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   "id": "81598ea8-8e97-4ad7-a45f-bd928d0ef416",
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   "source": [
    "import gradio as gr\n",
    "from ultralytics import YOLO\n",
    "import cv2\n",
    "import os\n",
    "\n",
    "def predict_image(image_input):\n",
    "    image = cv2.imread(image_input)\n",
    "    # load model\n",
    "    model = YOLO(\"best.pt\")\n",
    "    #run predict\n",
    "    outputs = model.predict(source=image_input)\n",
    "    results = output[0].cpu().numpy()\n",
    "    for i, det in enumerate(results.boxes.xyxy):\n",
    "        cv2.rectangle(image, (int(det[0]), int(det[1]), int(det[2]), int(det[3]),\n",
    "                              color=(0, 0, 255), thickness=2, lineType=cv2.Line_AA)\n",
    "    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
    "\n",
    "inputs_image = [gr.components.Image(type=\"filepath\", label=\"Input Image\")]\n",
    "outputs_image = [gr.components.Image(type=\"numpy\", label=\"Output Image\")]\n",
    "\n",
    "interface_image = gr.Interface(fn = predict_image, inputs=inputs_image, outputs=outputs_image, \n",
    "                               title=\"Fire & Smoke Detector\", cache_examples=False)\n",
    "\n",
    "interface_image.launch(Debug=True)\n"
   ]
  }
 ],
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