Add tested Rockchip RKOPT FP16 and INT8 detectors (Toolkit 2.3.2)

.gitattributes

@@ -61,3 +61,15 @@ models/obb/yolov8s-obb/rk3588/fp16/model.rknn filter=lfs diff=lfs merge=lfs -tex
 models/obb/yolov8s-obb/rk3588/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
 models/pose/yolov8s-pose/rk3588/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
 models/pose/yolov8s-pose/rk3588/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8m/rk3576/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8m/rk3576/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8m/rk3588/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8m/rk3588/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8n/rk3576/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8n/rk3576/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8n/rk3588/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8n/rk3588/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8s/rk3576/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8s/rk3576/int8/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8s/rk3588/fp16/model.rknn filter=lfs diff=lfs merge=lfs -text
+models/detect/yolov8s/rk3588/int8/model.rknn filter=lfs diff=lfs merge=lfs -text

README.md

@@ -13,10 +13,15 @@ tags:
 Rockchip-guided and custom YOLO exports for RK3576 and RK3588.
 Converted with RKNN Toolkit2 2.3.2.
 
-Available tasks: classify, obb, pose.
+Available tasks: detect, classify, obb, pose.
 
 Download `model.rknn` and `metadata.yaml` from the same folder under `models/<task>/<variant>/<chip>/<precision>/`.
 
 The manifest records model and metadata checksums. Original checkpoints, conversion scripts, and their provenance are in `source/`.
 
 The models and checkpoints are distributed under AGPL-3.0. See `LICENSE` and `source/weights.json`.
+
+Detection includes the n, s, and m sizes in FP16 and INT8 for both chips.
+The checkpoints were exported with Rockchip's RKOPT detector head and
+compiled with the Model Zoo converter. The exact checkpoint URLs, exporter
+commits, scripts, and ONNX graphs are under `source/`.

manifest.json

@@ -350,5 +350,197 @@
     "onnx_sha256": "9331aa2e49adefb04f88eec55360e3a5cfed082c3a138f336e81494c26a8a663",
     "metadata_sha256": "a5baf2163963cfb9d221b5fd248b43d504c3f816b91e6375a21b9d4fc4ae471b",
     "conversion": "rockchip-guided"
+  },
+  {
+    "name": "yolov8m",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3576",
+    "precision": "fp16",
+    "path": "models/detect/yolov8m/rk3576/fp16",
+    "sha256": "66650ced5c0fefa87c89e6e9c7b0a43d4b808a34d215dad5eb872ff4a82d8ce0",
+    "metadata_sha256": "794322a84d2a3c8e00957284acd9cedc84a74ffbcc962e152f6529f9d2c1cc86",
+    "source_onnx": "source/onnx/yolov8m.onnx",
+    "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+    "weights": "source/weights/yolov8m.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8m",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3576",
+    "precision": "int8",
+    "path": "models/detect/yolov8m/rk3576/int8",
+    "sha256": "71f5574f03aa58dd0ede450c5713b8676e1777d49f2ba2c6dc73c16ae3b60118",
+    "metadata_sha256": "794322a84d2a3c8e00957284acd9cedc84a74ffbcc962e152f6529f9d2c1cc86",
+    "source_onnx": "source/onnx/yolov8m.onnx",
+    "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+    "weights": "source/weights/yolov8m.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8n",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3576",
+    "precision": "fp16",
+    "path": "models/detect/yolov8n/rk3576/fp16",
+    "sha256": "fe19393941429eb24ed40d3961f0d497d0c178e5e2ed670f3bde11fc137615ea",
+    "metadata_sha256": "794322a84d2a3c8e00957284acd9cedc84a74ffbcc962e152f6529f9d2c1cc86",
+    "source_onnx": "source/onnx/yolov8n.onnx",
+    "onnx_sha256": "7feb33de8924ec21346fc60c16c5a85bfbe128efdd3d65b45a8dfe3691ddc244",
+    "weights": "source/weights/yolov8n.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8n.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8n",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3576",
+    "precision": "int8",
+    "path": "models/detect/yolov8n/rk3576/int8",
+    "sha256": "0976df062fbf15d8cec0214b0d817ac46164a2048f268cdf7cabe81173e785bd",
+    "metadata_sha256": "794322a84d2a3c8e00957284acd9cedc84a74ffbcc962e152f6529f9d2c1cc86",
+    "source_onnx": "source/onnx/yolov8n.onnx",
+    "onnx_sha256": "7feb33de8924ec21346fc60c16c5a85bfbe128efdd3d65b45a8dfe3691ddc244",
+    "weights": "source/weights/yolov8n.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8n.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8s",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3576",
+    "precision": "fp16",
+    "path": "models/detect/yolov8s/rk3576/fp16",
+    "sha256": "5929453f335f22f3f9744c3500f41cb210797998e1748730d76a43af6a42f7db",
+    "metadata_sha256": "794322a84d2a3c8e00957284acd9cedc84a74ffbcc962e152f6529f9d2c1cc86",
+    "source_onnx": "source/onnx/yolov8s.onnx",
+    "onnx_sha256": "e3cb174a72bd791640f8ccfad79c681519079c07b190ed42740f744f20ddd49f",
+    "weights": "source/weights/yolov8s.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8s.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8s",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3576",
+    "precision": "int8",
+    "path": "models/detect/yolov8s/rk3576/int8",
+    "sha256": "9d22ad44ab042daf1d7a92a9a144be8493e994b535091835e6e6516223c8718d",
+    "metadata_sha256": "794322a84d2a3c8e00957284acd9cedc84a74ffbcc962e152f6529f9d2c1cc86",
+    "source_onnx": "source/onnx/yolov8s.onnx",
+    "onnx_sha256": "e3cb174a72bd791640f8ccfad79c681519079c07b190ed42740f744f20ddd49f",
+    "weights": "source/weights/yolov8s.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8s.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8m",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3588",
+    "precision": "fp16",
+    "path": "models/detect/yolov8m/rk3588/fp16",
+    "sha256": "a164a9e5748d9ead9cb608f2136c83212b2f24ffaa9cdb06ed713c8e4d1b689b",
+    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5",
+    "source_onnx": "source/onnx/yolov8m.onnx",
+    "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+    "weights": "source/weights/yolov8m.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8m",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3588",
+    "precision": "int8",
+    "path": "models/detect/yolov8m/rk3588/int8",
+    "sha256": "4bd91e9d41a1c0efe3ef70efbb7865098b09bf317da29f3563feb8ed2a0d44b0",
+    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5",
+    "source_onnx": "source/onnx/yolov8m.onnx",
+    "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+    "weights": "source/weights/yolov8m.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8n",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3588",
+    "precision": "fp16",
+    "path": "models/detect/yolov8n/rk3588/fp16",
+    "sha256": "4b99521c1be89922c53985a7c7c6ae63ead00c84b200f9c79648076598c80657",
+    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5",
+    "source_onnx": "source/onnx/yolov8n.onnx",
+    "onnx_sha256": "7feb33de8924ec21346fc60c16c5a85bfbe128efdd3d65b45a8dfe3691ddc244",
+    "weights": "source/weights/yolov8n.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8n.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8n",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3588",
+    "precision": "int8",
+    "path": "models/detect/yolov8n/rk3588/int8",
+    "sha256": "71fa540a07d5cb48fa4f69d0c0386d7ab485be5be3d6fedd5c04fe62ca78ed76",
+    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5",
+    "source_onnx": "source/onnx/yolov8n.onnx",
+    "onnx_sha256": "7feb33de8924ec21346fc60c16c5a85bfbe128efdd3d65b45a8dfe3691ddc244",
+    "weights": "source/weights/yolov8n.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8n.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8s",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3588",
+    "precision": "fp16",
+    "path": "models/detect/yolov8s/rk3588/fp16",
+    "sha256": "26ea5993256b387ee18af406a60b68666ed92b32d3b2a9181cff386eddf50d58",
+    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5",
+    "source_onnx": "source/onnx/yolov8s.onnx",
+    "onnx_sha256": "e3cb174a72bd791640f8ccfad79c681519079c07b190ed42740f744f20ddd49f",
+    "weights": "source/weights/yolov8s.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8s.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
+  },
+  {
+    "name": "yolov8s",
+    "family": "yolov8",
+    "task": "detect",
+    "chip": "rk3588",
+    "precision": "int8",
+    "path": "models/detect/yolov8s/rk3588/int8",
+    "sha256": "2151ccd261ebc33a3538a6f03327c3f883c68ad83649394118849b41969d3179",
+    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5",
+    "source_onnx": "source/onnx/yolov8s.onnx",
+    "onnx_sha256": "e3cb174a72bd791640f8ccfad79c681519079c07b190ed42740f744f20ddd49f",
+    "weights": "source/weights/yolov8s.pt",
+    "source_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8s.pt",
+    "toolkit_version": "2.3.2",
+    "conversion": "rockchip-rkopt"
   }
 ]

models/detect/yolov8m/rk3576/fp16/conversion.json

@@ -0,0 +1,11 @@
+{
+  "compiler_version": "2.3.2",
+  "model_zoo_commit": "837db8e992815ff8647eadb709f07067f4bc3a71",
+  "rockchip_exporter": "https://github.com/airockchip/ultralytics_yolov8/tree/4674fe6e003dfbc5f2250d3b39dd31faaf7a9877",
+  "checkpoint_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+  "checkpoint_sha256": "5d4a90cdc7a21786cc59cd19778e9eafff836df9e2da32524737c7ee6efe4fe5",
+  "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+  "rknn_sha256": "66650ced5c0fefa87c89e6e9c7b0a43d4b808a34d215dad5eb872ff4a82d8ce0",
+  "chip": "rk3576",
+  "precision": "fp"
+}

models/detect/yolov8m/rk3576/fp16/metadata.yaml

@@ -0,0 +1,89 @@
+task: detect
+batch: 1
+channels: 3
+imgsz:
+- 640
+- 640
+names:
+- person
+- bicycle
+- car
+- motorcycle
+- airplane
+- bus
+- train
+- truck
+- boat
+- traffic light
+- fire hydrant
+- stop sign
+- parking meter
+- bench
+- bird
+- cat
+- dog
+- horse
+- sheep
+- cow
+- elephant
+- bear
+- zebra
+- giraffe
+- backpack
+- umbrella
+- handbag
+- tie
+- suitcase
+- frisbee
+- skis
+- snowboard
+- sports ball
+- kite
+- baseball bat
+- baseball glove
+- skateboard
+- surfboard
+- tennis racket
+- bottle
+- wine glass
+- cup
+- fork
+- knife
+- spoon
+- bowl
+- banana
+- apple
+- sandwich
+- orange
+- broccoli
+- carrot
+- hot dog
+- pizza
+- donut
+- cake
+- chair
+- couch
+- potted plant
+- bed
+- dining table
+- toilet
+- tv
+- laptop
+- mouse
+- remote
+- keyboard
+- cell phone
+- microwave
+- oven
+- toaster
+- sink
+- refrigerator
+- book
+- clock
+- vase
+- scissors
+- teddy bear
+- hair drier
+- toothbrush
+target_platform: rk3576
+coordinates: pixels

models/detect/yolov8m/rk3576/fp16/model.rknn

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+version https://git-lfs.github.com/spec/v1
+oid sha256:66650ced5c0fefa87c89e6e9c7b0a43d4b808a34d215dad5eb872ff4a82d8ce0
+size 57194057

models/detect/yolov8m/rk3576/int8/conversion.json

@@ -0,0 +1,11 @@
+{
+  "compiler_version": "2.3.2",
+  "model_zoo_commit": "837db8e992815ff8647eadb709f07067f4bc3a71",
+  "rockchip_exporter": "https://github.com/airockchip/ultralytics_yolov8/tree/4674fe6e003dfbc5f2250d3b39dd31faaf7a9877",
+  "checkpoint_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+  "checkpoint_sha256": "5d4a90cdc7a21786cc59cd19778e9eafff836df9e2da32524737c7ee6efe4fe5",
+  "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+  "rknn_sha256": "71f5574f03aa58dd0ede450c5713b8676e1777d49f2ba2c6dc73c16ae3b60118",
+  "chip": "rk3576",
+  "precision": "i8"
+}

models/detect/yolov8m/rk3576/int8/metadata.yaml

@@ -0,0 +1,89 @@
+task: detect
+batch: 1
+channels: 3
+imgsz:
+- 640
+- 640
+names:
+- person
+- bicycle
+- car
+- motorcycle
+- airplane
+- bus
+- train
+- truck
+- boat
+- traffic light
+- fire hydrant
+- stop sign
+- parking meter
+- bench
+- bird
+- cat
+- dog
+- horse
+- sheep
+- cow
+- elephant
+- bear
+- zebra
+- giraffe
+- backpack
+- umbrella
+- handbag
+- tie
+- suitcase
+- frisbee
+- skis
+- snowboard
+- sports ball
+- kite
+- baseball bat
+- baseball glove
+- skateboard
+- surfboard
+- tennis racket
+- bottle
+- wine glass
+- cup
+- fork
+- knife
+- spoon
+- bowl
+- banana
+- apple
+- sandwich
+- orange
+- broccoli
+- carrot
+- hot dog
+- pizza
+- donut
+- cake
+- chair
+- couch
+- potted plant
+- bed
+- dining table
+- toilet
+- tv
+- laptop
+- mouse
+- remote
+- keyboard
+- cell phone
+- microwave
+- oven
+- toaster
+- sink
+- refrigerator
+- book
+- clock
+- vase
+- scissors
+- teddy bear
+- hair drier
+- toothbrush
+target_platform: rk3576
+coordinates: pixels

models/detect/yolov8m/rk3576/int8/model.rknn

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+version https://git-lfs.github.com/spec/v1
+oid sha256:71f5574f03aa58dd0ede450c5713b8676e1777d49f2ba2c6dc73c16ae3b60118
+size 32107851

models/detect/yolov8m/rk3588/fp16/conversion.json

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+{
+  "compiler_version": "2.3.2",
+  "model_zoo_commit": "837db8e992815ff8647eadb709f07067f4bc3a71",
+  "rockchip_exporter": "https://github.com/airockchip/ultralytics_yolov8/tree/4674fe6e003dfbc5f2250d3b39dd31faaf7a9877",
+  "checkpoint_url": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+  "checkpoint_sha256": "5d4a90cdc7a21786cc59cd19778e9eafff836df9e2da32524737c7ee6efe4fe5",
+  "onnx_sha256": "cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e",
+  "rknn_sha256": "a164a9e5748d9ead9cb608f2136c83212b2f24ffaa9cdb06ed713c8e4d1b689b",
+  "chip": "rk3588",
+  "precision": "fp"
+}

models/detect/yolov8m/rk3588/fp16/metadata.yaml

@@ -0,0 +1,89 @@
+task: detect
+batch: 1
+channels: 3
+imgsz:
+- 640
+- 640
+names:
+- person
+- bicycle
+- car
+- motorcycle
+- airplane
+- bus
+- train
+- truck
+- boat
+- traffic light
+- fire hydrant
+- stop sign
+- parking meter
+- bench
+- bird
+- cat
+- dog
+- horse
+- sheep
+- cow
+- elephant
+- bear
+- zebra
+- giraffe
+- backpack
+- umbrella
+- handbag
+- tie
+- suitcase
+- frisbee
+- skis
+- snowboard
+- sports ball
+- kite
+- baseball bat
+- baseball glove
+- skateboard
+- surfboard
+- tennis racket
+- bottle
+- wine glass
+- cup
+- fork
+- knife
+- spoon
+- bowl
+- banana
+- apple
+- sandwich
+- orange
+- broccoli
+- carrot
+- hot dog
+- pizza
+- donut
+- cake
+- chair
+- couch
+- potted plant
+- bed
+- dining table
+- toilet
+- tv
+- laptop
+- mouse
+- remote
+- keyboard
+- cell phone
+- microwave
+- oven
+- toaster
+- sink
+- refrigerator
+- book
+- clock
+- vase
+- scissors
+- teddy bear
+- hair drier
+- toothbrush
+target_platform: rk3588
+coordinates: pixels

models/detect/yolov8m/rk3588/fp16/model.rknn

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+- keyboard
+- cell phone
+- microwave
+- oven
+- toaster
+- sink
+- refrigerator
+- book
+- clock
+- vase
+- scissors
+- teddy bear
+- hair drier
+- toothbrush
+target_platform: rk3588
+coordinates: pixels

models/detect/yolov8s/rk3588/int8/model.rknn

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2151ccd261ebc33a3538a6f03327c3f883c68ad83649394118849b41969d3179
+size 12466635

source/convert_official.py

@@ -0,0 +1,194 @@
+#!/usr/bin/env python3
+"""Download the ONNX listed by Rockchip and invoke its unmodified converters."""
+import argparse
+import concurrent.futures
+import hashlib
+from importlib.metadata import version
+import json
+from pathlib import Path
+import re
+import shutil
+import subprocess
+import sys
+import tempfile
+import yaml
+
+DETECTORS = ("yolov5", "yolov6", "yolov7", "yolov8", "yolov10", "yolo11",
+             "yolo26", "yolox", "ppyoloe", "yolo_world")
+TASKS = ("yolov5_seg", "yolov8_seg", "yolov8_pose", "yolov8_obb")
+SUPPLIED_ONNX = {
+    "yolo26n": "https://meta.zbox.filez.com/v/link/view/dddfdaa76107404a8a358673fa31a041",
+    "yolo26m": "https://meta.zbox.filez.com/v/link/view/198e90ee6bc94c71ad2002d5f9897ac4",
+}
+
+
+def inventory(zoo):
+    for family in (*DETECTORS, *TASKS):
+        readme = zoo / "examples" / family / "README.md"
+        urls = re.findall(r"\((https://[^)]+\.onnx)\)", readme.read_text())
+        assets = {Path(url).stem: url for url in urls}
+        if family in ("yolov8_pose", "yolov8_obb"):
+            assets = {name: url for name, url in assets.items() if "v5n-" in name or "v8n-" in name}
+        if family == "yolo26":
+            assets.update({"yolo26n": None, "yolo26m": None})
+        for name, url in assets.items():
+            yield family, name, url
+
+
+def download(root, zoo, family, name, url):
+    destination = root / "onnx" / family / f"{name}.onnx"
+    destination.parent.mkdir(parents=True, exist_ok=True)
+    if not destination.is_file():
+        local = zoo / "examples" / family / "model" / destination.name
+        if not url and local.is_file():
+            shutil.copy2(local, destination)
+        elif url:
+            partial = destination.with_suffix(".part")
+            subprocess.run(["curl", "-fLsS", "--retry", "2", "--connect-timeout", "12",
+                            "--max-time", "180", "-o", partial, url], check=True)
+            partial.replace(destination)
+        else:
+            raise FileNotFoundError(
+                f"Download {SUPPLIED_ONNX[name]} and save its ONNX as {destination}")
+    import onnx
+    onnx.load(str(destination), load_external_data=False)
+    return destination
+
+
+def digest(path):
+    checksum = hashlib.sha256()
+    with path.open("rb") as stream:
+        for block in iter(lambda: stream.read(1024 * 1024), b""):
+            checksum.update(block)
+    return checksum.hexdigest()
+
+
+def write_metadata(zoo, family, model, destination, chip):
+    if family == "yolo_world":
+        return
+    import onnx
+    inputs = onnx.load(str(model), load_external_data=False).graph.input
+    shape = [dim.dim_value for dim in inputs[0].type.tensor_type.shape.dim]
+    if len(shape) != 4 or shape[:2] != [1, 3] or min(shape[2:]) <= 0:
+        raise RuntimeError(f"Expected static NCHW RGB model, got {shape}")
+    assets = zoo / "examples" / family / "model"
+    labels = next(assets.glob("*labels_list.txt"))
+    tasks = {"yolov5_seg": "segment", "yolov8_seg": "segment",
+             "yolov8_pose": "pose", "yolov8_obb": "obb"}
+    task = tasks.get(family, "detect")
+    info = {
+        "task": task, "batch": 1, "channels": 3, "imgsz": shape[2:],
+        "names": [line.strip() for line in labels.read_text().splitlines() if line.strip()],
+        "target_platform": chip,
+        "coordinates": "pixels",
+    }
+    if family in ("yolov5", "yolov5_seg", "yolov7"):
+        values = [float(value) for value in next(assets.glob("anchors_*.txt")).read_text().split()]
+        info.update(head="anchored", anchors=[values[i:i + 6] for i in range(0, len(values), 6)])
+    if family == "yolox":
+        info["head"] = "yolox"
+    if family in ("yolov10", "yolo26"):
+        info["end2end"] = True
+    if task == "pose":
+        info["kpt_shape"] = [17, 3]
+    (destination / "metadata.yaml").write_text(yaml.safe_dump(info, sort_keys=False))
+
+
+def convert(root, zoo, asset, chip, precision, refresh_metadata=False):
+    family, name, model, source = asset
+    destination = root / "rknn" / chip / family / name / precision
+    destination.mkdir(parents=True, exist_ok=True)
+    output = destination / "model.rknn"
+    receipt = destination / "conversion.json"
+    if not refresh_metadata and output.is_file() and receipt.is_file() and (
+            family == "yolo_world" or (destination / "metadata.yaml").is_file()):
+        return f"cached {family}/{name} {chip} {precision}"
+    work_root = root / "scratch"
+    work_root.mkdir(exist_ok=True)
+    with tempfile.TemporaryDirectory(dir=work_root, prefix=f"{name}-{chip}-{precision}-") as scratch:
+        # Keep the relative dataset and model paths expected by the official scripts.
+        tree = Path(scratch)
+        (tree / "datasets").symlink_to(zoo / "datasets")
+        example = tree / "examples" / family
+        example.mkdir(parents=True)
+        (example / "model").symlink_to(zoo / "examples" / family / "model")
+        working = example / "python"
+        shutil.copytree(zoo / "examples" / family / "python", working)
+        staged = destination / "model.partial.rknn"
+        commands = []
+        if family == "yolo_world":
+            subdir = "clip_text" if name == "clip_text" else "yolo_world"
+            script = f"{subdir}/convert.py"
+            commands.append([script, str(model), chip, precision, str(staged)])
+        elif family == "yolov8_pose":
+            if precision == "i8":
+                commands.append(["convert.py", str(model), chip, "i8", "1"])
+                commands.append(["convert.py", str(model), chip, "i8", "2", str(staged)])
+            else:
+                commands.append(["convert.py", str(model), chip, "fp", "1", str(staged)])
+        else:
+            commands.append(["convert.py", str(model), chip, precision, str(staged)])
+        if not output.is_file():
+            with (destination / "convert.log").open("w") as log:
+                for command in commands:
+                    print(subprocess.list2cmdline(command), file=log, flush=True)
+                    subprocess.run([sys.executable, *command], cwd=working,
+                                   stdout=log, stderr=subprocess.STDOUT, check=True)
+            if not staged.is_file() or not staged.stat().st_size:
+                raise RuntimeError("Converter did not produce an RKNN file")
+            staged.replace(output)
+        write_metadata(zoo, family, model, destination, chip)
+        receipt.write_text(json.dumps({
+            "source": source, "onnx_sha256": digest(model), "rknn_sha256": digest(output),
+            "commands": commands, "toolkit_python": sys.executable,
+            "toolkit_version": version("rknn-toolkit2"),
+            "zoo_commit": subprocess.check_output(
+                ["git", "-C", str(zoo), "rev-parse", "HEAD"], text=True).strip(),
+        }, indent=2) + "\n")
+    return f"ok {family}/{name} {chip} {precision}"
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    root = Path(__file__).resolve().parent
+    parser.add_argument("--zoo", type=Path, default=root.parent / "rknn_model_zoo",
+                        help="Model Zoo checkout (default: ../rknn_model_zoo)")
+    parser.add_argument("--jobs", type=int, default=4)
+    parser.add_argument("--model", action="append", help="Limit the run to named variants")
+    parser.add_argument("--chip", choices=("rk3576", "rk3588"), action="append")
+    parser.add_argument("--precision", choices=("i8", "fp"), action="append")
+    parser.add_argument("--refresh-metadata", action="store_true")
+    args = parser.parse_args()
+    zoo = args.zoo.resolve()
+    inventory_rows = [item for item in inventory(zoo) if not args.model or item[1] in args.model]
+    failures = 0
+    with concurrent.futures.ThreadPoolExecutor(max_workers=6) as downloads, \
+            concurrent.futures.ThreadPoolExecutor(max_workers=args.jobs) as workers:
+        pending = {downloads.submit(download, root, zoo, *item): item for item in inventory_rows}
+        builds = {}
+        for future in concurrent.futures.as_completed(pending):
+            family, name, source = pending[future]
+            try:
+                model = future.result()
+                asset = family, name, model, source or SUPPLIED_ONNX.get(name) or str(model)
+                for chip in args.chip or ("rk3576", "rk3588"):
+                    for precision in args.precision or ("i8", "fp"):
+                        if name == "clip_text" and precision == "i8":
+                            continue
+                        job = workers.submit(convert, root, zoo, asset, chip, precision,
+                                             args.refresh_metadata)
+                        builds[job] = family, name, chip, precision
+            except Exception as error:
+                print(f"asset failed {family}/{name}: {error}", flush=True)
+                failures += 1
+        for future in concurrent.futures.as_completed(builds):
+            try:
+                print(future.result(), flush=True)
+            except Exception as error:
+                print(f"build failed {' '.join(builds[future])}: {error}", flush=True)
+                failures += 1
+    return bool(failures)
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

source/onnx/yolov8m.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cacf45350c81d4e367aa57bd4cf6b9c49f77b6f62f1b7235a2186893241fbb2e
+size 103600254

source/onnx/yolov8n.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7feb33de8924ec21346fc60c16c5a85bfbe128efdd3d65b45a8dfe3691ddc244
+size 12650245

source/onnx/yolov8s.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e3cb174a72bd791640f8ccfad79c681519079c07b190ed42740f744f20ddd49f
+size 44668901

source/rebuild-rockchip-detection.py

@@ -0,0 +1,51 @@
+"""Export published Ultralytics checkpoints with Rockchip's RKOPT detector head."""
+from concurrent.futures import ThreadPoolExecutor
+from importlib.metadata import version
+from pathlib import Path
+import json
+import os
+import re
+import subprocess
+import sys
+
+from convert_official import convert
+
+
+def main():
+    root, zoo, upstream, weights = [Path(value).resolve() for value in sys.argv[1:5]]
+    family, release = sys.argv[5:7]
+    checkpoint_prefix = 'yolo11' if family == 'yolo11' else family
+    assert version('rknn-toolkit2') == '2.3.2'
+    config = upstream / 'ultralytics/cfg/default.yaml'
+    original = config.read_text()
+    graphs = root / 'onnx' / family
+    graphs.mkdir(parents=True, exist_ok=True)
+    assets = []
+    try:
+        for size in 'nsm':
+            name = checkpoint_prefix + size
+            weight = weights / f'{name}.pt'
+            link = graphs / weight.name
+            if not link.exists():
+                link.symlink_to(weight)
+            graph = graphs / f'{name}.onnx'
+            if not graph.is_file():
+                config.write_text(re.sub(r'^model:.*$', 'model: ' + json.dumps(str(link)), original, flags=re.M))
+                with (graphs / f'{name}.log').open('w') as log:
+                    subprocess.run([sys.executable, 'ultralytics/engine/exporter.py'],
+                                   cwd=upstream, stdout=log, stderr=subprocess.STDOUT, check=True,
+                                   env={**os.environ, 'PYTHONPATH': '.', 'YOLO_AUTOINSTALL': 'false'})
+            source = f'https://github.com/ultralytics/assets/releases/download/{release}/{weight.name}'
+            assets.append((family, name, graph, source))
+    finally:
+        config.write_text(original)
+
+    with ThreadPoolExecutor(max_workers=6) as pool:
+        jobs = [pool.submit(convert, root, zoo, asset, chip, precision)
+                for asset in assets for chip in ('rk3576', 'rk3588') for precision in ('i8', 'fp')]
+        for job in jobs:
+            print(job.result(), flush=True)
+
+
+if __name__ == '__main__':
+    main()

source/weights.json

@@ -75,5 +75,38 @@
     "sha256": "234314cd8baf62616791aceb9ea6ad5c19f26cf6c0d8f3a1bfce1e23b186cfb3",
     "source": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8s-pose.pt",
     "file": "source/weights/yolov8s-pose.pt"
+  },
+  {
+    "name": "yolov8m",
+    "family": "yolov8",
+    "size": "m",
+    "task": "detect",
+    "imgsz": 640,
+    "bytes": 52136884,
+    "sha256": "5d4a90cdc7a21786cc59cd19778e9eafff836df9e2da32524737c7ee6efe4fe5",
+    "source": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8m.pt",
+    "file": "source/weights/yolov8m.pt"
+  },
+  {
+    "name": "yolov8n",
+    "family": "yolov8",
+    "size": "n",
+    "task": "detect",
+    "imgsz": 640,
+    "bytes": 6549796,
+    "sha256": "f59b3d833e2ff32e194b5bb8e08d211dc7c5bdf144b90d2c8412c47ccfc83b36",
+    "source": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8n.pt",
+    "file": "source/weights/yolov8n.pt"
+  },
+  {
+    "name": "yolov8s",
+    "family": "yolov8",
+    "size": "s",
+    "task": "detect",
+    "imgsz": 640,
+    "bytes": 22588772,
+    "sha256": "1f47a78bf100391c2a140b7ac73a1caae18c32779be7d310658112f7ac9aa78a",
+    "source": "https://github.com/ultralytics/assets/releases/download/v8.4.0/yolov8s.pt",
+    "file": "source/weights/yolov8s.pt"
   }
 ]

source/weights/yolov8m.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5d4a90cdc7a21786cc59cd19778e9eafff836df9e2da32524737c7ee6efe4fe5
+size 52136884

source/weights/yolov8n.pt

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+oid sha256:f59b3d833e2ff32e194b5bb8e08d211dc7c5bdf144b90d2c8412c47ccfc83b36
+size 6549796

source/weights/yolov8s.pt

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+oid sha256:1f47a78bf100391c2a140b7ac73a1caae18c32779be7d310658112f7ac9aa78a
+size 22588772