安裝包從 8 個 .nef 縮減為 2 個,models.json 保留完整定義以便日後 加回。 - Makefile 加 BUNDLED_NEFS 白名單,三平台共用 copy_bundled_data helper;用 POSIX find/cp 而非 rsync(Windows CI 的 Git Bash 沒有 rsync) - 白名單檔案不存在時 build 直接失敗,並在複製後驗證 models.json 存在且 .nef 數量相符 —— 避免產出「安裝後 0 個模型」卻回報成功 - FCOS Detection (KL520) 改名為「物件辨識」 - Tiny YOLOv3 (KL520) 改名為「人型監測」 (只改 name/description,id 不動以免影響既有設定與紀錄) - Repository 啟動時過濾 .nef 不存在的模型,否則使用者會看到未打包 的模型並在選取後拿到莫名錯誤 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
267 lines
6.6 KiB
JSON
267 lines
6.6 KiB
JSON
[
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{
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"id": "kl520-yolov5-detection",
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"name": "YOLOv5 Detection (KL520)",
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"description": "YOLOv5 object detection model compiled for Kneron KL520. No upsample variant optimized for NPU inference at 640x640 resolution.",
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"thumbnail": "/images/models/yolov5-det.png",
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"taskType": "object_detection",
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"categories": [
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"general",
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"multi-object"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 640,
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"height": 640
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},
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"modelSize": 7200000,
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"quantization": "INT8",
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"supportedHardware": [
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"KL520"
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],
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"labels": [
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"person",
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"bicycle",
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"car",
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"motorcycle",
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"airplane",
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"bus",
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"train",
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"truck",
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"boat",
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"traffic light"
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],
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"filePath": "data/nef/kl520/kl520_20005_yolov5-noupsample_w640h640.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "Apache-2.0",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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},
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{
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"id": "kl520-fcos-detection",
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"name": "物件辨識",
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"description": "通用物件偵測模型,可辨識人、車輛、動物等常見物件,適合一般場景的多物件偵測。",
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"thumbnail": "/images/models/fcos-det.png",
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"taskType": "object_detection",
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"categories": [
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"general",
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"multi-object"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 512,
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"height": 512
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},
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"modelSize": 8900000,
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"quantization": "INT8",
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"supportedHardware": [
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"KL520"
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],
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"labels": [
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"person",
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"bicycle",
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"car",
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"motorcycle",
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"airplane",
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"bus",
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"train",
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"truck",
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"boat",
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"traffic light"
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],
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"filePath": "data/nef/kl520/kl520_20004_fcos-drk53s_w512h512.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "Apache-2.0",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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},
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{
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"id": "kl520-ssd-face-detection",
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"name": "SSD Face Detection (KL520)",
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"description": "SSD-based face detection with landmark localization, compiled for KL520. Lightweight model suitable for face detection and alignment tasks.",
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"thumbnail": "/images/models/ssd-face.png",
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"taskType": "object_detection",
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"categories": [
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"face",
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"security"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 320,
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"height": 240
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},
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"modelSize": 1000000,
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"quantization": "INT8",
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"supportedHardware": [
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"KL520"
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],
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"labels": [
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"face"
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],
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"filePath": "data/nef/kl520/kl520_ssd_fd_lm.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "Apache-2.0",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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},
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{
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"id": "kl520-tiny-yolov3",
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"name": "人型監測",
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"description": "輕量快速的人員偵測模型,適合即時監控場景,可在邊緣裝置上高速偵測畫面中的人員。",
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"thumbnail": "/images/models/tiny-yolov3.png",
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"taskType": "object_detection",
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"categories": [
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"general",
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"multi-object"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 416,
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"height": 416
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},
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"modelSize": 9400000,
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"quantization": "INT8",
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"supportedHardware": [
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"KL520"
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],
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"labels": [
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"person",
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"bicycle",
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"car",
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"motorcycle",
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"airplane",
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"bus",
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"train",
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"truck",
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"boat",
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"traffic light"
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],
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"filePath": "data/nef/kl520/kl520_tiny_yolo_v3.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "Apache-2.0",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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},
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{
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"id": "kl720-yolov5-detection",
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"name": "YOLOv5 Detection (KL720)",
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"description": "YOLOv5 object detection model compiled for Kneron KL720. No upsample variant optimized for KL720 NPU inference at 640x640 resolution with USB 3.0 throughput.",
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"thumbnail": "/images/models/yolov5-det.png",
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"taskType": "object_detection",
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"categories": [
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"general",
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"multi-object"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 640,
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"height": 640
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},
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"modelSize": 10168348,
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"quantization": "INT8",
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"supportedHardware": [
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"KL720"
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],
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"labels": [
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"person",
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"bicycle",
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"car",
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"motorcycle",
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"airplane",
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"bus",
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"train",
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"truck",
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"boat",
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"traffic light"
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],
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"filePath": "data/nef/kl720/kl720_20005_yolov5-noupsample_w640h640.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "Apache-2.0",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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},
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{
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"id": "kl720-resnet18-classification",
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"name": "ImageNet Classification ResNet18 (KL720)",
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"description": "ResNet18-based image classification compiled for KL720. Supports 1000 ImageNet categories with fast inference via USB 3.0.",
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"thumbnail": "/images/models/imagenet-cls.png",
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"taskType": "classification",
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"categories": [
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"general",
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"image-classification"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 224,
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"height": 224
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},
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"modelSize": 12826804,
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"quantization": "INT8",
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"supportedHardware": [
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"KL720"
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],
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"labels": [
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"airplane",
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"automobile",
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"bird",
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"cat",
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"deer",
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"dog",
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"frog",
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"horse",
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"ship",
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"truck"
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],
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"filePath": "data/nef/kl720/kl720_20001_resnet18_w224h224.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "MIT",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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},
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{
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"id": "kl720-fcos-detection",
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"name": "FCOS Detection (KL720)",
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"description": "FCOS (Fully Convolutional One-Stage) object detection with DarkNet53s backbone, compiled for KL720. Anchor-free detection at 512x512.",
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"thumbnail": "/images/models/fcos-det.png",
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"taskType": "object_detection",
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"categories": [
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"general",
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"multi-object"
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],
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"framework": "NEF",
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"inputSize": {
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"width": 512,
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"height": 512
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},
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"modelSize": 13004640,
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"quantization": "INT8",
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"supportedHardware": [
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"KL720"
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],
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"labels": [
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"person",
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"bicycle",
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"car",
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"motorcycle",
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"airplane",
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"bus",
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"train",
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"truck",
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"boat",
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"traffic light"
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],
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"filePath": "data/nef/kl720/kl720_20004_fcos-drk53s_w512h512.nef",
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"version": "1.0.0",
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"author": "Kneron",
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"license": "Apache-2.0",
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"createdAt": "2024-01-01T00:00:00Z",
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"updatedAt": "2024-01-01T00:00:00Z"
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}
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]
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