fix: Add fixes in Instance Segmentation

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

@@ -53,6 +53,8 @@ For more information on loading resources, take a look at [loading models](../..
 - `error` - An error object if the model failed to load or encountered a runtime error.
 - `downloadProgress` - A value between 0 and 1 representing the download progress of the model binary.
 - `forward` - A function to run inference on an image.
+- `getAvailableInputSizes` - Returns the available input sizes for the loaded model, or `undefined` if the model accepts only a single input size. Use this to populate UI controls for selecting the input resolution.
+- `runOnFrame` - A synchronous worklet function for real-time VisionCamera frame processing. Returns `null` until the model is ready. See [VisionCamera Integration](./visioncamera-integration.md) for usage.
 
 ## Running the model
 

packages/react-native-executorch/src/hooks/computer_vision/useInstanceSegmentation.ts

@@ -13,10 +13,10 @@ import { useModuleFactory } from '../useModuleFactory';
  * React hook for managing an Instance Segmentation model instance.
  * @typeParam C - A {@link InstanceSegmentationModelSources} config specifying which model to load.
  * @param props - Configuration object containing `model` config and optional `preventLoad` flag.
- * @returns An object with model state (`error`, `isReady`, `isGenerating`, `downloadProgress`) and a typed `forward` function.
+ * @returns An object with model state (`error`, `isReady`, `isGenerating`, `downloadProgress`), a typed `forward` function, `getAvailableInputSizes` helper, and a `runOnFrame` worklet for VisionCamera integration.
  * @example
  * ```ts
- * const { isReady, isGenerating, forward, error, downloadProgress } =
+ * const { isReady, isGenerating, forward, error, downloadProgress, getAvailableInputSizes, runOnFrame } =
  *   useInstanceSegmentation({
  *     model: {
  *       modelName: 'yolo26n-seg',

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

@@ -276,15 +276,14 @@ export class InstanceSegmentationModule<
    * Override runOnFrame to add label mapping for VisionCamera integration.
    * The parent's runOnFrame returns raw native results with class indices;
    * this override maps them to label strings and provides an options-based API.
-   * @returns A worklet function for VisionCamera frame processing, or null if the model is not loaded.
+   * @returns A worklet function for VisionCamera frame processing.
+   * @throws {RnExecutorchError} If the underlying native worklet is unavailable (should not occur on a loaded module).
    */
-  override get runOnFrame():
-    | ((
-        frame: Frame,
-        isFrontCamera: boolean,
-        options?: InstanceSegmentationOptions<ResolveLabels<T>>
-      ) => SegmentedInstance<ResolveLabels<T>>[])
-    | null {
+  override get runOnFrame(): (
+    frame: Frame,
+    isFrontCamera: boolean,
+    options?: InstanceSegmentationOptions<ResolveLabels<T>>
+  ) => SegmentedInstance<ResolveLabels<T>>[] {
     const baseRunOnFrame = super.runOnFrame;
     if (!baseRunOnFrame) {
       throw new RnExecutorchError(

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

@@ -144,15 +144,14 @@ export class ObjectDetectionModule<
 
   /**
    * Override runOnFrame to provide an options-based API for VisionCamera integration.
-   * @returns A worklet function for frame processing, or null if the model is not loaded.
+   * @returns A worklet function for frame processing.
+   * @throws {RnExecutorchError} If the underlying native worklet is unavailable (should not occur on a loaded module).
    */
-  override get runOnFrame():
-    | ((
-        frame: any,
-        isFrontCamera: boolean,
-        options?: ObjectDetectionOptions<ResolveLabels<T>>
-      ) => Detection<ResolveLabels<T>>[])
-    | null {
+  override get runOnFrame(): (
+    frame: any,
+    isFrontCamera: boolean,
+    options?: ObjectDetectionOptions<ResolveLabels<T>>
+  ) => Detection<ResolveLabels<T>>[] {
     const baseRunOnFrame = super.runOnFrame;
     if (!baseRunOnFrame) {
       throw new RnExecutorchError(

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

@@ -32,7 +32,7 @@ export abstract class VisionModule<TOutput> extends BaseModule {
   /**
    * Synchronous worklet function for real-time VisionCamera frame processing.
    *
-   * Only available after the model is loaded. Returns null if not loaded.
+   * Only available after the model is loaded.
    *
    * **Use this for VisionCamera frame processing in worklets.**
    * For async processing, use `forward()` instead.
@@ -55,9 +55,10 @@ export abstract class VisionModule<TOutput> extends BaseModule {
    *   }
    * });
    * ```
-   * @returns A worklet function for frame processing, or null if the model is not loaded.
+   * @returns A worklet function for frame processing.
+   * @throws {RnExecutorchError} If the model is not loaded.
    */
-  get runOnFrame(): ((frame: Frame, ...args: any[]) => TOutput) | null {
+  get runOnFrame(): (frame: Frame, ...args: any[]) => TOutput {
     if (!this.nativeModule) {
       throw new RnExecutorchError(
         RnExecutorchErrorCode.ModuleNotLoaded,

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

@@ -196,7 +196,9 @@ export interface InstanceSegmentationType<L extends LabelEnum> {
    * **Use this for VisionCamera frame processing in worklets.**
    * For async processing, use `forward()` instead.
    *
-   * Available after model is loaded (`isReady: true`).
+   * `null` until the model is ready (`isReady: true`). The property itself is
+   * `null` when the model has not loaded yet — the function always returns an
+   * array (never `null`) once called.
    * @param frame - VisionCamera Frame object
    * @param isFrontCamera - Whether the front camera is active (for mirroring correction).
    * @param options - Optional configuration for the segmentation process.

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

@@ -6,10 +6,10 @@ export { CocoLabel };
 /**
  * Represents a bounding box for a detected object in an image.
  * @category Types
- * @property {number} x1 - The x-coordinate of the bottom-left corner of the bounding box.
- * @property {number} y1 - The y-coordinate of the bottom-left corner of the bounding box.
- * @property {number} x2 - The x-coordinate of the top-right corner of the bounding box.
- * @property {number} y2 - The y-coordinate of the top-right corner of the bounding box.
+ * @property {number} x1 - The x-coordinate of the top-left corner of the bounding box.
+ * @property {number} y1 - The y-coordinate of the top-left corner of the bounding box.
+ * @property {number} x2 - The x-coordinate of the bottom-right corner of the bounding box.
+ * @property {number} y2 - The y-coordinate of the bottom-right corner of the bounding box.
  */
 export interface Bbox {
   x1: number;