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modality
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2 values
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sequence_id
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10 values
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int64
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45
container_id
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10 values
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2 values
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10 values
target_visibility
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target_expected_zone
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10 values
zone_violation
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2 classes
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ngz_000001
train
image
factory_line
seq_0001
0
line_01
0 0 2560 1440
hard
zone_A
conveyor
allowed
crate_01
visible
zone_A
false
false
baseline
low
normal conveyor flow
ngz_000002
train
image
factory_line
seq_0001
1
line_01
0 0 2560 1440
hard
zone_B
maintenance_only
no_go
crate_01
visible
zone_A
true
false
zone_violation
high
crate placed in maintenance zone
ngz_000003
train
video
warehouse
seq_0002
12
wh_03
0 0 1920 1080
soft
zone_C
pedestrian_path
restricted
robot_07
visible
zone_D
true
false
zone_violation
medium
robot entering path with humans
ngz_000004
train
video
warehouse
seq_0002
13
wh_03
0 0 1920 1080
soft
zone_D
robot_lane
allowed
robot_07
visible
zone_D
false
false
baseline
low
robot back on assigned track
ngz_000005
train
image
lab_space
seq_0003
0
lab_01
0 0 1920 1080
hard
zone_E
biohazard
no_go
person_03
visible
zone_F
true
false
zone_violation
high
human crossing containment line
ngz_000006
train
image
lab_space
seq_0003
1
lab_01
0 0 1920 1080
hard
zone_F
observation_lane
allowed
person_03
visible
zone_F
false
false
baseline
low
correct position
ngz_000007
train
video
sports_pitch
seq_0004
30
pitch_02
0 0 1920 1080
soft
zone_G
referee_only
no_go
player_11
visible
zone_H
true
false
zone_violation
medium
player entering referee zone
ngz_000008
train
video
sports_pitch
seq_0004
31
pitch_02
0 0 1920 1080
soft
zone_H
play_zone
allowed
player_11
visible
zone_H
false
false
baseline
low
allowed space
ngz_000009
valid
image
construction
seq_0100
0
site_01
0 0 1920 1080
hard
zone_I
heavy_machinery
no_go
worker_04
visible
zone_J
true
false
zone_violation
high
worker next to active crane
ngz_000010
valid
image
construction
seq_0100
1
site_01
0 0 1920 1080
hard
zone_J
walkable
allowed
worker_04
visible
zone_J
false
false
baseline
low
correct safety compliance
ngz_000011
valid
video
hospital
seq_0200
18
ward_07
0 0 1920 1080
soft
zone_K
sterile_field
no_go
nurse_02
partial
zone_L
true
true
occlusion_test
high
partial occlusion inside sterile field
ngz_000012
valid
video
hospital
seq_0200
19
ward_07
0 0 1920 1080
soft
zone_L
staff_lane
allowed
nurse_02
visible
zone_L
false
false
baseline
low
returns to safe zone
ngz_000013
eval
image
airport
seq_0300
0
gate_03
0 0 2560 1440
hard
zone_M
security
no_go
bag_21
visible
zone_N
true
false
zone_violation
high
bag positioned past screening line
ngz_000014
eval
image
airport
seq_0300
1
gate_03
0 0 2560 1440
hard
zone_N
pre_screen
allowed
bag_21
visible
zone_N
false
false
baseline
low
correct container position
ngz_000015
eval
video
indoor_room
seq_0400
10
room_09
0 0 1920 1080
porous
zone_O
fragile_display
no_go
child_05
visible
zone_P
true
false
zone_violation
medium
child crossing rope barrier
ngz_000016
eval
video
indoor_room
seq_0400
11
room_09
0 0 1920 1080
porous
zone_P
visitor_lane
allowed
child_05
visible
zone_P
false
false
baseline
low
back in safe space
ngz_000017
eval
image
port
seq_0500
0
dock_01
0 0 2560 1440
hard
zone_Q
cargo_drop
no_go
worker_12
visible
zone_R
true
false
zone_violation
high
worker too close to suspended load
ngz_000018
eval
image
port
seq_0500
1
dock_01
0 0 2560 1440
hard
zone_R
markings
allowed
worker_12
visible
zone_R
false
false
baseline
low
correct alignment
ngz_000019
eval
video
airport
seq_0600
44
runway_02
0 0 2560 1440
hard
zone_S
runway
no_go
service_vehicle
visible
zone_T
true
false
zone_violation
high
vehicle on runway during takeoff prep
ngz_000020
eval
video
airport
seq_0600
45
runway_02
0 0 2560 1440
hard
zone_T
taxi_lane
allowed
service_vehicle
visible
zone_T
false
false
baseline
low
vehicle moving to allowed lane

ClarusC64/no_go_zone_compliance_v01

Dataset summary

This dataset checks whether models respect no-go zones inside a container.
A no-go zone is a region where entities must not appear for functional or safety reasons.
The dataset includes allowed zones, restricted zones, and no-go zones across multiple domains.

Core behavior tested

  • detect when an entity enters a no-go zone
  • classify zone status per frame
  • maintain zone compliance under occlusion
  • track transitions back to safe areas

Domains

  • factory lines (maintenance areas)
  • warehouses (pedestrian vs robot lanes)
  • labs (biohazard containment)
  • sports pitches (referee-only regions)
  • airports (runway vs taxi lanes)
  • hospitals (sterile fields)
  • construction sites (heavy machinery areas)

Key columns

  • zone_type: type of region inside the container
  • zone_status: allowed, restricted, or no_go
  • zone_violation: true if entity enters no_go
  • target_expected_zone: where the entity should be
  • drift_risk: likelihood of spatial failure

Sample failure questions

  • does the model treat restricted areas as normal?
  • does occlusion hide a violation?
  • does motion prediction cross forbidden boundaries?

Example usage

from datasets import load_dataset

ds = load_dataset("ClarusC64/no_go_zone_compliance_v01")

frame = ds["eval"][0]

print(frame["zone_id"], frame["zone_status"], frame["zone_violation"])
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