Merge pull request #24 from PTG-Kitware/dev/pose_repeat_rate

Add pose_repeat_rate to data generator to mimic online data
PTG-Kitware · May 16, 2024 · fe03abe · fe03abe
2 parents 33a8c92 + 818c848
commit fe03abe
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Showing 3 changed files with 45 additions and 22 deletions.
diff --git a/configs/experiment/r18/feat_v5.yaml b/configs/experiment/r18/feat_v5.yaml
@@ -32,10 +32,16 @@ model:
     dim: 33 # length of feature vector when top_k_objects=1
     #dim: xx # length of feature vector when top_k_objects=2
 
+# LIVE HZ
+IMAGE_HZ: 30 # zed bags
+#IMAGE_HZ: 15 # BBN hololens live
+OBJECT_DET_HZ: 15
+POSE_HZ: 4
 
 # GENERATE TRAINING DATA
 data_gen:
   top_k_objects: 1
+  pose_repeat_rate: 0 # Not applicable for this feature version
 
   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"
@@ -61,36 +67,40 @@ data_gen:
   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}"
+  exp_ext: "_NEW_ORDER_fix_overlap_gt" # anything unique about this run that isn't already in  exp_name
+  exp_name: "${task}_${data_gen.data_type}_data_top_${data_gen.top_k_objects}_objs_feat_v${feature_version}_pose_rate_${data_gen.pose_repeat_rate}${data_gen.exp_ext}"
 
 # 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
+  window_size: 25
+  sample_rate: 2 # ${IMAGE_HZ} / ${OBJECT_DET_HZ}
 
   # AUGMENTATIONS
   all_transforms:
     train_order: [] #["MoveCenterPts", "NormalizePixelPts"]
     test_order: [] #["NormalizePixelPts"]
     MoveCenterPts:
         feat_version: ${feature_version}
-        num_obj_classes: 6 # not including background
+        num_obj_classes: 6 # not including background, includes hands
+        top_k_objects: ${data_gen.top_k_objects}
     NormalizeFromCenter:
       feat_version: ${feature_version}
+      num_obj_classes: 6 # not including background, includes hands
+      top_k_objects: ${data_gen.top_k_objects}
     NormalizePixelPts:
       feat_version: ${feature_version}
-      num_obj_classes: 6 # not including background
+      num_obj_classes: 6 # not including background, includes hands
+      top_k_objects: ${data_gen.top_k_objects}
 
+exp_name: ${data_gen.exp_name}_win_${data.window_size}_obj_sample_${data.sample_rate}
+
+paths:
+  data_dir: "/data/PTG/medical/training/activity_classifier/TCN_data/${task}/${data_gen.exp_name}"
+  root_dir: "/data/PTG/medical/training/activity_classifier/TCN_HPL/"
 
 logger:
   aim:

diff --git a/configs/experiment/r18/feat_v6.yaml b/configs/experiment/r18/feat_v6.yaml
@@ -32,10 +32,16 @@ model:
     dim: 297 # length of feature vector when top_k_objects=1
     #dim: 506 # length of feature vector when top_k_objects=2
 
+# LIVE HZ
+IMAGE_HZ: 30 # zed bags
+#IMAGE_HZ: 15 # BBN hololens live
+OBJECT_DET_HZ: 15
+POSE_HZ: 4
 
 # GENERATE TRAINING DATA
 data_gen:
   top_k_objects: 1
+  pose_repeat_rate: 7.5 # ${IMAGE_HZ} / ${POSE_HZ}
 
   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"
@@ -61,37 +67,41 @@ data_gen:
   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"
+  exp_ext: "_NEW_ORDER_fix_overlap_gt" # anything unique about this run that isn't already in ``exp_name``
+  exp_name: "${task}_${data_gen.data_type}_data_top_${data_gen.top_k_objects}_objs_feat_v${feature_version}_pose_rate_${data_gen.pose_repeat_rate}${data_gen.exp_ext}"
 
 # TRAINING
-exp_name: ${data_gen.exp_name}_win_25_norm
-
-paths:
-  data_dir: "/data/PTG/medical/training/activity_classifier/TCN_data/${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: 25
-  sample_rate: 1
+  sample_rate: 2 # ${IMAGE_HZ} / ${OBJECT_DET_HZ}
 
   # AUGMENTATIONS
   all_transforms:
-    train_order: ["MoveCenterPts", "NormalizePixelPts"]
-    test_order: ["NormalizePixelPts"]
+    train_order: [] #["MoveCenterPts", "NormalizePixelPts"]
+    test_order: [] #["NormalizePixelPts"]
     MoveCenterPts:
         feat_version: ${feature_version}
         num_obj_classes: 6 # not including background, includes hands
+        top_k_objects: ${data_gen.top_k_objects}
     NormalizeFromCenter:
       feat_version: ${feature_version}
+      num_obj_classes: 6 # not including background, includes hands
+      top_k_objects: ${data_gen.top_k_objects}
     NormalizePixelPts:
       feat_version: ${feature_version}
       num_obj_classes: 6 # not including background, includes hands
       top_k_objects: ${data_gen.top_k_objects}
 
+exp_name: ${data_gen.exp_name}_win_${data.window_size}_obj_sample_${data.sample_rate}
+
+paths:
+  data_dir: "/data/PTG/medical/training/activity_classifier/TCN_data/${task}/${data_gen.exp_name}"
+  root_dir: "/data/PTG/medical/training/activity_classifier/TCN_HPL/"
+
 logger:
   aim:
     experiment: ${exp_name}

diff --git a/tcn_hpl/data/utils/ptg_datagenerator.py b/tcn_hpl/data/utils/ptg_datagenerator.py
@@ -47,6 +47,8 @@ def create_training_data(config_path):
     blue_glove_vids = config["data_gen"].get("blue_glove_vids", [])
     activity_config_fn = config["data_gen"]["activity_config_fn"]
     top_k_objects = config["data_gen"]["top_k_objects"]
+    pose_repeat_rate = config["data_gen"]["pose_repeat_rate"]
+    exp_ext = config["data_gen"]["exp_ext"]
 
     dset = kwcoco.CocoDataset(config["data_gen"]["dataset_kwcoco"])
     # Check if the dest has activity gt, if it doesn't then add it
@@ -86,7 +88,7 @@ def filter_dset_by_split(split):
     #####################
     # Output
     #####################
-    exp_name = f"{task_name}_{task_data_type}_data_top_{top_k_objects}_objs_feat_v{feat_version}_NEW_ORDER"
+    exp_name = f"{task_name}_{task_data_type}_data_top_{top_k_objects}_objs_feat_v{feat_version}_pose_rate_{pose_repeat_rate}{exp_ext}"
     data_dir = f"/data/PTG/{topic}/training/activity_classifier"
     output_data_dir = f"{data_dir}/TCN_data/{task_name}/{exp_name}"
     print(output_data_dir)
@@ -190,6 +192,7 @@ def filter_dset_by_split(split):
                 ann_by_image,
                 feat_version=feat_version,
                 top_k_objects=top_k_objects,
+                pose_repeat_rate=pose_repeat_rate
             )
             print(X.shape)