Organize RKNN models by Toolkit2 version

.gitattributes

@@ -133,3 +133,103 @@ models/segment/yolo11x-seg/rk3588/fp16/model.rknn filter=lfs diff=lfs merge=lfs
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README.md

@@ -12,7 +12,7 @@ tags:
 
 Converted with the Ultralytics export workflow and task-specific RKNN conversion tools. This repository contains 100 FP16 and INT8 exports for RK3576 and RK3588. Tasks include classify, detect, obb, pose, segment.
 
-Choose a model under `models/<task>/<variant>/<chip>/<precision>/` and download both `model.rknn` and `metadata.yaml`. The [manifest](manifest.json) lists the supported combinations and SHA-256 hashes.
+Choose a model under `models/<toolkit-version>/<task>/<variant>/<chip>/<precision>/` and download both `model.rknn` and `metadata.yaml`. The [manifest](manifest.json) lists the supported combinations and SHA-256 hashes.
 
 ## Source and license
 
@@ -25,3 +25,5 @@ The [source directory](tree/main/source) contains the original checkpoints, conv
 ### INT8 detection
 
 Use the `metadata.yaml` from the same INT8 model folder. The detector outputs normalized box coordinates, so the app needs `coordinates: normalized`. Import both files together in the warehouse. For the CLI, keep them in the same directory. Interpreting the coordinates as pixels can result in no boxes.
+
+Models are organized by RKNN Toolkit2 version under `models/v<version>/`. Each model and its metadata share a folder.

manifest.json

@@ -15,8 +15,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 80,
-    "path": "models/detect/yolo11n/rk3576/fp16",
-    "weights": "source/weights/yolo11n.pt"
+    "path": "models/v2.3.2/detect/yolo11n/rk3576/fp16",
+    "weights": "source/weights/yolo11n.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n",
@@ -34,8 +35,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 80,
-    "path": "models/detect/yolo11n/rk3588/fp16",
-    "weights": "source/weights/yolo11n.pt"
+    "path": "models/v2.3.2/detect/yolo11n/rk3588/fp16",
+    "weights": "source/weights/yolo11n.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-seg",
@@ -53,8 +55,9 @@
     "decode_precision": "fp16",
     "fp16_decode_tensors": 23,
     "classes": 80,
-    "path": "models/segment/yolo11n-seg/rk3576/int8",
-    "weights": "source/weights/yolo11n-seg.pt"
+    "path": "models/v2.3.2/segment/yolo11n-seg/rk3576/int8",
+    "weights": "source/weights/yolo11n-seg.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-seg",
@@ -72,8 +75,9 @@
     "decode_precision": "fp16",
     "fp16_decode_tensors": 23,
     "classes": 80,
-    "path": "models/segment/yolo11n-seg/rk3588/int8",
-    "weights": "source/weights/yolo11n-seg.pt"
+    "path": "models/v2.3.2/segment/yolo11n-seg/rk3588/int8",
+    "weights": "source/weights/yolo11n-seg.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-seg",
@@ -91,8 +95,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 80,
-    "path": "models/segment/yolo11n-seg/rk3576/fp16",
-    "weights": "source/weights/yolo11n-seg.pt"
+    "path": "models/v2.3.2/segment/yolo11n-seg/rk3576/fp16",
+    "weights": "source/weights/yolo11n-seg.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-pose",
@@ -110,8 +115,9 @@
     "decode_precision": "fp16",
     "fp16_decode_tensors": 30,
     "classes": 1,
-    "path": "models/pose/yolo11n-pose/rk3576/int8",
-    "weights": "source/weights/yolo11n-pose.pt"
+    "path": "models/v2.3.2/pose/yolo11n-pose/rk3576/int8",
+    "weights": "source/weights/yolo11n-pose.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-seg",
@@ -129,8 +135,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 80,
-    "path": "models/segment/yolo11n-seg/rk3588/fp16",
-    "weights": "source/weights/yolo11n-seg.pt"
+    "path": "models/v2.3.2/segment/yolo11n-seg/rk3588/fp16",
+    "weights": "source/weights/yolo11n-seg.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-pose",
@@ -148,8 +155,9 @@
     "decode_precision": "fp16",
     "fp16_decode_tensors": 30,
     "classes": 1,
-    "path": "models/pose/yolo11n-pose/rk3588/int8",
-    "weights": "source/weights/yolo11n-pose.pt"
+    "path": "models/v2.3.2/pose/yolo11n-pose/rk3588/int8",
+    "weights": "source/weights/yolo11n-pose.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-pose",
@@ -167,8 +175,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 1,
-    "path": "models/pose/yolo11n-pose/rk3576/fp16",
-    "weights": "source/weights/yolo11n-pose.pt"
+    "path": "models/v2.3.2/pose/yolo11n-pose/rk3576/fp16",
+    "weights": "source/weights/yolo11n-pose.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-pose",
@@ -186,8 +195,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 1,
-    "path": "models/pose/yolo11n-pose/rk3588/fp16",
-    "weights": "source/weights/yolo11n-pose.pt"
+    "path": "models/v2.3.2/pose/yolo11n-pose/rk3588/fp16",
+    "weights": "source/weights/yolo11n-pose.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-obb",
@@ -205,8 +215,9 @@
     "decode_precision": "fp16",
     "fp16_decode_tensors": 36,
     "classes": 15,
-    "path": "models/obb/yolo11n-obb/rk3576/int8",
-    "weights": "source/weights/yolo11n-obb.pt"
+    "path": "models/v2.3.2/obb/yolo11n-obb/rk3576/int8",
+    "weights": "source/weights/yolo11n-obb.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-obb",
@@ -224,8 +235,9 @@
     "decode_precision": "fp16",
     "fp16_decode_tensors": 36,
     "classes": 15,
-    "path": "models/obb/yolo11n-obb/rk3588/int8",
-    "weights": "source/weights/yolo11n-obb.pt"
+    "path": "models/v2.3.2/obb/yolo11n-obb/rk3588/int8",
+    "weights": "source/weights/yolo11n-obb.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-obb",
@@ -243,8 +255,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 15,
-    "path": "models/obb/yolo11n-obb/rk3576/fp16",
-    "weights": "source/weights/yolo11n-obb.pt"
+    "path": "models/v2.3.2/obb/yolo11n-obb/rk3576/fp16",
+    "weights": "source/weights/yolo11n-obb.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-obb",
@@ -262,8 +275,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 15,
-    "path": "models/obb/yolo11n-obb/rk3588/fp16",
-    "weights": "source/weights/yolo11n-obb.pt"
+    "path": "models/v2.3.2/obb/yolo11n-obb/rk3588/fp16",
+    "weights": "source/weights/yolo11n-obb.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n",
@@ -281,8 +295,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 80,
-    "path": "models/detect/yolo11n/rk3588/int8",
-    "weights": "source/weights/yolo11n.pt"
+    "path": "models/v2.3.2/detect/yolo11n/rk3588/int8",
+    "weights": "source/weights/yolo11n.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-cls",
@@ -300,8 +315,9 @@
     "decode_precision": null,
     "fp16_decode_tensors": null,
     "classes": 1000,
-    "path": "models/classify/yolo11n-cls/rk3576/fp16",
-    "weights": "source/weights/yolo11n-cls.pt"
+    "path": "models/v2.3.2/classify/yolo11n-cls/rk3576/fp16",
+    "weights": "source/weights/yolo11n-cls.pt",
+    "toolkit_version": "2.3.2"
   },
   {
     "name": "yolo11n-cls",
@@ -319,8 +335,9 @@
     "decode_precision": null,
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