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{
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"## How tu use\n",
"\n",
"- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus):\n",
"\n",
"```bash\n",
"pip install -U ultralyticsplus\n",
"```\n",
"\n",
"- Load model and perform prediction:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Found https://dl.ndl.go.jp/api/iiif/2534020/T0000001/full/full/0/default.jpg locally at default.jpg\n",
"image 1/1 /Users/nakamura/git/hf/models/yolov8-ndl-layout/default.jpg: 640x640 1 1_overall, 1 3_typography, 510.9ms\n",
"Speed: 2.2ms preprocess, 510.9ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 640)\n"
]
}
],
"source": [
"from ultralyticsplus import YOLO, render_result\n",
"import os\n",
"\n",
"# load model\n",
"model = YOLO('model_- 19 may 2024 15_13.pt')\n",
" \n",
"# set model parameters\n",
"conf_threshold = 0.25 # NMS confidence threshold\n",
"iou_threshold = 0.45 # NMS IoU threshold\n",
"\n",
"# set image\n",
"img = 'https://dl.ndl.go.jp/api/iiif/2534020/T0000001/full/full/0/default.jpg'\n",
"\n",
"# perform inference\n",
"results = model.predict(img, conf=conf_threshold, iou=iou_threshold)\n",
"render = render_result(model=model, image=img, result=results[0]) \n",
"\n",
"os.makedirs('results', exist_ok=True)\n",
"\n",
"# save\n",
"render.save('results/1.jpg')"
]
},
{
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"execution_count": null,
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"source": []
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