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Author: WongKinYiu

tools/reparameterization.ipynb

@@ -8,7 +8,15 @@
    "outputs": [],
    "source": [
     "import torch\n",
-    "from models.yolo import Model\n"
+    "from models.yolo import Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8680f822",
+   "metadata": {},
+   "source": [
+    "## Convert YOLOv9-C"
    ]
   },
   {
@@ -97,6 +105,119 @@
     "          'epoch': -1}\n",
     "torch.save(m_ckpt, \"./yolov9-c-converted.pt\")"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47c6e6ae",
+   "metadata": {},
+   "source": [
+    "## Convert YOLOv9-E"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "801a1b7c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "device = torch.device(\"cpu\")\n",
+    "cfg = \"./models/detect/gelan-e.yaml\"\n",
+    "model = Model(cfg, ch=3, nc=80, anchors=3)\n",
+    "#model = model.half()\n",
+    "model = model.to(device)\n",
+    "_ = model.eval()\n",
+    "ckpt = torch.load('./yolov9-e.pt', map_location='cpu')\n",
+    "model.names = ckpt['model'].names\n",
+    "model.nc = ckpt['model'].nc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2ef4fe6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "idx = 0\n",
+    "for k, v in model.state_dict().items():\n",
+    "    if \"model.{}.\".format(idx) in k:\n",
+    "        if idx < 29:\n",
+    "            kr = k.replace(\"model.{}.\".format(idx), \"model.{}.\".format(idx))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif idx < 42:\n",
+    "            kr = k.replace(\"model.{}.\".format(idx), \"model.{}.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif \"model.{}.cv2.\".format(idx) in k:\n",
+    "            kr = k.replace(\"model.{}.cv2.\".format(idx), \"model.{}.cv4.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif \"model.{}.cv3.\".format(idx) in k:\n",
+    "            kr = k.replace(\"model.{}.cv3.\".format(idx), \"model.{}.cv5.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif \"model.{}.dfl.\".format(idx) in k:\n",
+    "            kr = k.replace(\"model.{}.dfl.\".format(idx), \"model.{}.dfl2.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "    else:\n",
+    "        while True:\n",
+    "            idx += 1\n",
+    "            if \"model.{}.\".format(idx) in k:\n",
+    "                break\n",
+    "        if idx < 29:\n",
+    "            kr = k.replace(\"model.{}.\".format(idx), \"model.{}.\".format(idx))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif idx < 42:\n",
+    "            kr = k.replace(\"model.{}.\".format(idx), \"model.{}.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif \"model.{}.cv2.\".format(idx) in k:\n",
+    "            kr = k.replace(\"model.{}.cv2.\".format(idx), \"model.{}.cv4.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif \"model.{}.cv3.\".format(idx) in k:\n",
+    "            kr = k.replace(\"model.{}.cv3.\".format(idx), \"model.{}.cv5.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "        elif \"model.{}.dfl.\".format(idx) in k:\n",
+    "            kr = k.replace(\"model.{}.dfl.\".format(idx), \"model.{}.dfl2.\".format(idx+7))\n",
+    "            model.state_dict()[k] -= model.state_dict()[k]\n",
+    "            model.state_dict()[k] += ckpt['model'].state_dict()[kr]\n",
+    "            print(k, \"perfectly matched!!\")\n",
+    "_ = model.eval()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "27bc1869",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m_ckpt = {'model': model.half(),\n",
+    "          'optimizer': None,\n",
+    "          'best_fitness': None,\n",
+    "          'ema': None,\n",
+    "          'updates': None,\n",
+    "          'opt': None,\n",
+    "          'git': None,\n",
+    "          'date': None,\n",
+    "          'epoch': -1}\n",
+    "torch.save(m_ckpt, \"./yolov9-e-converted.pt\")"
+   ]
   }
  ],
  "metadata": {