Remove instanceId field

Author: benITo47

docs/docs/03-hooks/02-computer-vision/useInstanceSegmentation.md

@@ -15,13 +15,10 @@ It is recommended to use models provided by us, which are available at our [Hugg
 ## High Level Overview
 
 ```typescript
-import { useInstanceSegmentation } from 'react-native-executorch';
+import { useInstanceSegmentation, YOLO26N_SEG } from 'react-native-executorch';
 
 const model = useInstanceSegmentation({
-  model: {
-    modelName: 'yolo26n-seg',
-    modelSource: 'https://huggingface.co/.../yolo26n-seg.pte',
-  },
+  model: YOLO26N_SEG,
 });
 
 const imageUri = 'file:///Users/.../photo.jpg';
@@ -39,7 +36,7 @@ try {
 `useInstanceSegmentation` takes [`InstanceSegmentationProps`](../../06-api-reference/interfaces/InstanceSegmentationProps.md) that consists of:
 
 - `model` - An object containing:
-  - `modelName` - The name of a built-in model. See [`InstanceSegmentationModelSources`](../../06-api-reference/interfaces/InstanceSegmentationProps.md) for the list of supported models.
+  - `modelName` - The name of a built-in model. See [`InstanceSegmentationModelName`](../../06-api-reference/types/InstanceSegmentationModelName.md) for the list of supported models.
   - `modelSource` - The location of the model binary (a URL or a bundled resource).
 - An optional flag [`preventLoad`](../../06-api-reference/interfaces/InstanceSegmentationProps.md#preventload) which prevents auto-loading of the model.
 
@@ -78,19 +75,15 @@ To run the model, use the [`forward`](../../06-api-reference/interfaces/Instance
 - `mask` - A `Uint8Array` binary mask (0 or 1) representing the instance's segmentation.
 - `maskWidth` - Width of the mask array.
 - `maskHeight` - Height of the mask array.
-- `instanceId` - Unique identifier for this instance.
 
 ## Example
 
 ```typescript
-import { useInstanceSegmentation } from 'react-native-executorch';
+import { useInstanceSegmentation, YOLO26N_SEG } from 'react-native-executorch';
 
 function App() {
   const model = useInstanceSegmentation({
-    model: {
-      modelName: 'yolo26n-seg',
-      modelSource: 'https://huggingface.co/.../yolo26n-seg.pte',
-    },
+    model: YOLO26N_SEG,
   });
 
   const handleSegment = async () => {

packages/react-native-executorch/common/rnexecutorch/host_objects/JsiConversions.h

@@ -487,7 +487,6 @@ getJsiValue(const std::vector<models::instance_segmentation::types::Instance>
     instance.setProperty(runtime, "classIndex", instances[i].classIndex);
 
     instance.setProperty(runtime, "score", instances[i].score);
-    instance.setProperty(runtime, "instanceId", instances[i].instanceId);
 
     array.setValueAtIndex(runtime, i, instance);
   }

packages/react-native-executorch/common/rnexecutorch/models/instance_segmentation/BaseInstanceSegmentation.cpp

@@ -284,10 +284,6 @@ std::vector<types::Instance> BaseInstanceSegmentation::finalizeInstances(
     instances.resize(maxInstances);
   }
 
-  for (int32_t i = 0; std::cmp_less(i, instances.size()); ++i) {
-    instances[i].instanceId = i;
-  }
-
   return instances;
 }
 
@@ -357,7 +353,7 @@ std::vector<types::Instance> BaseInstanceSegmentation::postprocess(
         bboxOriginal,
         std::vector<uint8_t>(binaryMask.data,
                              binaryMask.data + binaryMask.total()),
-        binaryMask.cols, binaryMask.rows, labelIdx, score, i);
+        binaryMask.cols, binaryMask.rows, labelIdx, score);
   }
 
   return finalizeInstances(std::move(instances), iouThreshold, maxInstances);

packages/react-native-executorch/common/rnexecutorch/models/instance_segmentation/Types.h

@@ -10,7 +10,7 @@ namespace rnexecutorch::models::instance_segmentation::types {
  * Represents a single detected instance in instance segmentation output.
  *
  * Contains bounding box coordinates, binary segmentation mask, class label,
- * confidence score, and a unique instance identifier.
+ * and confidence score.
  */
 struct Instance {
   utils::computer_vision::BBox bbox; ///< Bounding box coordinates
@@ -19,15 +19,13 @@ struct Instance {
   int32_t maskHeight;                ///< Height of the mask array
   int32_t classIndex;                ///< Model output class index
   float score;                       ///< Confidence score [0, 1]
-  int32_t instanceId;                ///< Unique identifier for this instance
 
   Instance() = default;
   Instance(utils::computer_vision::BBox bbox, std::vector<uint8_t> mask,
            int32_t maskWidth, int32_t maskHeight, int32_t classIndex,
-           float score, int32_t instanceId)
+           float score)
       : bbox(bbox), mask(std::move(mask)), maskWidth(maskWidth),
-        maskHeight(maskHeight), classIndex(classIndex), score(score),
-        instanceId(instanceId) {}
+        maskHeight(maskHeight), classIndex(classIndex), score(score) {}
 };
 
 } // namespace rnexecutorch::models::instance_segmentation::types

packages/react-native-executorch/common/rnexecutorch/tests/integration/InstanceSegmentationTest.cpp

@@ -170,19 +170,6 @@ TEST(InstanceSegResultTests, InstancesHaveValidMasks) {
   }
 }
 
-TEST(InstanceSegResultTests, InstancesHaveUniqueIds) {
-  BaseInstanceSegmentation model(kValidInstanceSegModelPath, {}, {}, true,
-                                 nullptr);
-  auto results =
-      model.generate(kValidTestImagePath, 0.3, 0.5, 100, {}, true, kMethodName);
-
-  std::set<int> ids;
-  for (const auto &inst : results) {
-    EXPECT_TRUE(ids.insert(inst.instanceId).second)
-        << "Duplicate instanceId: " << inst.instanceId;
-  }
-}
-
 TEST(InstanceSegResultTests, InstancesHaveValidClassIndices) {
   BaseInstanceSegmentation model(kValidInstanceSegModelPath, {}, {}, true,
                                  nullptr);

packages/react-native-executorch/src/modules/computer_vision/InstanceSegmentationModule.ts

@@ -343,7 +343,6 @@ export class InstanceSegmentationModule<
         label: (labelLookup[inst.classIndex - labelEnumOffset] ??
           String(inst.classIndex)) as keyof ResolveLabels<T>,
         score: inst.score,
-        instanceId: inst.instanceId,
       }));
     };
   }
@@ -357,7 +356,7 @@ export class InstanceSegmentationModule<
    *
    * @param input - Image source (string path or PixelData object)
    * @param options - Optional configuration for the segmentation process. Includes `confidenceThreshold`, `iouThreshold`, `maxInstances`, `classesOfInterest`, `returnMaskAtOriginalResolution`, and `inputSize`.
-   * @returns A Promise resolving to an array of {@link SegmentedInstance} objects with `bbox`, `mask`, `maskWidth`, `maskHeight`, `label`, `score`, and `instanceId`.
+   * @returns A Promise resolving to an array of {@link SegmentedInstance} objects with `bbox`, `mask`, `maskWidth`, `maskHeight`, `label`, `score`.
    * @throws {RnExecutorchError} If the model is not loaded or if an invalid `inputSize` is provided.
    *
    * @example
@@ -455,7 +454,6 @@ export class InstanceSegmentationModule<
         inst.classIndex - this.labelEnumOffset
       ) ?? String(inst.classIndex)) as keyof ResolveLabels<T>,
       score: inst.score,
-      instanceId: inst.instanceId,
     }));
   }
 }

packages/react-native-executorch/src/types/instanceSegmentation.ts

@@ -15,7 +15,6 @@ export interface NativeSegmentedInstance {
   maskHeight: number;
   classIndex: number;
   score: number;
-  instanceId: number;
 }
 
 /**
@@ -29,7 +28,6 @@ export interface NativeSegmentedInstance {
  * @property {number} maskHeight - Height of the mask array.
  * @property {keyof L} label - The class label of the instance.
  * @property {number} score - Confidence score [0, 1].
- * @property {number} instanceId - Unique identifier for this instance.
  */
 export interface SegmentedInstance<L extends LabelEnum> {
   bbox: Bbox;
@@ -38,7 +36,6 @@ export interface SegmentedInstance<L extends LabelEnum> {
   maskHeight: number;
   label: keyof L;
   score: number;
-  instanceId: number;
 }
 
 /**