feat: initial commit

.gitignore

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+.DS_Store
+yolov8n.pt
+.venv

01_predict.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ultralyticsplus import YOLO, render_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt to 'yolov8n.pt'...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 6.23M/6.23M [00:00<00:00, 25.2MB/s]\n"
+     ]
+    },
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "[Errno 2] No such file or directory: 'default.jpg'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[2], line 14\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m image\u001b[38;5;241m.\u001b[39mstartswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttp\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m---> 14\u001b[0m     \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mremove\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     16\u001b[0m \u001b[38;5;66;03m# perform inference\u001b[39;00m\n\u001b[1;32m     17\u001b[0m results \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mpredict(image, conf\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.25\u001b[39m, verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'default.jpg'"
+     ]
+    }
+   ],
+   "source": [
+    "# load model\n",
+    "model = YOLO('best.pt')\n",
+    "# model = YOLO(\"nakamura196/yolov8s-layout-detection\")\n",
+    "\n",
+    "# set image\n",
+    "image = \"https://dl.ndl.go.jp/api/iiif/1879314/R0000039/full/640,640/0/default.jpg\"\n",
+    "\n",
+    "filename = image.split(\"/\")[-1]\n",
+    "\n",
+    "import os\n",
+    "\n",
+    "if image.startswith(\"http\"):\n",
+    "    if os.path.exists(filename):\n",
+    "        os.remove(filename)\n",
+    "\n",
+    "# perform inference\n",
+    "results = model.predict(image, conf=0.25, verbose=False)\n",
+    "\n",
+    "# observe results\n",
+    "render = render_result(model=model, image=image, result=results[0])\n",
+    "render.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

README.md

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 ---
+tags:
+  - ultralyticsplus
+  - yolov8
+  - ultralytics
+library_name: ultralytics
+library_version: 8.0.43
 license: cc-by-4.0
+model-index:
+  - name: nakamura196/yolov8m-wavy-line-detection
+    results:
+      - task:
+          type: object-detection
+        metrics:
+          - type: precision
+            value: 0.566
+            name: mAP50-95(B)
+          - type: precision
+            value: 0.925
+            name: mAP50(B)
+pipeline_tag: object-detection
 ---
+
+# YOLOv8 model to detect wavy lines in images
+
+## Inference
+
+### Supported Labels
+
+```python
+["line"]
+```
+
+### How to use
+
+```bash
+pip install ultralyticsplus
+```
+
+```python
+from ultralyticsplus import YOLO, render_result
+
+# load model
+model = YOLO('best.pt')
+
+# set image
+image = "https://dl.ndl.go.jp/api/iiif/1879314/R0000039/full/640,640/0/default.jpg"
+
+# perform inference
+results = model.predict(image, verbose=False)
+
+# observe results
+render = render_result(model=model, image=image, result=results[0])
+render.show()
+```

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8684c96c30592d3fe3097168428499eebf8b5577fc19000f2e5741b57eef8a4b
+size 52036310

config.json

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+{
+    "input_size": 640,
+    "task": "object-detection",
+    "ultralyticsplus_version": "0.0.24",
+    "ultralytics_version": "8.0.23",
+    "model_type": "v8",
+    "mAP@50": 0.925,
+    "mAp@50-95": 0.566
+}

requirements.txt

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+ultralyticsplus