Merge pull request #23 from PTG-Kitware/dev/feat_v6

Refactor data generation

PTG_README.md

@@ -0,0 +1,20 @@
+# Generate training data
+
+```bash
+$ python tcn_hpl/data/utils/ptg_datagenerator.py --config configs/experiment/r18/r18.yaml
+```
+
+* Update `paths.data_dir` in the config to point to the folder generated by this script
+
+# Train
+```bash
+$ python tcn_hpl/train.py  experiment=r18/feat_v6
+```
+
+## To view training metrics
+Navigate to the ${paths.root_dir} directory set in your experiment config. Then run
+```bash
+$ aim up - p {port_num}
+```
+
+then go to ``http://127.0.0.1:{port_num}`` in your browser

configs/data/all_transforms/ActivationDelta.yaml

@@ -0,0 +1,6 @@
+ActivationDelta:
+  _target_: tcn_hpl.data.components.augmentations.ActivationDelta
+  conf_delta: 0.05
+  num_obj_classes: 42
+  feat_version: 2
+  top_k_objects: 1

configs/data/all_transforms/MoveCenterPts.yaml

@@ -2,8 +2,9 @@ MoveCenterPts:
   _target_: tcn_hpl.data.components.augmentations.MoveCenterPts
   hand_dist_delta: 0.05
   obj_dist_delta: 0.05
-  window_size: ${data.window_size}
+  joint_dist_delta: 0.025
   im_w: 1280
   im_h: 720
   num_obj_classes: 42
   feat_version: 2
+  top_k_objects: 1

configs/data/all_transforms/NormalizeFromCenter.yaml

@@ -2,4 +2,6 @@ NormalizeFromCenter:
   _target_: tcn_hpl.data.components.augmentations.NormalizeFromCenter
   im_w: 1280
   im_h: 720
-  feat_version: 3
+  num_obj_classes: 42
+  feat_version: 2
+  top_k_objects: 1

configs/data/all_transforms/NormalizePixelPts.yaml

@@ -4,3 +4,4 @@ NormalizePixelPts:
   im_h: 720
   num_obj_classes: 42
   feat_version: 2
+  top_k_objects: 1

configs/data/all_transforms/default.yaml

@@ -2,6 +2,7 @@ defaults:
   - MoveCenterPts
   - NormalizePixelPts
   - NormalizeFromCenter
+  - ActivationDelta
   - _self_
 
 train_order: ['MoveCenterPts', 'NormalizePixelPts']

configs/experiment/r18/feat_v5.yaml

@@ -0,0 +1,100 @@
+# @package _global_
+
+# to execute this experiment run:
+# python train.py experiment=example
+topic: "medical"
+task: "r18"
+feature_version: 5
+
+defaults:
+  - override /data: ptg
+  - override /model: ptg
+  - override /callbacks: default
+  - override /trainer: gpu
+  - override /paths: default
+  - override /logger: aim
+
+# all parameters below will be merged with parameters from default configurations set above
+
+tags: ["r18", "ms_tcn"]
+
+seed: 12345
+
+trainer:
+  min_epochs: 50
+  max_epochs: 500
+
+
+model:
+  compile: false
+
+  net:
+    dim: 33 # length of feature vector when top_k_objects=1
+    #dim: xx # length of feature vector when top_k_objects=2
+
+
+# GENERATE TRAINING DATA
+data_gen:
+  top_k_objects: 1
+
+  data_type: "pro"
+  dataset_kwcoco: "/data/PTG/medical/training/yolo_object_detector/detect/r18_all/r18_all_all_obj_results_with_dets_and_pose.mscoco.json"
+  train_vid_ids: [1, 2, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 17, 19, 20, 21,
+                  22, 23, 24, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40,
+                  42, 43, 44, 45, 46, 48, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
+                  61, 62, 63, 64, 65, 66, 67, 68, 69, 70]
+  val_vid_ids: [3, 7, 10, 18, 27, 32, 41]
+  test_vid_ids: [50, 13, 47, 25]
+  names_black_gloves: []
+  names_blue_gloves: []
+  #data_type: "lab"
+  #dataset_kwcoco: "/data/PTG/medical/training/yolo_object_detector/detect/r18_all_bbn_lab_data/r18_all_bbn_lab_data_all_obj_results.mscoco.json"
+  #train_vid_ids: [1, 2, 3, 4, 5, 6, 7, 8]
+  #val_vid_ids: [9]
+  #test_vid_ids: [10]
+  #names_black_gloves: []
+  #names_blue_gloves: []
+
+  filter_black_gloves: false
+  filter_blue_gloves: false
+
+  activity_config_fn: "/home/local/KHQ/hannah.defazio/angel_system/config/activity_labels/medical/r18.yaml"
+
+  # This matches the folder name created in the data generator
+  exp_name: "${task}_${data_gen.data_type}_data_top_${data_gen.top_k_objects}_objs_feat_v${feature_version}"
+
+# TRAINING
+exp_name: ${data_gen.exp_name}_win_25
+
+paths:
+  data_dir: "/data/PTG/medical/training/activity_classifier/TCN_data/${task}/${data_gen.exp_name}"
+  root_dir: "/data/PTG/medical/training/activity_classifier/TCN_HPL/"
+
+data:
+  num_classes: 6 # activities: includes background
+  batch_size: 512
+  num_workers: 0
+  epoch_length: 20000
+  window_size: 45
+  sample_rate: 1
+
+  # AUGMENTATIONS
+  all_transforms:
+    train_order: [] #["MoveCenterPts", "NormalizePixelPts"]
+    test_order: [] #["NormalizePixelPts"]
+    MoveCenterPts:
+        feat_version: ${feature_version}
+        num_obj_classes: 6 # not including background
+    NormalizeFromCenter:
+      feat_version: ${feature_version}
+    NormalizePixelPts:
+      feat_version: ${feature_version}
+      num_obj_classes: 6 # not including background
+
+
+logger:
+  aim:
+    experiment: ${exp_name}
+    capture_terminal_logs: true
+
+task_name: ${exp_name}

configs/experiment/r18/feat_v6.yaml

@@ -2,7 +2,10 @@
 
 # to execute this experiment run:
 # python train.py experiment=example
+topic: "medical"
 task: "r18"
+feature_version: 6
+
 defaults:
   - override /data: ptg
   - override /model: ptg
@@ -12,13 +15,6 @@ defaults:
   - override /logger: aim
 
 # all parameters below will be merged with parameters from default configurations set above
-# this allows you to overwrite only specified parameters
-# exp_name: "p_m2_tqt_data_test_feat_v6_with_pose" #[_v2_aug_False]
-# exp_name: "p_r18_feat_v6_with_pose_v3_aug_False_reshuffle_True" #[_v2_aug_False]
-exp_name: "p_r18_feat_v6_with_pose_v3_aug_False_reshuffle_True_bbn" #[_v2_aug_False]
-# exp_name: "p_m2_tqt_data_test_feat_v6_with_pose_v2_aug_False_reshuffle_False" #[_v2_aug_False]
-# exp_name: "p_m2_tqt_data_test_feat_v6_with_pose_v2_aug_True_reshuffle_True" #[_v2_aug_False]
-# exp_name: "p_m2_tqt_data_test_feat_v6_with_pose_v2_aug_True_reshuffle_False" #[_v2_aug_False]
 
 tags: ["r18", "ms_tcn"]
 
@@ -33,65 +29,68 @@ model:
   compile: false
 
   net:
-    dim: 209 # length of feature vector
-
-data:
-  num_classes: 6 # activities: includes background
-  batch_size: 512
-  num_workers: 0
-  epoch_length: 20000
-  window_size: 45
-  sample_rate: 1
-
-
-  all_transforms:
-    train_order: [] #["MoveCenterPts", "NormalizePixelPts"]
-    test_order: [] #["NormalizePixelPts"]
-    MoveCenterPts:
-        feat_version: 6
-        num_obj_classes: 4 # not including background
-    NormalizeFromCenter:
-      feat_version: 6
-    NormalizePixelPts:
-      feat_version: 6
-      num_obj_classes: 4 # not including background
+    dim: 297 # length of feature vector when top_k_objects=1
+    #dim: 506 # length of feature vector when top_k_objects=2
 
 
+# GENERATE TRAINING DATA
 data_gen:
-  reshuffle_datasets: true
-  augment: false
-  num_augs: 5
-  feat_type: "with_pose" #[no_pose, with_pose, only_hands_joints, only_objects_joints]
-  filter_black_gloves: false
-  filter_blue_gloves: false
+  top_k_objects: 1
+
+  data_type: "pro"
+  dataset_kwcoco: "/data/PTG/medical/training/yolo_object_detector/detect/r18_all/r18_all_all_obj_results_with_dets_and_pose.mscoco.json"
   train_vid_ids: [1, 2, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 17, 19, 20, 21,
                   22, 23, 24, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40,
                   42, 43, 44, 45, 46, 48, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
                   61, 62, 63, 64, 65, 66, 67, 68, 69, 70]
   val_vid_ids: [3, 7, 10, 18, 27, 32, 41]
   test_vid_ids: [50, 13, 47, 25]
+  names_black_gloves: []
+  names_blue_gloves: []
+  #data_type: "lab"
+  #dataset_kwcoco: "/data/PTG/medical/training/yolo_object_detector/detect/r18_all_bbn_lab_data/r18_all_bbn_lab_data_all_obj_results.mscoco.json"
+  #train_vid_ids: [1, 2, 3, 4, 5, 6, 7, 8]
+  #val_vid_ids: [9]
+  #test_vid_ids: [10]
+  #names_black_gloves: []
+  #names_blue_gloves: []
 
-  train_vid_ids_bbn: [1, 2, 3, 4, 5, 6, 7, 8]
-  val_vid_ids_bbn: [9]
-  test_vid_ids_bbn: [10]
+  filter_black_gloves: false
+  filter_blue_gloves: false
+
+  activity_config_fn: "/home/local/KHQ/hannah.defazio/angel_system/config/activity_labels/medical/r18.yaml"
+
+  # This matches the folder name created in the data generator
+  exp_name: "${task}_${data_gen.data_type}_data_top_${data_gen.top_k_objects}_objs_feat_v${feature_version}_NEW_ORDER"
+
+# TRAINING
+exp_name: ${data_gen.exp_name}_win_25_norm
 
 paths:
-  # data_dir: "/data/PTG/TCN_data/r18/p_r18_feat_v6_with_pose_v3_aug_False_reshuffle_True" #[_v2_aug_False]
-  data_dir: "/data/PTG/TCN_data/r18/p_r18_feat_v6_with_pose_v3_aug_False_reshuffle_True_bbn" #[_v2_aug_False]
-  # data_dir: "/data/PTG/TCN_data/m2/p_m2_tqt_data_test_feat_v6_with_pose_v2_aug_False_reshuffle_False" #[_v2_aug_False]
-  # data_dir: "/data/PTG/TCN_data/m2/p_m2_tqt_data_test_feat_v6_with_pose_v2_aug_True_reshuffle_True" #[_v2_aug_False]
-  # data_dir: "/data/PTG/TCN_data/m2/p_m2_tqt_data_test_feat_v6_with_pose_v2_aug_True_reshuffle_False" #[_v2_aug_False]
-  # root_dir: "/data/PTG/medical/training/activity_classifier/TCN_HPL"
-  root_dir: "/data/users/peri.akiva/PTG/medical/training/activity_classifier/TCN_HPL"
-  dataset_kwcoco: "/data/users/peri.akiva/datasets/ptg/r18_all_all_obj_results_with_dets_and_pose.mscoco.json"
-  dataset_kwcoco_lab: "/data/users/peri.akiva/datasets/ptg/r18_all_bbn_lab_data_all_obj_results_with_dets_and_pose.mscoco.json"
-  activity_config_root: "/home/local/KHQ/peri.akiva/projects/angel_system/config/activity_labels"
-  activity_config_fn: "${paths.activity_config_root}/${task}"
-  ptg_root: "/home/local/KHQ/peri.akiva/angel_system"
-  activity_config_path: "${paths.ptg_root}/config/activity_labels/medical"
-  output_data_dir_root: "/data/PTG/TCN_data"
-  # bbn_data_root: "{bbn_data_dir}/Release_v0.5/v0.56"
-  bbn_data_dir: "/data/PTG/medical/bbn_data"
+  data_dir: "/data/PTG/medical/training/activity_classifier/TCN_data/${task}/${data_gen.exp_name}"
+  root_dir: "/data/PTG/medical/training/activity_classifier/TCN_HPL/"
+
+data:
+  num_classes: 6 # activities: includes background
+  batch_size: 512
+  num_workers: 0
+  epoch_length: 20000
+  window_size: 25
+  sample_rate: 1
+
+  # AUGMENTATIONS
+  all_transforms:
+    train_order: ["MoveCenterPts", "NormalizePixelPts"]
+    test_order: ["NormalizePixelPts"]
+    MoveCenterPts:
+        feat_version: ${feature_version}
+        num_obj_classes: 6 # not including background, includes hands
+    NormalizeFromCenter:
+      feat_version: ${feature_version}
+    NormalizePixelPts:
+      feat_version: ${feature_version}
+      num_obj_classes: 6 # not including background, includes hands
+      top_k_objects: ${data_gen.top_k_objects}
 
 logger:
   aim:

configs/model/ptg.yaml

@@ -32,6 +32,7 @@ criterion:
   # weight: [1, 1, 1, 1, 1, 1]
   reduction: "mean"
 
+topic: ${topic}
 data_dir: ${paths.data_dir}
 
 # Smoothing loss weight

requirements.txt

@@ -1,13 +1,13 @@
 # --------- pytorch --------- #
-# torch>=2.0.0
-# torchvision>=0.15.0
-# lightning>=2.0.0
-# torchmetrics>=0.11.4
+torch>=2.0.0
+torchvision>=0.15.0
+lightning>=2.0.0
+torchmetrics>=0.11.4
 
 # --------- hydra --------- #
-# hydra-core==1.3.2
-# hydra-colorlog==1.2.0
-# hydra-optuna-sweeper==1.2.0
+hydra-core==1.3.2
+hydra-colorlog==1.2.0
+hydra-optuna-sweeper==1.2.0
 
 # --------- loggers --------- #
 # wandb