@@ -68,11 +68,10 @@ const pipeline = await geoai.pipeline(
6868// Run classification
6969const result = await pipeline .inference ({
7070 inputs: { polygon: myPolygon },
71- postProcessingParams: { minArea: 20 },
7271});
7372
7473console .log (
75- ` Classified ${result .classifications .features .length } land cover areas `
74+ ` Detections ${result .detections .features .length }`
7675);
7776```
7877
@@ -83,14 +82,6 @@ console.log(
8382
8483## Parameters
8584
86- ### Post-Processing
87-
88- ``` typescript
89- postProcessingParams : {
90- minArea : 20 ; // Minimum area threshold for classification polygons
91- }
92- ```
93-
9485### Map Source
9586
9687``` typescript
@@ -114,15 +105,13 @@ mapSourceParams: {
114105
115106## Output
116107
117- Returns a list of GeoJSON FeatureCollections (one for each land cover class):
108+ Returns a FeatureCollection (each feature has its own land cover class):
118109
119110``` typescript
120111{
121112 geoRawImage : GeoRawImage , // Inference image
122113 outPutImage : GeoRawImage , // combined masks
123- binaryMasks : RawImage // binary mask for each class
124- detections : [ // list of FeatureCollection
125- {
114+ detections : {
126115 type : " FeatureCollection" ,
127116 features : [
128117 {
@@ -132,19 +121,6 @@ Returns a list of GeoJSON FeatureCollections (one for each land cover class):
132121 }
133122 }
134123 ]
135- },
136- {
137- type: " FeatureCollection" ,
138- features: [
139- {
140- geometry: { /* agriculture polygon */ },
141- properties: {
142- class: " agriculture land"
143- }
144- }
145- ]
146124 }
147- // ... one FeatureCollection for each detected land cover class
148- ]
149125}
150126```
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