From 9793a2efc1d52de45c6a1561d8b49755ce4b05b8 Mon Sep 17 00:00:00 2001 From: jim800121chen Date: Thu, 16 Apr 2026 08:44:16 +0800 Subject: [PATCH] =?UTF-8?q?chore(local-tool):=20models.json=20=E5=8F=AA?= =?UTF-8?q?=E4=BF=9D=E7=95=99=E6=9C=89=E5=AF=A6=E9=AB=94=20.nef=20?= =?UTF-8?q?=E7=9A=84=207=20=E5=80=8B=E9=A0=90=E8=A8=AD=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 使用者要求：前端模型庫只保留有適配裝置的模型（KL520 4 個 + KL720 3 個）。 原本 models.json 有 15 筆： - 8 筆 ONNX framework 的 demo 模型（yolov5-face-detection / imagenet-classification / person-detection / vehicle-classification / hand-gesture-recognition / coco-object-detection / face-mask-detection / license-plate-detection）— 都沒有實體 .nef 檔，是 placeholder metadata - 7 筆 NEF framework 的實體模型（每個都有 filePath 指向 data/nef/） 現在只保留 7 筆實體模型： KL520（4 個）： - kl520-yolov5-detection (yolov5 no-upsample 640x640) - kl520-fcos-detection (fcos-drk53s 512x512) - kl520-ssd-face-detection (ssd_fd_lm 320x240) - kl520-tiny-yolov3 (tiny_yolo_v3 416x416) KL720（3 個）： - kl720-yolov5-detection (yolov5 no-upsample 640x640) - kl720-resnet18-classification (resnet18 224x224) - kl720-fcos-detection (fcos-drk53s 512x512) server/data/models.json 是 runtime 讀取，三平台（macOS/Windows/Linux） 共用同一份，改一次三平台全部生效。 驗證： - python3 json.load 解析正常，7 筆 entries - 每筆 filePath 指向的 .nef 實體檔都存在於 server/data/nef/{kl520,kl720}/ - 檔案大小：1-13 MB，合計 ~64 MB - macOS dmg 重 build 163MB OK - Bundle 內 Contents/Resources/data/models.json 更新為 7 筆 Co-Authored-By: Claude Opus 4.6 (1M context) --- local-tool/server/data/models.json | 177 ----------------------------- 1 file changed, 177 deletions(-) diff --git a/local-tool/server/data/models.json b/local-tool/server/data/models.json index 833f6f7..c957aec 100644 --- a/local-tool/server/data/models.json +++ b/local-tool/server/data/models.json @@ -1,181 +1,4 @@ [ - { - "id": "yolov5-face-detection", - "name": "YOLOv5 Face Detection", - "description": "Real-time face detection model based on YOLOv5 architecture, optimized for edge deployment on Kneron KL720. Detects faces with high accuracy in various lighting conditions.", - "thumbnail": "/images/models/yolov5-face.png", - "taskType": "object_detection", - "categories": ["face", "security", "people"], - "framework": "ONNX", - "inputSize": {"width": 640, "height": 640}, - "modelSize": 14200000, - "quantization": "INT8", - "accuracy": 0.92, - "latencyMs": 33, - "fps": 30, - "supportedHardware": ["KL720", "KL730"], - "labels": ["face"], - "version": "1.0.0", - "author": "Kneron", - "license": "Apache-2.0", - "createdAt": "2024-01-15T00:00:00Z", - "updatedAt": "2024-06-01T00:00:00Z" - }, - { - "id": "imagenet-classification", - "name": "ImageNet Classification (ResNet18)", - "description": "ResNet18-based image classification model trained on ImageNet. Supports 1000 object categories with efficient inference on KL520 edge devices.", - "thumbnail": "/images/models/imagenet-cls.png", - "taskType": "classification", - "categories": ["general", "image-classification"], - "framework": "ONNX", - "inputSize": {"width": 224, "height": 224}, - "modelSize": 12000000, - "quantization": "INT8", - "accuracy": 0.78, - "latencyMs": 15, - "fps": 60, - "supportedHardware": ["KL520", "KL720", "KL730"], - "labels": ["airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck"], - "filePath": "data/nef/kl520/kl520_20001_resnet18_w224h224.nef", - "version": "2.1.0", - "author": "Kneron", - "license": "MIT", - "createdAt": "2024-02-10T00:00:00Z", - "updatedAt": "2024-07-15T00:00:00Z" - }, - { - "id": "person-detection", - "name": "Person Detection", - "description": "Lightweight person detection model optimized for real-time surveillance and people counting. Low latency with high accuracy on person class.", - "thumbnail": "/images/models/person-det.png", - "taskType": "object_detection", - "categories": ["people", "security", "surveillance"], - "framework": "ONNX", - "inputSize": {"width": 416, "height": 416}, - "modelSize": 11800000, - "quantization": "INT8", - "accuracy": 0.89, - "latencyMs": 28, - "fps": 35, - "supportedHardware": ["KL720", "KL730"], - "labels": ["person"], - "version": "1.2.0", - "author": "Kneron", - "license": "Apache-2.0", - "createdAt": "2024-03-01T00:00:00Z", - "updatedAt": "2024-08-01T00:00:00Z" - }, - { - "id": "vehicle-classification", - "name": "Vehicle Classification", - "description": "Vehicle type classification model that identifies cars, trucks, buses, motorcycles, and bicycles. Ideal for traffic monitoring and smart parking.", - "thumbnail": "/images/models/vehicle-cls.png", - "taskType": "classification", - "categories": ["vehicle", "traffic", "transportation"], - "framework": "ONNX", - "inputSize": {"width": 224, "height": 224}, - "modelSize": 6200000, - "quantization": "INT8", - "accuracy": 0.85, - "latencyMs": 12, - "fps": 75, - "supportedHardware": ["KL520", "KL720", "KL730"], - "labels": ["car", "truck", "bus", "motorcycle", "bicycle"], - "version": "1.0.0", - "author": "Kneron", - "license": "MIT", - "createdAt": "2024-03-20T00:00:00Z", - "updatedAt": "2024-05-10T00:00:00Z" - }, - { - "id": "hand-gesture-recognition", - "name": "Hand Gesture Recognition", - "description": "Recognizes 10 common hand gestures in real-time. Suitable for touchless interfaces and gesture-based control systems.", - "thumbnail": "/images/models/hand-gesture.png", - "taskType": "classification", - "categories": ["gesture", "hand", "interaction"], - "framework": "ONNX", - "inputSize": {"width": 224, "height": 224}, - "modelSize": 5800000, - "quantization": "INT8", - "accuracy": 0.88, - "latencyMs": 18, - "fps": 50, - "supportedHardware": ["KL520", "KL720"], - "labels": ["thumbs_up", "thumbs_down", "open_palm", "fist", "peace", "ok", "pointing", "wave", "grab", "pinch"], - "version": "1.1.0", - "author": "Kneron", - "license": "Apache-2.0", - "createdAt": "2024-04-05T00:00:00Z", - "updatedAt": "2024-09-01T00:00:00Z" - }, - { - "id": "coco-object-detection", - "name": "COCO Object Detection", - "description": "General-purpose object detection model trained on COCO dataset. Detects 80 common object categories including people, animals, vehicles, and household items.", - "thumbnail": "/images/models/coco-det.png", - "taskType": "object_detection", - "categories": ["general", "multi-object", "coco"], - "framework": "ONNX", - "inputSize": {"width": 640, "height": 640}, - "modelSize": 23500000, - "quantization": "INT8", - "accuracy": 0.82, - "latencyMs": 45, - "fps": 22, - "supportedHardware": ["KL720", "KL730"], - "labels": ["person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow"], - "version": "3.0.0", - "author": "Kneron", - "license": "Apache-2.0", - "createdAt": "2024-01-01T00:00:00Z", - "updatedAt": "2024-10-01T00:00:00Z" - }, - { - "id": "face-mask-detection", - "name": "Face Mask Detection", - "description": "Detects whether a person is wearing a face mask, wearing it incorrectly, or not wearing one. Built for health compliance monitoring.", - "thumbnail": "/images/models/face-mask.png", - "taskType": "object_detection", - "categories": ["face", "health", "safety"], - "framework": "ONNX", - "inputSize": {"width": 320, "height": 320}, - "modelSize": 9800000, - "quantization": "INT8", - "accuracy": 0.91, - "latencyMs": 22, - "fps": 45, - "supportedHardware": ["KL720", "KL730"], - "labels": ["mask_on", "mask_off", "mask_incorrect"], - "version": "1.3.0", - "author": "Kneron", - "license": "MIT", - "createdAt": "2024-02-28T00:00:00Z", - "updatedAt": "2024-07-20T00:00:00Z" - }, - { - "id": "license-plate-detection", - "name": "License Plate Detection", - "description": "Detects and localizes license plates in images and video streams. Optimized for various plate formats and viewing angles.", - "thumbnail": "/images/models/license-plate.png", - "taskType": "object_detection", - "categories": ["vehicle", "traffic", "ocr"], - "framework": "ONNX", - "inputSize": {"width": 416, "height": 416}, - "modelSize": 12400000, - "quantization": "INT8", - "accuracy": 0.87, - "latencyMs": 30, - "fps": 33, - "supportedHardware": ["KL720", "KL730"], - "labels": ["license_plate"], - "version": "1.0.0", - "author": "Kneron", - "license": "Apache-2.0", - "createdAt": "2024-05-15T00:00:00Z", - "updatedAt": "2024-08-30T00:00:00Z" - }, { "id": "kl520-yolov5-detection", "name": "YOLOv5 Detection (KL520)",