chore(apps): destructure heavily-used \models\ groups for readability

Per Kuba's review on #1148 — hoist a camelCase alias for any group used
≥ 2 times in a file, e.g.

  const instanceSegmentation = models.instance_segmentation;
  const objectDetection = models.object_detection;

Then \`models.instance_segmentation.yolo26n_seg()\` becomes
\`instanceSegmentation.yolo26n_seg()\`. Applied to 14 files where it actually
reduces noise.

Skips aliasing when the camelCase name would shadow an existing local
identifier — common in the LLM/STT/embeddings screens where \`llm\`,
\`speechToText\`, \`imageEmbedding\` etc. already name hook return values
or temporaries.

Author: msluszniak

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

@@ -6,15 +6,16 @@ import {
   ClassificationModelSources,
 } from 'react-native-executorch';
 import { ModelPicker, ModelOption } from '../../components/ModelPicker';
+const classification = models.classification;
 
 const MODELS: ModelOption<ClassificationModelSources>[] = [
   {
     label: 'EfficientNet V2 S Quantized',
-    value: models.classification.efficientnet_v2_s(),
+    value: classification.efficientnet_v2_s(),
   },
   {
     label: 'EfficientNet V2 S',
-    value: models.classification.efficientnet_v2_s({ quant: false }),
+    value: classification.efficientnet_v2_s({ quant: false }),
   },
 ];
 import { View, StyleSheet, Image, Text, ScrollView } from 'react-native';
@@ -27,9 +28,7 @@ import ErrorBanner from '../../components/ErrorBanner';
 
 export default function ClassificationScreen() {
   const [selectedModel, setSelectedModel] =
-    useState<ClassificationModelSources>(
-      models.classification.efficientnet_v2_s()
-    );
+    useState<ClassificationModelSources>(classification.efficientnet_v2_s());
   const [results, setResults] = useState<{ label: string; score: number }[]>(
     []
   );

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

@@ -22,25 +22,27 @@ import ImageWithMasks, {
   DisplayInstance,
 } from '../../components/ImageWithMasks';
 import { StatsBar } from '../../components/StatsBar';
+const instanceSegmentation = models.instance_segmentation;
+const objectDetection = models.object_detection;
 
 const MODELS: ModelOption<InstanceSegmentationModelSources>[] = [
-  { label: 'Yolo26N', value: models.instance_segmentation.yolo26n_seg() },
-  { label: 'Yolo26S', value: models.instance_segmentation.yolo26s_seg() },
-  { label: 'Yolo26M', value: models.instance_segmentation.yolo26m_seg() },
-  { label: 'Yolo26L', value: models.instance_segmentation.yolo26l_seg() },
-  { label: 'Yolo26X', value: models.instance_segmentation.yolo26x_seg() },
+  { label: 'Yolo26N', value: instanceSegmentation.yolo26n_seg() },
+  { label: 'Yolo26S', value: instanceSegmentation.yolo26s_seg() },
+  { label: 'Yolo26M', value: instanceSegmentation.yolo26m_seg() },
+  { label: 'Yolo26L', value: instanceSegmentation.yolo26l_seg() },
+  { label: 'Yolo26X', value: instanceSegmentation.yolo26x_seg() },
   {
     label: 'RF-DeTR Nano',
-    value: models.instance_segmentation.rf_detr_nano_seg(),
+    value: instanceSegmentation.rf_detr_nano_seg(),
   },
-  { label: 'FastSAM-S', value: models.object_detection.fastsam_s() },
-  { label: 'FastSAM-X', value: models.object_detection.fastsam_x() },
+  { label: 'FastSAM-S', value: objectDetection.fastsam_s() },
+  { label: 'FastSAM-X', value: objectDetection.fastsam_x() },
 ];
 
 export default function InstanceSegmentationScreen() {
   const [selectedModel, setSelectedModel] =
     useState<InstanceSegmentationModelSources>(
-      models.instance_segmentation.yolo26n_seg()
+      instanceSegmentation.yolo26n_seg()
     );
   const [inferenceTime, setInferenceTime] = useState<number | null>(null);
 

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

@@ -14,21 +14,22 @@ import React, { useContext, useEffect, useState } from 'react';
 import { GeneratingContext } from '../../context';
 import ScreenWrapper from '../../ScreenWrapper';
 import { StatsBar } from '../../components/StatsBar';
+const objectDetection = models.object_detection;
 
 const MODELS: ModelOption<ObjectDetectionModelSources>[] = [
   {
     label: 'RF-DeTR Nano',
-    value: models.object_detection.rf_detr_nano(),
+    value: objectDetection.rf_detr_nano(),
   },
   {
     label: 'SSDLite MobileNet',
-    value: models.object_detection.ssdlite_320_mobilenet_v3_large(),
+    value: objectDetection.ssdlite_320_mobilenet_v3_large(),
   },
-  { label: 'YOLO26N', value: models.object_detection.yolo26n() },
-  { label: 'YOLO26S', value: models.object_detection.yolo26s() },
-  { label: 'YOLO26M', value: models.object_detection.yolo26m() },
-  { label: 'YOLO26L', value: models.object_detection.yolo26l() },
-  { label: 'YOLO26X', value: models.object_detection.yolo26x() },
+  { label: 'YOLO26N', value: objectDetection.yolo26n() },
+  { label: 'YOLO26S', value: objectDetection.yolo26s() },
+  { label: 'YOLO26M', value: objectDetection.yolo26m() },
+  { label: 'YOLO26L', value: objectDetection.yolo26l() },
+  { label: 'YOLO26X', value: objectDetection.yolo26x() },
 ];
 import ErrorBanner from '../../components/ErrorBanner';
 
@@ -41,9 +42,7 @@ export default function ObjectDetectionScreen() {
     height: number;
   }>();
   const [selectedModel, setSelectedModel] =
-    useState<ObjectDetectionModelSources>(
-      models.object_detection.rf_detr_nano()
-    );
+    useState<ObjectDetectionModelSources>(objectDetection.rf_detr_nano());
   const [inferenceTime, setInferenceTime] = useState<number | null>(null);
 
   const model = useObjectDetection({ model: selectedModel });

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

@@ -45,21 +45,20 @@ import ImageWithMasks, {
 } from '../../components/ImageWithMasks';
 import { getImage } from '../../utils';
 import ColorPalette from '../../colors';
+const objectDetection = models.object_detection;
 
 type PromptMode = 'point' | 'box' | 'text';
 
 const MODELS: ModelOption<InstanceSegmentationModelSources>[] = [
-  { label: 'FastSAM-S', value: models.object_detection.fastsam_s() },
-  { label: 'FastSAM-X', value: models.object_detection.fastsam_x() },
+  { label: 'FastSAM-S', value: objectDetection.fastsam_s() },
+  { label: 'FastSAM-X', value: objectDetection.fastsam_x() },
 ];
 
 export default function SegmentAnythingScreen() {
   const { setGlobalGenerating } = useContext(GeneratingContext);
 
   const [selectedModel, setSelectedModel] =
-    useState<InstanceSegmentationModelSources>(
-      models.object_detection.fastsam_s()
-    );
+    useState<InstanceSegmentationModelSources>(objectDetection.fastsam_s());
   const [mode, setMode] = useState<PromptMode>('point');
   const [inferenceTime, setInferenceTime] = useState<number | null>(null);
 

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

@@ -21,6 +21,7 @@ import { GeneratingContext } from '../../context';
 import ScreenWrapper from '../../ScreenWrapper';
 import { StatsBar } from '../../components/StatsBar';
 import ErrorBanner from '../../components/ErrorBanner';
+const semanticSegmentation = models.semantic_segmentation;
 
 const numberToColor: number[][] = [
   [255, 87, 51], // 0 Red
@@ -49,39 +50,39 @@ const numberToColor: number[][] = [
 const MODELS: ModelOption<SemanticSegmentationModelSources>[] = [
   {
     label: 'DeepLab MobileNet',
-    value: models.semantic_segmentation.deeplab_v3_mobilenet_v3_large(),
+    value: semanticSegmentation.deeplab_v3_mobilenet_v3_large(),
   },
   {
     label: 'DeepLab ResNet50',
-    value: models.semantic_segmentation.deeplab_v3_resnet50(),
+    value: semanticSegmentation.deeplab_v3_resnet50(),
   },
   {
     label: 'DeepLab ResNet101',
-    value: models.semantic_segmentation.deeplab_v3_resnet101(),
+    value: semanticSegmentation.deeplab_v3_resnet101(),
   },
   {
     label: 'LRASPP MobileNet',
-    value: models.semantic_segmentation.lraspp_mobilenet_v3_large(),
+    value: semanticSegmentation.lraspp_mobilenet_v3_large(),
   },
   {
     label: 'FCN ResNet50',
-    value: models.semantic_segmentation.fcn_resnet50(),
+    value: semanticSegmentation.fcn_resnet50(),
   },
   {
     label: 'FCN ResNet101',
-    value: models.semantic_segmentation.fcn_resnet101(),
+    value: semanticSegmentation.fcn_resnet101(),
   },
   {
     label: 'Selfie Segmentation',
-    value: models.semantic_segmentation.selfie_segmentation(),
+    value: semanticSegmentation.selfie_segmentation(),
   },
 ];
 
 export default function SemanticSegmentationScreen() {
   const { setGlobalGenerating } = useContext(GeneratingContext);
   const [selectedModel, setSelectedModel] =
     useState<SemanticSegmentationModelSources>(
-      models.semantic_segmentation.deeplab_v3_mobilenet_v3_large()
+      semanticSegmentation.deeplab_v3_mobilenet_v3_large()
     );
 
   const {

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

@@ -15,26 +15,27 @@ import React, { useContext, useEffect, useState } from 'react';
 import { GeneratingContext } from '../../context';
 import ScreenWrapper from '../../ScreenWrapper';
 import { StatsBar } from '../../components/StatsBar';
+const styleTransfer = models.style_transfer;
 
 type StyleTransferModelSources = {
   modelName: StyleTransferModelName;
   modelSource: ResourceSource;
 };
 
 const MODELS: ModelOption<StyleTransferModelSources>[] = [
-  { label: 'Candy', value: models.style_transfer.candy() },
-  { label: 'Mosaic', value: models.style_transfer.mosaic() },
+  { label: 'Candy', value: styleTransfer.candy() },
+  { label: 'Mosaic', value: styleTransfer.mosaic() },
   {
     label: 'Rain Princess',
-    value: models.style_transfer.rain_princess(),
+    value: styleTransfer.rain_princess(),
   },
-  { label: 'Udnie', value: models.style_transfer.udnie() },
+  { label: 'Udnie', value: styleTransfer.udnie() },
 ];
 import ErrorBanner from '../../components/ErrorBanner';
 
 export default function StyleTransferScreen() {
   const [selectedModel, setSelectedModel] = useState<StyleTransferModelSources>(
-    models.style_transfer.candy()
+    styleTransfer.candy()
   );
 
   const model = useStyleTransfer({ model: selectedModel });

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

@@ -25,17 +25,18 @@ import ProgressBar from '../../components/ProgressBar';
 import { Ionicons } from '@expo/vector-icons';
 import { StatsBar } from '../../components/StatsBar';
 import ErrorBanner from '../../components/ErrorBanner';
+const imageGeneration = models.image_generation;
 
 type TextToImageModelSources = TextToImageProps['model'];
 
 const MODELS: ModelOption<TextToImageModelSources>[] = [
   {
     label: 'BK-SDM 256',
-    value: models.image_generation.bk_sdm_tiny_vpred_256(),
+    value: imageGeneration.bk_sdm_tiny_vpred_256(),
   },
   {
     label: 'BK-SDM 512',
-    value: models.image_generation.bk_sdm_tiny_vpred_512(),
+    value: imageGeneration.bk_sdm_tiny_vpred_512(),
   },
 ];
 
@@ -47,7 +48,7 @@ export default function TextToImageScreen() {
 
   const [input, setInput] = useState('');
   const [selectedModel, setSelectedModel] = useState<TextToImageModelSources>(
-    models.image_generation.bk_sdm_tiny_vpred_256()
+    imageGeneration.bk_sdm_tiny_vpred_256()
   );
   const [generationTime, setGenerationTime] = useState<number | null>(null);
 

apps/computer-vision/components/vision_camera/tasks/InstanceSegmentationTask.tsx

@@ -17,6 +17,8 @@ import {
   buildDisplayInstances,
   DisplayInstance,
 } from '../../../components/ImageWithMasks';
+const instanceSegmentation = models.instance_segmentation;
+const objectDetection = models.object_detection;
 
 type InstSegModelId =
   | 'instanceSegmentationYolo26n'
@@ -39,19 +41,19 @@ export default function InstanceSegmentationTask({
   onErrorChange,
 }: Props) {
   const yolo26n = useInstanceSegmentation({
-    model: models.instance_segmentation.yolo26n_seg(),
+    model: instanceSegmentation.yolo26n_seg(),
     preventLoad: activeModel !== 'instanceSegmentationYolo26n',
   });
   const rfdetr = useInstanceSegmentation({
-    model: models.instance_segmentation.rf_detr_nano_seg(),
+    model: instanceSegmentation.rf_detr_nano_seg(),
     preventLoad: activeModel !== 'instanceSegmentationRfdetr',
   });
   const fastsamS = useInstanceSegmentation({
-    model: models.object_detection.fastsam_s(),
+    model: objectDetection.fastsam_s(),
     preventLoad: activeModel !== 'instanceSegmentationFastsamS',
   });
   const fastsamX = useInstanceSegmentation({
-    model: models.object_detection.fastsam_x(),
+    model: objectDetection.fastsam_x(),
     preventLoad: activeModel !== 'instanceSegmentationFastsamX',
   });
 

apps/computer-vision/components/vision_camera/tasks/ObjectDetectionTask.tsx

@@ -11,6 +11,7 @@ import {
 } from 'react-native-executorch';
 import BoundingBoxes from '../../BoundingBoxes';
 import { FRAME_TARGET_RESOLUTION, TaskProps } from './types';
+const objectDetection = models.object_detection;
 
 type ObjModelId =
   | 'objectDetectionSsdlite'
@@ -32,15 +33,15 @@ export default function ObjectDetectionTask({
   onErrorChange,
 }: Props) {
   const ssdlite = useObjectDetection({
-    model: models.object_detection.ssdlite_320_mobilenet_v3_large(),
+    model: objectDetection.ssdlite_320_mobilenet_v3_large(),
     preventLoad: activeModel !== 'objectDetectionSsdlite',
   });
   const rfdetr = useObjectDetection({
-    model: models.object_detection.rf_detr_nano(),
+    model: objectDetection.rf_detr_nano(),
     preventLoad: activeModel !== 'objectDetectionRfdetr',
   });
   const yolo26n = useObjectDetection({
-    model: models.object_detection.yolo26n(),
+    model: objectDetection.yolo26n(),
     preventLoad: activeModel !== 'objectDetectionYolo26n',
   });
 

apps/computer-vision/components/vision_camera/tasks/SegmentationTask.tsx

@@ -13,6 +13,7 @@ import {
 } from '@shopify/react-native-skia';
 import { CLASS_COLORS } from '../../utils/colors';
 import { FRAME_TARGET_RESOLUTION, TaskProps } from './types';
+const semanticSegmentation = models.semantic_segmentation;
 
 type SegModelId =
   | 'segmentationDeeplabResnet50'
@@ -38,31 +39,31 @@ export default function SegmentationTask({
   onErrorChange,
 }: Props) {
   const segDeeplabResnet50 = useSemanticSegmentation({
-    model: models.semantic_segmentation.deeplab_v3_resnet50(),
+    model: semanticSegmentation.deeplab_v3_resnet50(),
     preventLoad: activeModel !== 'segmentationDeeplabResnet50',
   });
   const segDeeplabResnet101 = useSemanticSegmentation({
-    model: models.semantic_segmentation.deeplab_v3_resnet101(),
+    model: semanticSegmentation.deeplab_v3_resnet101(),
     preventLoad: activeModel !== 'segmentationDeeplabResnet101',
   });
   const segDeeplabMobilenet = useSemanticSegmentation({
-    model: models.semantic_segmentation.deeplab_v3_mobilenet_v3_large(),
+    model: semanticSegmentation.deeplab_v3_mobilenet_v3_large(),
     preventLoad: activeModel !== 'segmentationDeeplabMobilenet',
   });
   const segLraspp = useSemanticSegmentation({
-    model: models.semantic_segmentation.lraspp_mobilenet_v3_large(),
+    model: semanticSegmentation.lraspp_mobilenet_v3_large(),
     preventLoad: activeModel !== 'segmentationLraspp',
   });
   const segFcnResnet50 = useSemanticSegmentation({
-    model: models.semantic_segmentation.fcn_resnet50(),
+    model: semanticSegmentation.fcn_resnet50(),
     preventLoad: activeModel !== 'segmentationFcnResnet50',
   });
   const segFcnResnet101 = useSemanticSegmentation({
-    model: models.semantic_segmentation.fcn_resnet101(),
+    model: semanticSegmentation.fcn_resnet101(),
     preventLoad: activeModel !== 'segmentationFcnResnet101',
   });
   const segSelfie = useSemanticSegmentation({
-    model: models.semantic_segmentation.selfie_segmentation(),
+    model: semanticSegmentation.selfie_segmentation(),
     preventLoad: activeModel !== 'segmentationSelfie',
   });