pat2echo commited on
Commit
d48ce1e
·
verified ·
1 Parent(s): 7709ce0

Upload column_descriptions.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. column_descriptions.md +169 -0
column_descriptions.md ADDED
@@ -0,0 +1,169 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Kaggle column descriptions - copy/paste reference
2
+
3
+ For each group below, open every listed file's "Column descriptions" editor on the Kaggle dataset page and paste in the same column/description text.
4
+
5
+ ## Label files (start_time / end_time / action / is_fall)
6
+
7
+ **Files:**
8
+ - `train/labels/hr_fall_detection_1.csv`
9
+ - `train/labels/hr_fall_detection_2.csv`
10
+ - `train/labels/hr_fall_detection_3.csv`
11
+ - `valid/labels/fall_detection_4.csv`
12
+ - `valid/labels/fall_detection_5.csv`
13
+ - `valid/labels/fall_detection_6.csv`
14
+ - `valid/labels/fall_detection_7.csv`
15
+ - `valid/labels/fall_detection_8.csv`
16
+ - `valid/labels/fall_detection_9.csv`
17
+ - `valid/labels/fall_detection_10.csv`
18
+
19
+ **Columns:**
20
+
21
+ - `start_time` (integer): Start of the labelled segment, in seconds from the start of the video.
22
+ - `end_time` (integer): End of the labelled segment, in seconds from the start of the video.
23
+ - `action` (string): Activity/posture label for this segment (e.g. Stand, Sit, Lie). A hyphenated value (e.g. Stand-Sit) marks a transition between two states. Blank means no activity was assigned yet (e.g. before the subject enters frame).
24
+ - `is_fall` (boolean): Whether this segment is labelled as a fall event.
25
+
26
+ ## Static-pose feature files (un-predicted)
27
+
28
+ **Files:**
29
+ - `train/pose-1st-iteration/features_output.csv`
30
+ - `train/pose/features_output.csv`
31
+ - `train/pose/model1_features_output.csv`
32
+ - `train/pose/model2_features_output.csv`
33
+
34
+ **Columns:**
35
+
36
+ - `image_name` (string): Source static-pose image file name.
37
+ - `is_upright` (boolean): Whether the shoulder line is rotated enough relative to the hip line to indicate an upright torso (part of the standing-vs-lying rule).
38
+ - `percent_upright` (numeric): Confidence percentage backing the is_upright classification.
39
+ - `stand_left` (string): Left-leg standing classification from hip-knee-ankle bone-length geometry: standing, non_standing, squat, or uncertain_standing/uncertain_squat.
40
+ - `stand_right` (string): Right-leg equivalent of stand_left.
41
+ - `percent_stand_left` (numeric): Confidence percentage backing the stand_left classification.
42
+ - `percent_stand_right` (numeric): Confidence percentage backing the stand_right classification.
43
+ - `sit_left` (string): Left-leg sitting classification: sitting, non_sitting, or uncertain_sitting.
44
+ - `sit_right` (string): Right-leg equivalent of sit_left.
45
+ - `percent_sit_left` (numeric): Confidence percentage backing the sit_left classification.
46
+ - `percent_sit_right` (numeric): Confidence percentage backing the sit_right classification.
47
+ - `lie_left` (string): Left-side lying classification: lying or non_lying.
48
+ - `lie_right` (string): Right-side equivalent of lie_left.
49
+
50
+ ## Static-pose feature files (predicted)
51
+
52
+ **Files:**
53
+ - `train/pose-1st-iteration/features_output_predicted.csv`
54
+ - `train/pose/features_output_predicted.csv`
55
+ - `train/pose/model1_features_output_predicted.csv`
56
+ - `train/pose/model2_features_output_predicted.csv`
57
+
58
+ **Columns:**
59
+
60
+ - `image_name` (string): Source static-pose image file name.
61
+ - `is_upright` (boolean): Whether the shoulder line is rotated enough relative to the hip line to indicate an upright torso (part of the standing-vs-lying rule).
62
+ - `percent_upright` (numeric): Confidence percentage backing the is_upright classification.
63
+ - `stand_left` (string): Left-leg standing classification from hip-knee-ankle bone-length geometry: standing, non_standing, squat, or uncertain_standing/uncertain_squat.
64
+ - `stand_right` (string): Right-leg equivalent of stand_left.
65
+ - `percent_stand_left` (numeric): Confidence percentage backing the stand_left classification.
66
+ - `percent_stand_right` (numeric): Confidence percentage backing the stand_right classification.
67
+ - `sit_left` (string): Left-leg sitting classification: sitting, non_sitting, or uncertain_sitting.
68
+ - `sit_right` (string): Right-leg equivalent of sit_left.
69
+ - `percent_sit_left` (numeric): Confidence percentage backing the sit_left classification.
70
+ - `percent_sit_right` (numeric): Confidence percentage backing the sit_right classification.
71
+ - `lie_left` (string): Left-side lying classification: lying or non_lying.
72
+ - `lie_right` (string): Right-side equivalent of lie_left.
73
+ - `label` (string): Ground-truth static posture (stand, sit, lie, bend, squat, etc.), parsed from the image filename.
74
+ - `predicted_label` (string): The package's rule-based static-posture prediction for this image. Blank where MediaPipe failed to detect any landmarks (this happens on some lying/occluded poses).
75
+
76
+ ## K-means aspect-ratio cluster summary
77
+
78
+ **Files:**
79
+ - `train/pose/grouped_kmeans_static_pose_boundingbox_data.csv`
80
+
81
+ **Columns:**
82
+
83
+ - `aspect_ratio` (numeric): Minimum bounding-box aspect ratio within this K-means cluster. NOTE: this file is a pandas multi-index aggregation (groupby(...).agg(['min','max','mean','count'])) exported with duplicate-suffixed column names; row 0 of the data holds the literal sub-column labels ('min','max','mean','count') rather than a value - skip row 0 when loading, or treat it as a second header row.
84
+ - `aspect_ratio.1` (numeric): Maximum bounding-box aspect ratio within this K-means cluster (see column 'aspect_ratio' note about row 0).
85
+ - `aspect_ratio.2` (numeric): Mean bounding-box aspect ratio within this K-means cluster (see column 'aspect_ratio' note about row 0).
86
+ - `aspect_ratio.3` (numeric): Number of images in this K-means cluster (see column 'aspect_ratio' note about row 0).
87
+
88
+ ## Overall bounding-box summary
89
+
90
+ **Files:**
91
+ - `train/pose/grouped_static_pose_boundingbox_data.csv`
92
+
93
+ **Columns:**
94
+
95
+ - `aspect_ratio` (numeric): Mean bounding-box aspect ratio across all 113 static pose images. NOTE: same pandas multi-index export artifact as grouped_kmeans_static_pose_boundingbox_data.csv - row 0 of the data holds the literal sub-column label ('mean') rather than a value.
96
+ - `relative_width` (numeric): Mean bounding-box width as a fraction of frame width, across all 113 images (see 'aspect_ratio' column note about row 0).
97
+ - `relative_height` (numeric): Mean bounding-box height as a fraction of frame height, across all 113 images (see 'aspect_ratio' column note about row 0).
98
+
99
+ ## Bounding-box geometry (focused keypoints)
100
+
101
+ **Files:**
102
+ - `train/pose/static_pose_boundingbox_data.csv`
103
+
104
+ **Columns:**
105
+
106
+ - `image_name` (string): Source static-pose image file name.
107
+ - `frame_width` (integer): Source image width, in pixels.
108
+ - `frame_height` (integer): Source image height, in pixels.
109
+ - `aspect_ratio` (numeric): Height/width ratio of the MediaPipe pose bounding box.
110
+ - `relative_width` (numeric): Bounding box width as a fraction of the frame width.
111
+ - `relative_height` (numeric): Bounding box height as a fraction of the frame height.
112
+
113
+ ## Bounding-box geometry (all 33 keypoints)
114
+
115
+ **Files:**
116
+ - `train/pose/static_pose_boundingbox_data_all_keypoints.csv`
117
+
118
+ **Columns:**
119
+
120
+ - `image_name` (string): Source static-pose image file name.
121
+ - `frame_width` (integer): Source image width, in pixels.
122
+ - `frame_height` (integer): Source image height, in pixels.
123
+ - `aspect_ratio` (numeric): Height/width ratio of the MediaPipe pose bounding box.
124
+ - `relative_width` (numeric): Bounding box width as a fraction of the frame width.
125
+ - `relative_height` (numeric): Bounding box height as a fraction of the frame height.
126
+
127
+ ## Bounding-box geometry (with prediction)
128
+
129
+ **Files:**
130
+ - `train/pose/static_pose_boundingbox_data_bounding_box_size_predicted.csv`
131
+
132
+ **Columns:**
133
+
134
+ - `image_name` (string): Source static-pose image file name.
135
+ - `frame_width` (integer): Source image width, in pixels.
136
+ - `frame_height` (integer): Source image height, in pixels.
137
+ - `aspect_ratio` (numeric): Height/width ratio of the MediaPipe pose bounding box.
138
+ - `relative_width` (numeric): Bounding box width as a fraction of the frame width.
139
+ - `relative_height` (numeric): Bounding box height as a fraction of the frame height.
140
+ - `label` (string): Ground-truth static posture, parsed from the image filename.
141
+ - `predicted_label` (string): Posture prediction from a bounding-box-aspect-ratio-only classifier - an alternative to the landmark-angle-based classifier, useful when MediaPipe landmark detection itself fails (e.g. on occluded or lying poses).
142
+
143
+ ## Per-frame video results
144
+
145
+ **Files:**
146
+ - `train/results of static pose classifier on training videos/hr_fall_detection_static_pose_class_on_video_1_results.csv`
147
+ - `train/results of static pose classifier on training videos/hr_fall_detection_static_pose_class_on_video_2_results.csv`
148
+ - `train/results of static pose classifier on training videos/hr_fall_detection_static_pose_class_on_video_3_results.csv`
149
+
150
+ **Columns:**
151
+
152
+ - `file_name` (integer): Frame index within the source video.
153
+ - `max_value` (numeric): Peak frame-differencing magnitude used to flag motion at this frame.
154
+ - `process_image` (boolean): Whether this frame was selected for pose estimation. Frames are motion-triggered rather than exhaustively sampled, so not every frame is processed.
155
+ - `label` (string): Ground-truth posture for this frame, derived from the manual activity-label CSV for the matching video and timestamp.
156
+ - `prediction` (string): The package's rule-based static-posture prediction for this frame. Blank where the frame was not processed or no pose was detected.
157
+ - `image_name` (string): Unused in this per-frame file (carried over from the shared feature-extraction function); always blank.
158
+ - `is_upright` (boolean): Whether the shoulder line is rotated enough relative to the hip line to indicate an upright torso (part of the standing-vs-lying rule).
159
+ - `percent_upright` (numeric): Confidence percentage backing the is_upright classification.
160
+ - `stand_left` (string): Left-leg standing classification from hip-knee-ankle bone-length geometry: standing, non_standing, squat, or uncertain_standing/uncertain_squat.
161
+ - `stand_right` (string): Right-leg equivalent of stand_left.
162
+ - `percent_stand_left` (numeric): Confidence percentage backing the stand_left classification.
163
+ - `percent_stand_right` (numeric): Confidence percentage backing the stand_right classification.
164
+ - `sit_left` (string): Left-leg sitting classification: sitting, non_sitting, or uncertain_sitting.
165
+ - `sit_right` (string): Right-leg equivalent of sit_left.
166
+ - `percent_sit_left` (numeric): Confidence percentage backing the sit_left classification.
167
+ - `percent_sit_right` (numeric): Confidence percentage backing the sit_right classification.
168
+ - `lie_left` (string): Left-side lying classification: lying or non_lying.
169
+ - `lie_right` (string): Right-side equivalent of lie_left.