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     "text": [
      "/home/shiv-nlp-mldl-cv/anaconda3/envs/S15-Yolo1/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
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     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "Running on public URL: https://fa61d92c4dbab3b5e3.gradio.live\n",
      "\n",
      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
     ]
    },
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     },
     "execution_count": 1,
     "metadata": {},
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    }
   ],
   "source": [
    "import gradio as gr\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "import os\n",
    "import uuid\n",
    "\n",
    "def inference(input_img):\n",
    "    temp = uuid.uuid4()\n",
    "    shell = f\"python yolov9/detect.py --source {input_img} --img 640 --device cpu --weights yolov9/runs/train/exp/weights/best.pt --name {temp}\"\n",
    "    os.system(shell)\n",
    "    return f\"yolov9/runs/detect/{temp}/{input_img.split('/')[-1]}\"\n",
    "    #return \"yolov9/runs/detect/f807164a-496b-413c-bb47-f5daf8803dcd/cut_a_1.mp4\"\n",
    "\n",
    "def inference_video(input_img):\n",
    "    org_img = input_img\n",
    "    return input_img\n",
    "\n",
    "with gr.Blocks() as demo:\n",
    "    gr.Markdown(\n",
    "        \"\"\"\n",
    "        # Vehicle detection using Yolo-v9\n",
    "        \"\"\"\n",
    "    )\n",
    "\n",
    "    with gr.Tab(\"Video\"):\n",
    "        gr.Markdown(\n",
    "            \"\"\"\n",
    "            Upload image file and detect vehicles present in the image\n",
    "            \"\"\"\n",
    "        )\n",
    "        with gr.Row():\n",
    "            img_input = [gr.PlayableVideo(label=\"Input Image\", autoplay=True,  width=300, height=300)]\n",
    "            pred_outputs = [gr.PlayableVideo(label=\"Output Image\",width=640, autoplay=True, height=640)]\n",
    "        \n",
    "        gr.Markdown(\"## Examples\")\n",
    "\n",
    "        with gr.Row(): \n",
    "            gr.Examples([ \n",
    "                'cut_a_2.mp4',\n",
    "                'cut_b_1.mp4','tresa.mp4'], \n",
    "                inputs=img_input, fn=inference)\n",
    "        \n",
    "            image_button = gr.Button(\"Predict\")\n",
    "            image_button.click(inference, inputs=img_input, outputs=pred_outputs)\n",
    "\n",
    "    with gr.Tab(\"Image\"):\n",
    "        \n",
    "        \n",
    "        gr.Markdown(\n",
    "            \"\"\"\n",
    "            Upload image file and detect vehicles present in the image\n",
    "            \"\"\"\n",
    "        )\n",
    "        with gr.Row():\n",
    "            img_input = [gr.Image(type=\"filepath\",label=\"Input Image\",width=300, height=300)]\n",
    "            pred_outputs = [gr.Image(label=\"Output Image\",width=640, height=640)]\n",
    "\n",
    "        gr.Markdown(\"## Examples\")\n",
    "\n",
    "        with gr.Row(): \n",
    "            gr.Examples([ \n",
    "                         'rohan.jpg',\n",
    "                         'lamborghini-aventador-2932196_1280.jpg', \n",
    "                         '0KL1ICR33YYZ.jpg',\n",
    "                         '0RVD53V60NOM.jpg',\n",
    "                         '0RW4I2NTAH8K.jpg',\n",
    "                         '1CSLEJ2UJD3G.jpg',\n",
    "                         '1E4CD5K13UXO.jpg',\n",
    "                         '2.jpg',\n",
    "                         'truck.jpg',\n",
    "                         '3BXRTQZ70A7M.jpg',\n",
    "                         '3GVLVIQ2J4P2.jpg',\n",
    "                         '3RIYE11PE0VK.jpg',\n",
    "                         '4AS6VDRS3Y07.jpg',\n",
    "                         '4DM206U83T3B.jpg',\n",
    "                         '05U2U2R2K6DN.jpg',\n",
    "                         '6LBV93O0MWUY.jpg',\n",
    "                         '6MFW23QQFW3E.jpg',\n",
    "                         '6V4OYHB47QOX.jpg',\n",
    "                         '6VOUS49LKRLI.jpg',\n",
    "                         '6VOUS49LKRLI.jpg',\n",
    "                         '7L1KFQDNLCBY.jpg',\n",
    "                         '23BNPRMYV2RT.jpg',\n",
    "                         '24IHCQ74TBML.jpg',\n",
    "                         '38EE8ZBTSGD1.jpg',\n",
    "                         '05U2U2R2K6DN.jpg',\n",
    "                         '0KL1ICR33YYZ.jpg'\n",
    "                         ], \n",
    "                        inputs=img_input, fn=inference)\n",
    "            image_button = gr.Button(\"Predict\")\n",
    "            image_button.click(inference, inputs=img_input, outputs=pred_outputs)\n",
    "\n",
    "        \n",
    "\n",
    "\n",
    "\n",
    "demo.launch(share=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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