feat: suggested changes / improve comments

Author: NorbertKlockiewicz

apps/computer-vision/app/object_detection_live/index.tsx

@@ -182,8 +182,6 @@ const styles = StyleSheet.create({
     fontWeight: '600',
     letterSpacing: 0.3,
   },
-
-  // Bottom stats bar
   bottomBarWrapper: {
     position: 'absolute',
     bottom: 0,

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

@@ -346,6 +346,15 @@ inline jsi::Value getJsiValue(const std::vector<char> &vec,
   return {runtime, array};
 }
 
+inline jsi::Value getJsiValue(const std::vector<int64_t> &vec,
+                              jsi::Runtime &runtime) {
+  jsi::Array array(runtime, vec.size());
+  for (size_t i = 0; i < vec.size(); i++) {
+    array.setValueAtIndex(runtime, i, jsi::Value(static_cast<double>(vec[i])));
+  }
+  return {runtime, array};
+}
+
 // Conditional as on android, size_t and uint64_t reduce to the same type,
 // introducing ambiguity
 template <typename T,
@@ -360,15 +369,6 @@ inline jsi::Value getJsiValue(uint64_t val, jsi::Runtime &runtime) {
   return {runtime, bigInt};
 }
 
-inline jsi::Value getJsiValue(const std::vector<int64_t> &vec,
-                              jsi::Runtime &runtime) {
-  jsi::Array array(runtime, vec.size());
-  for (size_t i = 0; i < vec.size(); i++) {
-    array.setValueAtIndex(runtime, i, jsi::Value(static_cast<double>(vec[i])));
-  }
-  return {runtime, array};
-}
-
 inline jsi::Value getJsiValue(int val, jsi::Runtime &runtime) {
   return {runtime, val};
 }

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

@@ -46,6 +46,12 @@ template <typename Model> class ModelHostObject : public JsiHostObject {
           "getInputShape"));
     }
 
+    if constexpr (meta::HasGenerate<Model>) {
+      addFunctions(JSI_EXPORT_FUNCTION(ModelHostObject<Model>,
+                                       promiseHostFunction<&Model::generate>,
+                                       "generate"));
+    }
+
     if constexpr (meta::HasEncode<Model>) {
       addFunctions(JSI_EXPORT_FUNCTION(ModelHostObject<Model>,
                                        promiseHostFunction<&Model::encode>,

packages/react-native-executorch/common/rnexecutorch/metaprogramming/TypeConcepts.h

@@ -11,6 +11,11 @@ concept DerivedFromOrSameAs = std::is_base_of_v<Base, T>;
 template <typename T, typename Base>
 concept SameAs = std::is_same_v<Base, T>;
 
+template <typename T>
+concept HasGenerate = requires(T t) {
+  { &T::generate };
+};
+
 template <typename T>
 concept HasGenerateFromString = requires(T t) {
   { &T::generateFromString };

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

@@ -122,7 +122,7 @@ TEST(ObjectDetectionGenerateTests, DetectionsHaveValidLabels) {
 // ============================================================================
 TEST(ObjectDetectionPixelTests, ValidPixelDataReturnsResults) {
   ObjectDetection model(kValidObjectDetectionModelPath, nullptr);
-  constexpr int width = 4, height = 4, channels = 3;
+  constexpr int32_t width = 4, height = 4, channels = 3;
   std::vector<uint8_t> pixelData(width * height * channels, 128);
   JSTensorViewIn tensorView{pixelData.data(),
                             {height, width, channels},
@@ -142,7 +142,7 @@ TEST(ObjectDetectionPixelTests, WrongSizesLengthThrows) {
 
 TEST(ObjectDetectionPixelTests, WrongChannelCountThrows) {
   ObjectDetection model(kValidObjectDetectionModelPath, nullptr);
-  constexpr int width = 4, height = 4, channels = 4;
+  constexpr int32_t width = 4, height = 4, channels = 4;
   std::vector<uint8_t> pixelData(width * height * channels, 0);
   JSTensorViewIn tensorView{pixelData.data(),
                             {height, width, channels},
@@ -153,7 +153,7 @@ TEST(ObjectDetectionPixelTests, WrongChannelCountThrows) {
 
 TEST(ObjectDetectionPixelTests, WrongScalarTypeThrows) {
   ObjectDetection model(kValidObjectDetectionModelPath, nullptr);
-  constexpr int width = 4, height = 4, channels = 3;
+  constexpr int32_t width = 4, height = 4, channels = 3;
   std::vector<uint8_t> pixelData(width * height * channels, 0);
   JSTensorViewIn tensorView{pixelData.data(),
                             {height, width, channels},
@@ -164,7 +164,7 @@ TEST(ObjectDetectionPixelTests, WrongScalarTypeThrows) {
 
 TEST(ObjectDetectionPixelTests, NegativeThresholdThrows) {
   ObjectDetection model(kValidObjectDetectionModelPath, nullptr);
-  constexpr int width = 4, height = 4, channels = 3;
+  constexpr int32_t width = 4, height = 4, channels = 3;
   std::vector<uint8_t> pixelData(width * height * channels, 128);
   JSTensorViewIn tensorView{pixelData.data(),
                             {height, width, channels},
@@ -175,7 +175,7 @@ TEST(ObjectDetectionPixelTests, NegativeThresholdThrows) {
 
 TEST(ObjectDetectionPixelTests, ThresholdAboveOneThrows) {
   ObjectDetection model(kValidObjectDetectionModelPath, nullptr);
-  constexpr int width = 4, height = 4, channels = 3;
+  constexpr int32_t width = 4, height = 4, channels = 3;
   std::vector<uint8_t> pixelData(width * height * channels, 128);
   JSTensorViewIn tensorView{pixelData.data(),
                             {height, width, channels},

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

@@ -28,6 +28,7 @@ export class ObjectDetectionModule extends VisionModule<Detection[]> {
         onDownloadProgressCallback,
         model.modelSource
       );
+
       if (!paths?.[0]) {
         throw new RnExecutorchError(
           RnExecutorchErrorCode.DownloadInterrupted,

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

@@ -43,11 +43,16 @@ export abstract class VisionModule<TOutput> extends BaseModule {
    * const model = new ClassificationModule();
    * await model.load({ modelSource: MODEL });
    *
+   * // Use the functional form of setState to store the worklet — passing it
+   * // directly would cause React to invoke it immediately as an updater fn.
+   * const [runOnFrame, setRunOnFrame] = useState(null);
+   * setRunOnFrame(() => model.runOnFrame);
+   *
    * const frameOutput = useFrameOutput({
    *   onFrame(frame) {
    *     'worklet';
-   *     if (!model.runOnFrame) return;
-   *     const result = model.runOnFrame(frame);
+   *     if (!runOnFrame) return;
+   *     const result = runOnFrame(frame);
    *     frame.dispose();
    *   }
    * });

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

@@ -179,9 +179,6 @@ export interface PixelData extends Omit<TensorPtr, 'dataPtr' | 'scalarType'> {
 
 /**
  * Frame data for vision model processing.
- * Supports two modes:
- * 1. ArrayBuffer mode (with memory copy) - Compatible with all platforms
- * 2. NativeBuffer mode (zero-copy) - Better performance with Vision Camera v5
  */
 export interface Frame {
   /**
@@ -194,7 +191,7 @@ export interface Frame {
   getNativeBuffer(): { pointer: bigint; release(): void };
 }
 
-/** *
+/**
  * A readonly record mapping string keys to numeric or string values.
  * Used to represent enum-like label maps for models.
  *

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

@@ -176,7 +176,7 @@ export interface ObjectDetectionType {
    * 1. **String path/URI**: File path, URL, or Base64-encoded string
    * 2. **PixelData**: Raw pixel data from image libraries (e.g., NitroImage)
    *
-   * **Note**: For VisionCamera frame processing, use `processFrame` instead.
+   * **Note**: For VisionCamera frame processing, use `runOnFrame` instead.
    *
    * @param input - Image source (string or PixelData object)
    * @param detectionThreshold - An optional number between 0 and 1 representing the minimum confidence score. Default is 0.5.