ddad_tiny|train_selfsup_front
29
+ validation:
30
+ recipe: datasets/ddad_tiny|validation_front
31
+
configs/overfit/generic.yaml ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ max_epochs: 1
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ networks:
8
+ depth:
9
+ recipe: networks/mono_depth_res_net|default
10
+ depth_range: [0.1,100.0]
11
+ pose:
12
+ recipe: networks/pose_net|default
13
+ losses:
14
+ reprojection:
15
+ recipe: losses/reprojection|default
16
+ smoothness:
17
+ recipe: losses/smoothness|default
18
+ optimizers:
19
+ depth:
20
+ recipe: optimizers|adam_20_05
21
+ pose:
22
+ recipe: optimizers|adam_20_05
23
+ datasets:
24
+ train:
25
+ recipe: datasets/generic|default_train
26
+ validation:
27
+ recipe: datasets/generic|default_validation
configs/overfit/kitti_tiny.yaml ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ max_epochs: 1
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ networks:
8
+ depth:
9
+ recipe: networks/mono_depth_res_net|default
10
+ depth_range: [0.1,100.0]
11
+ pose:
12
+ recipe: networks/pose_net|default
13
+ losses:
14
+ reprojection:
15
+ recipe: losses/reprojection|default
16
+ smoothness:
17
+ recipe: losses/smoothness|default
18
+ evaluation:
19
+ depth:
20
+ recipe: evaluation/depth|kitti_resize
21
+ optimizers:
22
+ depth:
23
+ recipe: optimizers|adam_20_05
24
+ pose:
25
+ recipe: optimizers|adam_20_05
26
+ datasets:
27
+ train:
28
+ recipe: datasets/kitti_tiny|train_selfsup_mr
29
+ validation:
30
+ recipe: datasets/kitti_tiny|validation_mr
31
+
configs/papers/define/scannet_temporal_test.yaml ADDED
@@ -0,0 +1,79 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ seed: 42
3
+ min_epochs: 0
4
+ max_epochs: 0
5
+ find_unused_parameters: True
6
+ flip_lr_prob: 0.5
7
+ validate_first: True
8
+ validate_flipped: False
9
+ sync_batch_norm: True
10
+ evaluation:
11
+ rgb:
12
+ only_first: False
13
+ depth:
14
+ crop: ''
15
+ min_depth: 0.2
16
+ max_depth: 10.0
17
+ scale_output: resize
18
+ median_scaling: True
19
+ post_process: False
20
+ arch:
21
+ model:
22
+ checkpoint: /data/vidar/models/scannet_full.ckpt
23
+ file: perceiver/DefineGenericModel
24
+ use_pose_noise: []
25
+ use_virtual_cameras: []
26
+ virtual_cameras_eval: False
27
+ use_virtual_rgb: False
28
+ augment_canonical: False
29
+ encode_train: all
30
+ encode_eval: all
31
+ decode_train: all
32
+ decode_eval: all
33
+ decode_encodes: False
34
+ task_weights: [1.0,1.0]
35
+ scale_loss: True
36
+ sample_decoded_queries: 0.0
37
+ network:
38
+ tasks: [depth]
39
+ depth_range: [0.1,10.]
40
+ image_shape: [128,192]
41
+ num_bands_orig: 20
42
+ num_bands_dirs: 10
43
+ max_resolution_orig: 60
44
+ max_resolution_dirs: 60
45
+ to_world: True
46
+ d_latents: 512
47
+ num_latents: 1024
48
+ hidden_dropout_prob: 0.25
49
+ num_cross_attention_heads: 1
50
+ num_self_attends_per_block: 8
51
+ num_self_attention_heads: 8
52
+ decoder_num_heads: 1
53
+ rgb_feat_dim: 960
54
+ rgb_feat_type: resnet_all
55
+ downsample_encoder: 4
56
+ downsample_decoder: 4
57
+ upsample_convex: 'convex'
58
+ encoder_with_rgb: True
59
+ decoder_with_rgb: False
60
+ output_mode: inv_depth
61
+ sample_encoding_rays: 0
62
+ with_monodepth: False
63
+ datasets:
64
+ validation:
65
+ name: [ScanNetTemporal]
66
+ path: [/data/vidar/scannet_processed]
67
+ split: [test]
68
+ context: [-2,2]
69
+ stride: [10]
70
+ labels: [depth,pose]
71
+ cameras: [[0]]
72
+ dataloader:
73
+ batch_size: 1
74
+ pin_memory: True
75
+ num_workers: 4
76
+ augmentation:
77
+ resize: [128,192]
78
+ resize_supervision: True
79
+ preserve_depth: True
configs/papers/define/scannet_temporal_test_context_1.yaml ADDED
@@ -0,0 +1,79 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ seed: 42
3
+ min_epochs: 0
4
+ max_epochs: 0
5
+ find_unused_parameters: True
6
+ flip_lr_prob: 0.5
7
+ validate_first: True
8
+ validate_flipped: False
9
+ sync_batch_norm: True
10
+ evaluation:
11
+ rgb:
12
+ only_first: False
13
+ depth:
14
+ crop: ''
15
+ min_depth: 0.2
16
+ max_depth: 10.0
17
+ scale_output: resize
18
+ median_scaling: True
19
+ post_process: False
20
+ arch:
21
+ model:
22
+ checkpoint: /data/vidar/models/scannet_full.ckpt
23
+ file: perceiver/DefineGenericModel
24
+ use_pose_noise: []
25
+ use_virtual_cameras: []
26
+ virtual_cameras_eval: False
27
+ use_virtual_rgb: False
28
+ augment_canonical: False
29
+ encode_train: all
30
+ encode_eval: all
31
+ decode_train: all
32
+ decode_eval: all
33
+ decode_encodes: False
34
+ task_weights: [1.0,1.0]
35
+ scale_loss: True
36
+ sample_decoded_queries: 0.0
37
+ network:
38
+ tasks: [depth]
39
+ depth_range: [0.1,10.]
40
+ image_shape: [128,192]
41
+ num_bands_orig: 20
42
+ num_bands_dirs: 10
43
+ max_resolution_orig: 60
44
+ max_resolution_dirs: 60
45
+ to_world: True
46
+ d_latents: 512
47
+ num_latents: 1024
48
+ hidden_dropout_prob: 0.25
49
+ num_cross_attention_heads: 1
50
+ num_self_attends_per_block: 8
51
+ num_self_attention_heads: 8
52
+ decoder_num_heads: 1
53
+ rgb_feat_dim: 960
54
+ rgb_feat_type: resnet_all
55
+ downsample_encoder: 4
56
+ downsample_decoder: 4
57
+ upsample_convex: 'convex'
58
+ encoder_with_rgb: True
59
+ decoder_with_rgb: False
60
+ output_mode: inv_depth
61
+ sample_encoding_rays: 0
62
+ with_monodepth: False
63
+ datasets:
64
+ validation:
65
+ name: [ScanNetTemporal]
66
+ path: [/data/vidar/scannet_processed]
67
+ split: [test]
68
+ context: [1]
69
+ stride: [10]
70
+ labels: [depth,pose]
71
+ cameras: [[0]]
72
+ dataloader:
73
+ batch_size: 1
74
+ pin_memory: True
75
+ num_workers: 4
76
+ augmentation:
77
+ resize: [128,192]
78
+ resize_supervision: True
79
+ preserve_depth: True
configs/papers/depthformer/inference_kitti.yaml ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ arch:
4
+ model:
5
+ file: depth/DepthFormerModel
6
+ checkpoint: /data/vidar/models/papers/final/DepthFormer_MR_selfsup_KITTI.ckpt
7
+ warp_context: [-1,1]
8
+ match_context: [-1]
9
+ motion_masking: True
10
+ matching_augmentation: False
11
+ freeze_teacher_and_pose: 40
12
+ networks:
13
+ transformer:
14
+ recipe: networks/transformer|depthformer
15
+ mono_depth:
16
+ recipe: networks/mono_depth_res_net|default
17
+ depth_range: [0.1,100.0]
18
+ multi_depth:
19
+ recipe: networks/multi_depth_res_net|depthformer
20
+ pose:
21
+ recipe: networks/pose_net|default
22
+ evaluation:
23
+ depth:
24
+ recipe: evaluation/depth|kitti_resize
25
+ datasets:
26
+ validation:
27
+ recipe: datasets/kitti|validation_mr
28
+ labels: [depth,pose]
29
+ context: [-1,1]
30
+ save:
31
+ recipe: save|depth_splitname
configs/papers/fsm/inference_ddad.yaml ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ arch:
4
+ model:
5
+ file: depth/FSMModel
6
+ checkpoint: /data/vidar/models/papers/final/FSM_MR_6cams_DDAD.ckpt
7
+ networks:
8
+ depth:
9
+ recipe: networks/focal_depth_res_net|fsm_ddad
10
+ pose:
11
+ recipe: networks/conv_pose_net|default
12
+ evaluation:
13
+ depth:
14
+ recipe: evaluation/depth|ddad_resize
15
+ datasets:
16
+ validation:
17
+ recipe: datasets/ddad|validation_6cams
18
+ save:
19
+ recipe: save|depth_splitname
configs/papers/packnet/inference_packnet.yaml ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ arch:
4
+ model:
5
+ file: depth/SelfSupervisedModel
6
+ checkpoint: /data/vidar/models/papers/final/PackNet_MR_selfsup_KITTI.ckpt
7
+ networks:
8
+ depth:
9
+ recipe: networks/packnet|default
10
+ depth_range: [0.1,100.0]
11
+ pose:
12
+ recipe: networks/conv_pose_net|default
13
+ evaluation:
14
+ depth:
15
+ recipe: evaluation/depth|kitti_resize
16
+ datasets:
17
+ validation:
18
+ recipe: datasets/kitti|validation_mr
19
+ save:
20
+ recipe: save|depth_splitname
configs/papers/packnet/inference_resnet.yaml ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ arch:
4
+ model:
5
+ file: depth/SelfSupervisedModel
6
+ checkpoint: /data/vidar/models/papers/final/ResNet18_MR_selfsup_KITTI.ckpt
7
+ networks:
8
+ depth:
9
+ recipe: networks/mono_depth_res_net|default
10
+ depth_range: [0.1,100.0]
11
+ pose:
12
+ recipe: networks/pose_net|default
13
+ evaluation:
14
+ depth:
15
+ recipe: evaluation/depth|kitti_resize
16
+ datasets:
17
+ validation:
18
+ recipe: datasets/kitti|validation_mr
19
+ save:
20
+ recipe: save|depth_splitname
configs/papers/selfcalib/ds_euroc.yaml ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ validate_first: False
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ use_gt_intrinsics: False
8
+ networks:
9
+ depth:
10
+ recipe: networks/mono_depth_res_net|default
11
+ depth_range: [0.1,80.0]
12
+ pose:
13
+ recipe: networks/pose_net|default
14
+ intrinsics:
15
+ file: intrinsics/IntrinsicsNet
16
+ camera_model: 'DS'
17
+ shape: [256, 384]
18
+ losses:
19
+ reprojection:
20
+ recipe: losses/reprojection|default
21
+ smoothness:
22
+ recipe: losses/smoothness|default
23
+ evaluation:
24
+ depth:
25
+ recipe: evaluation/depth|kitti_resize
26
+ optimizers:
27
+ depth:
28
+ recipe: optimizers|adam_20_05
29
+ lr: 0.0002
30
+ pose:
31
+ recipe: optimizers|adam_20_05
32
+ lr: 0.0002
33
+ intrinsics:
34
+ recipe: optimizers|adam_20_05
35
+ lr: 0.01
36
+ datasets:
37
+ train:
38
+ recipe: datasets/euroc|train_selfsup
39
+ validation:
40
+ recipe: datasets/euroc|validation
configs/papers/selfcalib/eucm_euroc.yaml ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ validate_first: False
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ use_gt_intrinsics: False
8
+ networks:
9
+ depth:
10
+ recipe: networks/mono_depth_res_net|default
11
+ depth_range: [0.1,80.0]
12
+ pose:
13
+ recipe: networks/pose_net|default
14
+ intrinsics:
15
+ file: intrinsics/IntrinsicsNet
16
+ camera_model: 'EUCM'
17
+ shape: [256, 384]
18
+ losses:
19
+ reprojection:
20
+ recipe: losses/reprojection|default
21
+ smoothness:
22
+ recipe: losses/smoothness|default
23
+ evaluation:
24
+ depth:
25
+ recipe: evaluation/depth|kitti_resize
26
+ optimizers:
27
+ depth:
28
+ recipe: optimizers|adam_20_05
29
+ lr: 0.0002
30
+ pose:
31
+ recipe: optimizers|adam_20_05
32
+ lr: 0.0002
33
+ intrinsics:
34
+ recipe: optimizers|adam_20_05
35
+ lr: 0.01
36
+ datasets:
37
+ train:
38
+ recipe: datasets/euroc|train_selfsup
39
+ validation:
40
+ recipe: datasets/euroc|validation
configs/papers/selfcalib/ucm_euroc.yaml ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ validate_first: False
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ use_gt_intrinsics: False
8
+ networks:
9
+ depth:
10
+ recipe: networks/mono_depth_res_net|default
11
+ depth_range: [0.1,80.0]
12
+ pose:
13
+ recipe: networks/pose_net|default
14
+ intrinsics:
15
+ file: intrinsics/IntrinsicsNet
16
+ camera_model: 'UCM'
17
+ shape: [256, 384]
18
+ losses:
19
+ reprojection:
20
+ recipe: losses/reprojection|default
21
+ smoothness:
22
+ recipe: losses/smoothness|default
23
+ evaluation:
24
+ depth:
25
+ recipe: evaluation/depth|kitti_resize
26
+ optimizers:
27
+ depth:
28
+ recipe: optimizers|adam_20_05
29
+ lr: 0.0002
30
+ pose:
31
+ recipe: optimizers|adam_20_05
32
+ lr: 0.0002
33
+ intrinsics:
34
+ recipe: optimizers|adam_20_05
35
+ lr: 0.01
36
+ datasets:
37
+ train:
38
+ recipe: datasets/euroc|train_selfsup
39
+ validation:
40
+ recipe: datasets/euroc|validation
configs/papers/selfcalib/ucm_kitti.yaml ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wrapper:
2
+ recipe: wrapper|default
3
+ validate_first: False
4
+ arch:
5
+ model:
6
+ file: depth/SelfSupervisedModel
7
+ use_gt_intrinsics: False
8
+ networks:
9
+ depth:
10
+ recipe: networks/mono_depth_res_net|default
11
+ depth_range: [0.1,100.0]
12
+ pose:
13
+ recipe: networks/pose_net|default
14
+ intrinsics:
15
+ file: intrinsics/IntrinsicsNet
16
+ camera_model: 'UCM'
17
+ shape: [192, 640]
18
+ losses:
19
+ reprojection:
20
+ recipe: losses/reprojection|default
21
+ smoothness:
22
+ recipe: losses/smoothness|default
23
+ evaluation:
24
+ depth:
25
+ recipe: evaluation/depth|kitti_resize
26
+ optimizers:
27
+ depth:
28
+ recipe: optimizers|adam_20_05
29
+ lr: 0.0002
30
+ pose:
31
+ recipe: optimizers|adam_20_05
32
+ lr: 0.0002
33
+ intrinsics:
34
+ recipe: optimizers|adam_20_05
35
+ lr: 0.01
36
+ datasets:
37
+ train:
38
+ recipe: datasets/kitti|train_selfsup_mr
39
+ dataloader:
40
+ batch_size: 8
41
+ validation:
42
+ recipe: datasets/kitti|validation_mr
43
+ dataloader:
44
+ batch_size: 1
configs/recipes/checkpoint.yaml ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ default:
2
+ folder: /data/vidar/checkpoints
3
+ s3_bucket: miru-us-east-1/vidar/checkpoints
4
+ save_code: True
5
+ keep_top: 5
6
+ default_local:
7
+ folder: /data/vidar/checkpoints
8
+ keep_top: 5
configs/recipes/datasets/ddad.yaml ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ train_selfsup_6cams:
2
+ name: [Ouroboros]
3
+ path: [/data/vidar/DDAD/ddad.json]
4
+ split: [train]
5
+ augmentation:
6
+ jittering: [0.2, 0.2, 0.2, 0.05]
7
+ resize: [384, 640]
8
+ dataloader:
9
+ batch_size: 1
10
+ pin_memory: True
11
+ num_workers: 16
12
+ context: [-1,1]
13
+ labels: [depth]
14
+ cameras: [[1],[5],[6],[7],[8],[9]]
15
+ depth_type: [lidar]
16
+ repeat: [100]
17
+ validation_6cams:
18
+ name: [Ouroboros]
19
+ path: [/data/vidar/DDAD/ddad.json]
20
+ split: [val]
21
+ augmentation:
22
+ resize: [384, 640]
23
+ dataloader:
24
+ batch_size: 1
25
+ pin_memory: True
26
+ num_workers: 16
27
+ context: []
28
+ labels: [depth]
29
+ cameras: [[1],[5],[6],[7],[8],[9]]
30
+ depth_type: [lidar]
31
+
32
+
configs/recipes/datasets/ddad_tiny.yaml ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ train_selfsup_front:
2
+ name: [Ouroboros]
3
+ path: [/data/vidar/DDAD_tiny/ddad_tiny.json]
4
+ split: [train]
5
+ augmentation:
6
+ jittering: [0.2, 0.2, 0.2, 0.05]
7
+ resize: [384, 640]
8
+ dataloader:
9
+ batch_size: 1
10
+ pin_memory: True
11
+ num_workers: 16
12
+ context: [-1,1]
13
+ labels: [depth]
14
+ cameras: [[1]]
15
+ depth_type: [lidar]
16
+ repeat: [100]
17
+ validation_front:
18
+ name: [Ouroboros]
19
+ path: [/data/vidar/DDAD_tiny/ddad_tiny.json]
20
+ split: [train]
21
+ augmentation:
22
+ resize: [384, 640]
23
+ dataloader:
24
+ batch_size: 1
25
+ pin_memory: True
26
+ num_workers: 16
27
+ context: []
28
+ labels: [depth]
29
+ cameras: [[1]]
30
+ depth_type: [lidar]
31
+
32
+
configs/recipes/datasets/euroc.yaml ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ train_selfsup:
2
+ name: [EUROC]
3
+ path: [/data/vidar/euroc/euroc_cam/cam0]
4
+ augmentation:
5
+ jittering: [0.2, 0.2, 0.2, 0.05]
6
+ resize: [256, 384]
7
+ dataloader:
8
+ batch_size: 16
9
+ pin_memory: True
10
+ num_workers: 16
11
+ context: [-1, 1]
12
+ strides: [[49999872, 50000128]]
13
+ cameras: [[0]]
14
+ split: [euroc-train]
15
+ labels: []
16
+ repeat: [1]
17
+ validation:
18
+ name: [EUROC]
19
+ path: [/data/vidar/euroc/euroc_has_depth/V2_01_easy_has_depth/mav0/]
20
+ augmentation:
21
+ resize: [256, 384]
22
+ dataloader:
23
+ batch_size: 1
24
+ pin_memory: True
25
+ num_workers: 16
26
+ split: [euroc-val]
27
+ labels: [depth]
28
+ context: []
29
+ strides: [[0, 0]]
30
+ cameras: [[0]]
configs/recipes/datasets/generic.yaml ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ default_train:
2
+ name: [Generic]
3
+ path: [data/generic]
4
+ split: ['']
5
+ context: [-1,1]
6
+ cameras: [[0]]
7
+ labels: []
8
+ extension: [jpg]
9
+ repeat: [100]
10
+ augmentation:
11
+ jittering: [0.2, 0.2, 0.2, 0.05]
12
+ resize: [384, 640]
13
+ dataloader:
14
+ batch_size: 1
15
+ pin_memory: True
16
+ num_workers: 16
17
+ default_validation:
18
+ name: [Generic]
19
+ path: [data/generic]
20
+ split: ['']
21
+ context: []
22
+ cameras: [[0]]
23
+ labels: []
24
+ extension: [jpg]
25
+ augmentation:
26
+ resize: [384, 640]
27
+ dataloader:
28
+ batch_size: 1
29
+ pin_memory: True
30
+ num_workers: 16
configs/recipes/datasets/kitti.yaml ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ train_selfsup_mr:
2
+ name: [KITTI]
3
+ path: [/data/vidar/KITTI_raw]
4
+ split: [data_splits/eigen_zhou_files.txt]
5
+ augmentation:
6
+ jittering: [0.2, 0.2, 0.2, 0.05]
7
+ resize: [192, 640]
8
+ dataloader:
9
+ batch_size: 1
10
+ pin_memory: True
11
+ num_workers: 16
12
+ context: [-1,1]
13
+ labels: []
14
+ cameras: [[0]]
15
+ single_intrinsics: [True]
16
+ repeat: [1]
17
+ validation_mr:
18
+ name: [KITTI]
19
+ path: [/data/vidar/KITTI_raw]
20
+ split: [data_splits/eigen_test_files.txt]
21
+ augmentation:
22
+ resize: [192, 640]
23
+ dataloader:
24
+ batch_size: 1
25
+ pin_memory: True
26
+ num_workers: 16
27
+ context: []
28
+ labels: [depth]
29
+ cameras: [[0]]
30
+ single_intrinsics: [True]
31
+ depth_type: [velodyne,groundtruth]
configs/recipes/datasets/kitti_tiny.yaml ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ train_selfsup_mr:
2
+ name: [KITTI]
3
+ path: [/data/vidar/KITTI_tiny]
4
+ split: [kitti_tiny.txt]
5
+ augmentation:
6
+ jittering: [0.2,0.2,0.2,0.05]
7
+ resize: [192,640]
8
+ dataloader:
9
+ batch_size: 1
10
+ pin_memory: True
11
+ num_workers: 16
12
+ context: [-1,1]
13
+ labels: []
14
+ cameras: [[0]]
15
+ single_intrinsics: [True]
16
+ repeat: [100]
17
+ depth_type: [velodyne]
18
+ validation_mr:
19
+ name: [KITTI]
20
+ path: [/data/vidar/KITTI_tiny]
21
+ split: [kitti_tiny.txt]
22
+ augmentation:
23
+ resize: [192,640]
24
+ dataloader:
25
+ batch_size: 1
26
+ pin_memory: True
27
+ num_workers: 16
28
+ context: []
29
+ labels: [depth]
30
+ cameras: [[0]]
31
+ single_intrinsics: [True]
32
+ depth_type: [velodyne]
configs/recipes/datasets/vkitti2.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ tiny:
2
+ name: [VKITTI2]
3
+ path: [/data/vidar/VKITTI2_tiny]
4
+ split: ['']
5
+ augmentation:
6
+ resize: [192, 640]
7
+ resize_supervision: True
8
+ dataloader:
9
+ batch_size: 1
10
+ pin_memory: True
11
+ num_workers: 16
12
+ context: [-1,1]
13
+ labels: [depth,pose]
14
+ labels_context: [depth,pose]
15
+ cameras: [[0]]
16
+ depth_type: [zbuffer]
configs/recipes/evaluation/depth.yaml ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ kitti_resize:
2
+ crop: garg
3
+ min_depth: 0.0
4
+ max_depth: 80.0
5
+ scale_output: resize
6
+ median_scaling: True
7
+ post_process: True
8
+ kitti_crop:
9
+ crop: garg
10
+ min_depth: 0.0
11
+ max_depth: 80.0
12
+ scale_output: top-center
13
+ median_scaling: True
14
+ post_process: True
15
+ ddad_resize:
16
+ crop: ''
17
+ min_depth: 0.0
18
+ max_depth: 200.0
19
+ scale_output: resize
20
+ median_scaling: True
21
+ post_process: True
configs/recipes/losses/reprojection.yaml ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ default:
2
+ file: ReprojectionLoss
3
+ automasking: True
4
+ reprojection_reduce_op: min
5
+ jitter_identity_reprojection: 0.00001
6
+ photometric:
7
+ file: PhotometricLoss
8
+ weight: 1.0
9
+ alpha: 0.85
configs/recipes/losses/smoothness.yaml ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ default:
2
+ file: SmoothnessLoss
3
+ normalize: True
4
+ weight: 0.0001
5
+ gamma: 0.5
configs/recipes/losses/supervised_depth.yaml ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ huber:
2
+ file: SupervisedDepthLoss
3
+ gamma: 0.5
4
+ method: huber
5
+ mask_sparse: True
6
+ abs_rel:
7
+ file: SupervisedDepthLoss
8
+ gamma: 0.5
9
+ method: abs_rel
10
+ mask_sparse: True
11
+ l1log:
12
+ file: SupervisedDepthLoss
13
+ gamma: 0.5
14
+ method: l1log
15
+ mask_sparse: True
16
+ l1:
17
+ file: SupervisedDepthLoss
18
+ gamma: 0.5
19
+ method: l1
20
+ mask_sparse: True
21
+ mse:
22
+ file: SupervisedDepthLoss
23
+ gamma: 0.5
24
+ method: mse
25
+ mask_sparse: True
26
+ rmse:
27
+ file: SupervisedDepthLoss
28
+ gamma: 0.5
29
+ method: rmse
30
+ mask_sparse: True
31
+ mixture:
32
+ file: SupervisedDepthLoss
33
+ gamma: 0.5
34
+ method: mixture
35
+ mask_sparse: True
36
+ cross_entropy:
37
+ file: SupervisedDepthLoss
38
+ gamma: 0.5
39
+ method: cross_entropy
40
+ mask_sparse: True
configs/recipes/networks/conv_pose_net.yaml ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ default:
2
+ file: pose/ConvPoseNet
3
+ version: 18
4
+ pretrained: True
5
+ num_rgb_in: 2
configs/recipes/networks/focal_depth_res_net.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ fsm_ddad:
2
+ file: depth/FocalDepthResNet
3
+ encoder:
4
+ version: 18
5
+ pretrained: True
6
+ num_rgb_in: 1
7
+ decoder:
8
+ use_skips: True
9
+ activation: sigmoid
10
+ num_ch_out: 1
11
+ min_depth: 0.005
12
+ max_depth: 0.3
configs/recipes/networks/mono_depth_res_net.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ default:
2
+ file: depth/MonoDepthResNet
3
+ encoder:
4
+ version: 18
5
+ pretrained: True
6
+ num_rgb_in: 1
7
+ decoder:
8
+ use_skips: True
9
+ activation: sigmoid
10
+ num_ch_out: 1
configs/recipes/networks/multi_depth_res_net.yaml ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ depthformer:
2
+ file: depth/MultiDepthResNet
3
+ encoder:
4
+ version: 18
5
+ pretrained: True
6
+ input_shape: [192,640]
7
+ adaptive_bins: True
8
+ depth_range: [0.1,100.]
9
+ depth_bin_range: [0.1,100.0]
10
+ depth_binning: sid
11
+ num_depth_bins: 128
12
+ decoder:
13
+ use_skips: True
14
+ use_aux_depth: False
15
+ activation: sigmoid
16
+ num_ch_out: 1
17
+ depth_range: [0.1,100.]
configs/recipes/networks/packnet.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ default:
2
+ file: depth/PackNet
3
+ encoder:
4
+ version: 18
5
+ pretrained: True
6
+ num_rgb_in: 1
7
+ decoder:
8
+ use_skips: True
9
+ activation: sigmoid
10
+ num_ch_out: 1
configs/recipes/networks/pose_net.yaml ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ default:
2
+ file: pose/PoseNet
3
+ version: 18
4
+ pretrained: True
5
+ num_rgb_in: 2
configs/recipes/networks/transformer.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ depthformer:
2
+ file: transformers/MatchModule
3
+ context_adjustment:
4
+ expansion_ratio: 4
5
+ feat_dim: 16
6
+ num_blocks: 8
7
+ channel_dim: 128
8
+ nheads: 8
9
+ num_attn_layers: 6
10
+ min_depth: 0.1
11
+ max_depth: 100.0
12
+ num_bins: 128
configs/recipes/optimizers.yaml ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ adam_20_05:
2
+ name: Adam
3
+ lr: 0.0001
4
+ scheduler:
5
+ name: StepLR
6
+ step_size: 20
7
+ gamma: 0.5
configs/recipes/save.yaml ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ depth_splitname:
2
+ folder: /data/vidar/save
3
+ naming: splitname
4
+ rgb: [tgt]
5
+ depth: [viz,npz]
configs/recipes/wandb.yaml ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ default:
2
+ folder: /data/vidar/wandb
3
+ entity: tri
4
+ project: vidar
5
+ num_validation_logs: 5
configs/recipes/wrapper.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ default:
2
+ seed: 42
3
+ min_epochs: 0
4
+ max_epochs: 50
5
+ grad_scaler: False
6
+ find_unused_parameters: True
7
+ flip_lr_prob: 0.5
8
+ validate_first: True
9
+ validate_flipped: True
10
+ sync_batch_norm: True
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