Facility Extraction API
Module: mls.facility. This page documents 1 public functions with exact tool IDs, complete parameters, Parameters fields, and examples.
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Functions
road_facility_detection— Detect and vectorize road facilities (traffic signs, traffic lights, manhole covers, etc.) from panoramic/planar images using deep learning.
road_facility_detection
Detect and vectorize road facilities (traffic signs, traffic lights, manhole covers, etc.) from panoramic/planar images using deep learning.
- Exact tool ID:
Facility_Road_Facility_Detection - Recommended call:
mls.facility.road_facility_detection(...) - Alias:
Road_Facility_Detection - Required parameters:
input_paths,Parameters
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
input_paths |
array |
Yes | — |
Camera file paths (panoramic or planar) for facility detection. |
Parameters |
object |
Yes | — |
Facility detection parameters |
Parameters fields
| Field | Type | Required | Default | Description |
|---|---|---|---|---|
fromClass |
object |
No | — |
Class selection. JSON object mapping selection index to classification code. Example: {"0":2} |
type |
integer |
No | 0 |
Run mode: 0 = Built-in model, 2 = Custom mode |
GPU |
boolean |
No | True |
Whether to use GPU mode |
GPUID |
integer |
No | 0 |
GPU device ID |
cameraType |
integer |
No | 0 |
Camera type: 0 = panoramic, 1 = planar |
startPic |
integer |
No | 0 |
Start image index |
endPic |
integer |
No | 999999999 |
End image index |
panoramaCameraFile |
string |
No | — |
Panoramic camera file path |
planarCameraFile |
string |
No | — |
Planar camera file path |
planarCameraName |
string |
No | — |
Planar camera name |
minDis |
number |
No | 2.0 |
Minimum distance for object filtering |
maxDis |
number |
No | 20.0 |
Maximum distance for object filtering |
batchCell |
number |
No | 50.0 |
Batch processing grid size |
warningConf |
number |
No | 0.5 |
Warning sign confidence threshold |
injunctionConf |
number |
No | 0.5 |
Injunction sign confidence threshold |
instructionConf |
number |
No | 0.5 |
Instruction sign confidence threshold |
guideConf |
number |
No | 0.5 |
Guide sign confidence threshold |
travelConf |
number |
No | 0.5 |
Travel sign confidence threshold |
limitConf |
number |
No | 0.5 |
Limit sign confidence threshold |
trafficLightConf |
number |
No | 0.6 |
Traffic light confidence threshold |
auxiliaryConf |
number |
No | 0.5 |
Auxiliary facility confidence threshold |
manholeConf |
number |
No | 0.7 |
Manhole cover confidence threshold |
sewageGrateConf |
number |
No | 0.7 |
Sewage grate confidence threshold |
dustbinConf |
number |
No | 0.3 |
Dustbin confidence threshold |
monitorConf |
number |
No | 0.3 |
Monitor confidence threshold |
streetLightConf |
number |
No | 0.7 |
Street light confidence threshold |
busConf |
number |
No | 0.3 |
Bus station confidence threshold |
roadConstruction |
number |
No | 0.5 |
Road construction confidence threshold |
transformer |
number |
No | 0.3 |
Transformer confidence threshold |
pole |
number |
No | 1.1 |
Pole confidence threshold |
customRunType |
integer |
No | -1 |
Custom mode type: 0 = model mode, 1 = json mode, -1 = invalid |
customModelFullPath |
string |
No | — |
Custom model full path |
jsonDirFullPath |
string |
No | — |
JSON directory full path |
distRadius |
number |
No | 0 |
Horizontal distance radius for camera point cloud range |
targetPointLayerID |
string |
No | — |
Target point layer ID for custom mode |
Example
from gvscript import mls
params = mls.facility.road_facility_detection_parameters()
params.fromClass = {}
result = mls.facility.road_facility_detection(
Parameters=params,
input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)