llavaMed-demo.ipynb

{
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   "cell_type": "markdown",
   "id": "718bac1e-7b0a-4fe6-b048-e09f3e1f7d4f",
   "metadata": {},
   "source": [
    "# LLaVA-Med++ Demo\n",
    "Enhancing Visual Instruction Tuning with LLaMA 3.1 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06797b97-e283-4adf-a89e-88da055267ce",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a2aa71a6-82af-46cc-8214-86182c7ff668",
   "metadata": {
    "execution": {
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     "shell.execute_reply.started": "2024-08-28T08:48:35.334403Z"
    }
   },
   "outputs": [],
   "source": [
    "## reduce logging\n",
    "import logging, sys\n",
    "logging.getLogger().setLevel(logging.CRITICAL)\n",
    "logging.disable(sys.maxsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "88f7f360-5940-448e-9f89-cd6929b8b48b",
   "metadata": {
    "execution": {
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    }
   },
   "outputs": [],
   "source": [
    "#!conda env export --no-builds > environment.yml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "342d107d-8eb7-4695-af67-1308fb91a044",
   "metadata": {
    "execution": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(True, 1, 0)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## fix warning\n",
    "## \"bash: /miniconda/envs/llava-more/lib/libtinfo.so.6: no version information available (required by bash)\"\n",
    "# conda install -c conda-forge ncurses\n",
    "\n",
    "# conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia\n",
    "\n",
    "import torch\n",
    "torch.cuda.is_available(), torch.cuda.device_count(), torch.cuda.current_device()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1fd69662-a22e-4269-9da5-2ea04750601d",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-08-28T08:16:19.473294Z",
     "shell.execute_reply.started": "2024-08-28T08:16:19.471673Z"
    }
   },
   "outputs": [],
   "source": [
    "## fix widgets\n",
    "#!conda install -c conda-forge ipywidgets -y\n",
    "#!jupyter nbextension enable --py widgetsnbextension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b93483b4-d16e-4cd2-8087-ceb47a605244",
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "# conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia\n",
    "#!pip uninstall flash-attn -y\n",
    "#!pip install flash-attn --no-build-isolation\n",
    "#!pip install ipywidgets\n",
    "#!pip install transformers==4.44.2\n",
    "#!pip install scipy\n",
    "#!pip install python-dotenv\n",
    "\n",
    "#!pip install datasets\n",
    "#!pip install accelerate\n",
    "#!pip install git+https://github.com/bfshi/scaling_on_scales.git\n",
    "\n",
    "# from huggingface_hub import notebook_login\n",
    "# notebook_login()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ab548805-378c-4c75-a0b3-6a77353717f4",
   "metadata": {
    "execution": {
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     "shell.execute_reply.started": "2024-08-28T08:16:19.476970Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nvcc: NVIDIA (R) Cuda compiler driver\n",
      "Copyright (c) 2005-2023 NVIDIA Corporation\n",
      "Built on Tue_Feb__7_19:32:13_PST_2023\n",
      "Cuda compilation tools, release 12.1, V12.1.66\n",
      "Build cuda_12.1.r12.1/compiler.32415258_0\n"
     ]
    }
   ],
   "source": [
    "!nvcc --version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5e2a13b8-0477-4780-87e1-72066f42ba86",
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2024-08-28T08:16:19.607224Z",
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    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python 3.10.14\n"
     ]
    }
   ],
   "source": [
    "!python --version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0801b6e0-513c-49a5-a19e-34f0a5f5bc17",
   "metadata": {
    "execution": {
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     "iopub.status.idle": "2024-08-28T08:16:19.940967Z",
     "shell.execute_reply": "2024-08-28T08:16:19.940663Z",
     "shell.execute_reply.started": "2024-08-28T08:16:19.728437Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "transformers =  4.44.2\n",
      "torch = 2.3.1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/miniconda/envs/llava-med++/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"
     ]
    }
   ],
   "source": [
    "import transformers\n",
    "print(\"transformers = \",transformers.__version__)\n",
    "import torch\n",
    "print (\"torch =\", torch.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3a382a66-4dff-4ecd-ad4d-3a996768ca67",
   "metadata": {
    "execution": {
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    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/pop/hosting/medical/MedTrinity-25M\n"
     ]
    }
   ],
   "source": [
    "!pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "36b16b24-d85e-4d03-8edd-3f81577c5e21",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:20.061459Z",
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   },
   "outputs": [],
   "source": [
    "%load_ext dotenv\n",
    "%dotenv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bcc86e7-be20-4aa0-9463-99a39fbc84f9",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "59f3af15-89ee-4850-9edc-f9f610b6146f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:47:30.954187Z",
     "iopub.status.busy": "2024-08-28T08:47:30.953968Z",
     "iopub.status.idle": "2024-08-28T08:47:32.901380Z",
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     "shell.execute_reply.started": "2024-08-28T08:47:30.954174Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/miniconda/envs/llava-med++/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"
     ]
    }
   ],
   "source": [
    "##%tb\n",
    "import argparse\n",
    "import torch\n",
    "import requests\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "import re\n",
    "\n",
    "from llava.constants import (\n",
    "    IMAGE_TOKEN_INDEX,\n",
    "    DEFAULT_IMAGE_TOKEN,\n",
    "    DEFAULT_IM_START_TOKEN,\n",
    "    DEFAULT_IM_END_TOKEN,\n",
    "    IMAGE_PLACEHOLDER,\n",
    ")\n",
    "from llava.conversation import conv_templates, SeparatorStyle\n",
    "from llava.model.builder import load_pretrained_model\n",
    "from llava.utils import disable_torch_init\n",
    "from llava.mm_utils import (\n",
    "    process_images,\n",
    "    tokenizer_image_token,\n",
    "    get_model_name_from_path,\n",
    ")\n",
    "\n",
    "def image_parser(args):\n",
    "    out = args.image_file.split(args.sep)\n",
    "    return out\n",
    "\n",
    "\n",
    "def load_image(image_file):\n",
    "    if image_file.startswith(\"http\") or image_file.startswith(\"https\"):\n",
    "        response = requests.get(image_file)\n",
    "        image = Image.open(BytesIO(response.content)).convert(\"RGB\")\n",
    "    else:\n",
    "        image = Image.open(image_file).convert(\"RGB\")\n",
    "    return image\n",
    "\n",
    "\n",
    "def load_images(image_files):\n",
    "    out = []\n",
    "    for image_file in image_files:\n",
    "        image = load_image(image_file)\n",
    "        out.append(image)\n",
    "    return out\n",
    "\n",
    "def eval_model(args):\n",
    "    # Model\n",
    "    disable_torch_init()\n",
    "\n",
    "    model_name = get_model_name_from_path(args.model_path)\n",
    "    model_name= 'llava'\n",
    "\n",
    "    tokenizer, model, image_processor, context_len = load_pretrained_model(\n",
    "        args.model_path, args.model_base, model_name, load_8bit=False\n",
    "    )\n",
    "    #print(model.config)\n",
    "    \n",
    "    qs = args.query\n",
    "    image_token_se = DEFAULT_IM_START_TOKEN + DEFAULT_IMAGE_TOKEN + DEFAULT_IM_END_TOKEN\n",
    "    if IMAGE_PLACEHOLDER in qs:\n",
    "        if model.config.mm_use_im_start_end:\n",
    "            qs = re.sub(IMAGE_PLACEHOLDER, image_token_se, qs)\n",
    "        else:\n",
    "            qs = re.sub(IMAGE_PLACEHOLDER, DEFAULT_IMAGE_TOKEN, qs)\n",
    "    else:\n",
    "        if model.config.mm_use_im_start_end:\n",
    "            qs = image_token_se + \"\\n\" + qs\n",
    "        else:\n",
    "            qs = DEFAULT_IMAGE_TOKEN + \"\\n\" + qs\n",
    "\n",
    "    if \"llama-2\" in model_name.lower():\n",
    "        conv_mode = \"llava_llama_2\"\n",
    "    elif \"mistral\" in model_name.lower():\n",
    "        conv_mode = \"mistral_instruct\"\n",
    "    elif \"v1.6-34b\" in model_name.lower():\n",
    "        conv_mode = \"chatml_direct\"\n",
    "    elif \"v1\" in model_name.lower():\n",
    "        conv_mode = \"llava_v1\"\n",
    "    elif \"mpt\" in model_name.lower():\n",
    "        conv_mode = \"mpt\"\n",
    "    else:\n",
    "        conv_mode = \"llava_v0\"\n",
    "\n",
    "    if args.conv_mode is not None and conv_mode != args.conv_mode:\n",
    "        print(\n",
    "            \"[WARNING] the auto inferred conversation mode is {}, while `--conv-mode` is {}, using {}\".format(\n",
    "                conv_mode, args.conv_mode, args.conv_mode\n",
    "            )\n",
    "        )\n",
    "    else:\n",
    "        args.conv_mode = conv_mode\n",
    "    \n",
    "    conv = conv_templates[args.conv_mode].copy()\n",
    "    conv.append_message(conv.roles[0], qs)\n",
    "    conv.append_message(conv.roles[1], None)\n",
    "    prompt = conv.get_prompt()\n",
    "    conv.tokenizer = tokenizer\n",
    "\n",
    "    image_files = image_parser(args)\n",
    "    images = load_images(image_files)\n",
    "    image_sizes = [x.size for x in images]\n",
    "    images_tensor = process_images(\n",
    "        images,\n",
    "        image_processor,\n",
    "        model.config\n",
    "    ).to(model.device, dtype=torch.float16)\n",
    "\n",
    "    input_ids = (\n",
    "        tokenizer_image_token(prompt, tokenizer, IMAGE_TOKEN_INDEX, return_tensors=\"pt\")\n",
    "        .unsqueeze(0)\n",
    "        .cuda()\n",
    "    )\n",
    "\n",
    "    with torch.inference_mode():\n",
    "        output_ids = model.generate(\n",
    "            input_ids,\n",
    "            images=images_tensor,\n",
    "            image_sizes=image_sizes,\n",
    "            do_sample=True if args.temperature > 0 else False,\n",
    "            temperature=args.temperature,\n",
    "            top_p=args.top_p,\n",
    "            num_beams=args.num_beams,\n",
    "            max_new_tokens=args.max_new_tokens,\n",
    "            use_cache=True,\n",
    "        )\n",
    "\n",
    "    outputs = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0].strip()\n",
    "    #print(outputs)\n",
    "    return outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "963a02ee-4586-41dc-9499-b0a52938eccd",
   "metadata": {},
   "source": [
    "## demo dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "18473ac8-aea9-4aae-bead-6b4c9c8b86b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:21.912149Z",
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     "shell.execute_reply.started": "2024-08-28T08:16:21.912131Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetDict({\n",
       "    train: Dataset({\n",
       "        features: ['image', 'id', 'caption'],\n",
       "        num_rows: 161630\n",
       "    })\n",
       "})"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "\n",
    "ds = load_dataset(\"UCSC-VLAA/MedTrinity-25M\", \"25M_demo\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fa5ca82a-2c99-40de-aadb-4e4c9ee0959f",
   "metadata": {
    "execution": {
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     "shell.execute_reply.started": "2024-08-28T08:16:23.862821Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'80306b2e-1b5c-11ef-af70-000066532cad'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[\"train\"][2000]['id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "464ea787-e26f-4bef-a56f-9546c228f371",
   "metadata": {
    "execution": {
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    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"The image is a non-contrast computed tomography (CT) scan of the brain, showing the cerebral structures without the use of contrast media. The region of interest, located centrally and in the lower-middle area of the brain, occupies approximately 0.5% of the image area and is indicative of an intracranial hemorrhage. This region appears denser than the surrounding brain tissue, which is a characteristic feature of acute hemorrhage on CT imaging. The location of the hemorrhage could potentially affect nearby brain structures due to mass effect or increased intracranial pressure, although the image does not provide evidence of such complications. The hemorrhage's proximity to critical brain areas suggests a possible impact on the patient's neurological function.\""
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[\"train\"][2000]['caption']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0f721efe-80e6-41b5-aaa2-70942a7e9c4f",
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=512x512>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im=ds[\"train\"][2000]['image']\n",
    "im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "aa90dae9-96a9-40a1-8d30-23cb00414a31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:23.898570Z",
     "iopub.status.busy": "2024-08-28T08:16:23.898482Z",
     "iopub.status.idle": "2024-08-28T08:16:23.922657Z",
     "shell.execute_reply": "2024-08-28T08:16:23.922377Z",
     "shell.execute_reply.started": "2024-08-28T08:16:23.898557Z"
    }
   },
   "outputs": [],
   "source": [
    "# save a image using extension\n",
    "#out_im = Image.fromarray(im)\n",
    "im.save('med_test_2000.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6a3942e-abe7-4b2a-8ed8-f3ccffff050e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "132537b5-909a-434f-b382-a66735aeda21",
   "metadata": {},
   "source": [
    "## Test-1 VGA RAD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "224d53fc-779b-4cae-a263-fb56397ec178",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:23.923078Z",
     "iopub.status.busy": "2024-08-28T08:16:23.923004Z",
     "iopub.status.idle": "2024-08-28T08:16:23.926144Z",
     "shell.execute_reply": "2024-08-28T08:16:23.925845Z",
     "shell.execute_reply.started": "2024-08-28T08:16:23.923067Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_153409/4283171320.py:5: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
      "  from IPython.core.display import Image, display\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<img src=\"https://prod-images-static.radiopaedia.org/images/566180/d527ff6fc1482161c9225345c4ab42_big_gallery.jpg\" width=\"600\" height=\"100\" class=\"unconfined\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "path=\"https://prod-images-static.radiopaedia.org/images/566180/d527ff6fc1482161c9225345c4ab42_big_gallery.jpg\"\n",
    "#display(Image.open(path))\n",
    "#Image(url= path, width=100, height=100)\n",
    "from IPython.core.display import Image, display\n",
    "display(Image(url=path, width=600, height=100, unconfined=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a88b334a-3fd9-4c5f-b8e0-f8b7db427010",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:23.926581Z",
     "iopub.status.busy": "2024-08-28T08:16:23.926506Z",
     "iopub.status.idle": "2024-08-28T08:16:34.551040Z",
     "shell.execute_reply": "2024-08-28T08:16:34.550545Z",
     "shell.execute_reply.started": "2024-08-28T08:16:23.926570Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:07<00:00,  1.98s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 23.3 s, sys: 21.3 s, total: 44.6 s\n",
      "Wall time: 10.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift\"    \n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift_20240817\"\n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://prod-images-static.radiopaedia.org/images/566180/d527ff6fc1482161c9225345c4ab42_big_gallery.jpg\"\n",
    "    query: str = \"What Do Chest X-Rays Show?\"\n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = 3\n",
    "    num_beams: int = 3\n",
    "    max_new_tokens: int = 256\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result = eval_model(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "583044a4-f182-46c6-8869-1e87a46105d6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:34.551673Z",
     "iopub.status.busy": "2024-08-28T08:16:34.551589Z",
     "iopub.status.idle": "2024-08-28T08:16:34.554356Z",
     "shell.execute_reply": "2024-08-28T08:16:34.554017Z",
     "shell.execute_reply.started": "2024-08-28T08:16:34.551661Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cardiomegaly'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39528ef9-0461-474d-99c3-fe10d2b967b3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "69ba4f4e-b574-46ed-805e-df3d098cafce",
   "metadata": {},
   "source": [
    "## Test-2 PathVGA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "210bc188-02a2-423d-aebe-f4da462a4437",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:34.554830Z",
     "iopub.status.busy": "2024-08-28T08:16:34.554759Z",
     "iopub.status.idle": "2024-08-28T08:16:56.278332Z",
     "shell.execute_reply": "2024-08-28T08:16:56.277828Z",
     "shell.execute_reply.started": "2024-08-28T08:16:34.554820Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetune-pathvqa_orift/\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:07<00:00,  1.78s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 25.3 s, sys: 21.4 s, total: 46.8 s\n",
      "Wall time: 21.7 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetune-pathvqa_orift/\"    \n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift_20240817\"\n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://prod-images-static.radiopaedia.org/images/566180/d527ff6fc1482161c9225345c4ab42_big_gallery.jpg\"    \n",
    "    query: str = \"What Do Chest X-Rays Show?\"\n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = 3\n",
    "    num_beams: int = 3\n",
    "    max_new_tokens: int = 256\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "result = eval_model(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e8b7d91c-0e47-438a-9c4c-b58c6f2cd611",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:56.278969Z",
     "iopub.status.busy": "2024-08-28T08:16:56.278878Z",
     "iopub.status.idle": "2024-08-28T08:16:56.281716Z",
     "shell.execute_reply": "2024-08-28T08:16:56.281372Z",
     "shell.execute_reply.started": "2024-08-28T08:16:56.278956Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'aorta not opened surrounded by large nodes'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e368e39b-6e62-4cdd-8bfc-3ff82063e64c",
   "metadata": {},
   "source": [
    "## Test-3 Captioner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "09898a03-cc10-4617-aa46-761e2d6d3f98",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:16:56.282151Z",
     "iopub.status.busy": "2024-08-28T08:16:56.282069Z",
     "iopub.status.idle": "2024-08-28T08:17:17.098346Z",
     "shell.execute_reply": "2024-08-28T08:17:17.097928Z",
     "shell.execute_reply.started": "2024-08-28T08:16:56.282141Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:08<00:00,  2.25s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 32.4 s, sys: 20.3 s, total: 52.7 s\n",
      "Wall time: 20.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\"    \n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift_20240817\"\n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://prod-images-static.radiopaedia.org/images/566180/d527ff6fc1482161c9225345c4ab42_big_gallery.jpg\"    \n",
    "    #image_file:str = \"https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41598-022-27266-9/MediaObjects/41598_2022_27266_Fig1_HTML.png\"\n",
    "    #image_file: str = \"med_test_2000.png\"    \n",
    "    query: str = \"Give me detailed description of the image, based on coarse caption, lesion region, medical knowledge\"\n",
    "    #query: str = \"What is abnormal show in the X-Ray?\"    \n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = None\n",
    "    num_beams: int = 3\n",
    "    max_new_tokens: int = 1024\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result=eval_model(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "69c36606-ee7b-4fd9-bd60-468eca4bfffc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:17:17.099098Z",
     "iopub.status.busy": "2024-08-28T08:17:17.098937Z",
     "iopub.status.idle": "2024-08-28T08:17:17.101679Z",
     "shell.execute_reply": "2024-08-28T08:17:17.101394Z",
     "shell.execute_reply.started": "2024-08-28T08:17:17.099083Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"The image is a chest X-ray showing the thoracic cavity, including the lungs, heart, and the bony structures such as the ribs and the spine. A region of interest is located at left part of the image horizontally and middle part of image vertically, occupying approximately 18.5% of the total area. The lungs are the primary organs visible, with the heart situated centrally between them. The left lung is on the right side of the image, and the right lung is on the left side due to the perspective of the X-ray. There are no medical devices visible in the image.\\n\\nThe region of interest is located in the left lung, which is on the right side of the image from the viewer's perspective. This area shows an abnormal texture and possibly a difference in density compared to the surrounding lung tissue, which may indicate a lesion or other pathological change.\\n\\nThe abnormal area within the region of interest could be related to the surrounding lung tissue in terms of pathology, as diseases of the lung can often affect adjacent areas or be a localized manifestation of a more widespread condition. The proximity to the heart and the rest of the lung tissue suggests that the pathology could have implications for the function of these adjacent structures.\\n\\nCombining the information, the chest X-ray reveals an abnormal area in the left lung, which is situated on the right side of the image. This area exhibits an unusual texture and density, suggesting a lesion or other pathological change that could potentially impact the function of adjacent lung tissue and the heart.\""
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cdf16d2-375f-40c5-a499-79213667839a",
   "metadata": {},
   "source": [
    "## Test 4 Slake\n",
    "https://www.topdoctors.co.uk/medical-dictionary/pneumonia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "357826ff-f0dd-48a1-99df-f5be45d6bf70",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:17:17.102107Z",
     "iopub.status.busy": "2024-08-28T08:17:17.102035Z",
     "iopub.status.idle": "2024-08-28T08:17:31.263362Z",
     "shell.execute_reply": "2024-08-28T08:17:31.262853Z",
     "shell.execute_reply.started": "2024-08-28T08:17:17.102096Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetune-slake_orift\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:06<00:00,  1.73s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 18.3 s, sys: 28.9 s, total: 47.2 s\n",
      "Wall time: 14.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\"    \n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetune-slake_orift\"\n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://www.topdoctors.co.uk/files/Image/large/5a536fd0-0d70-4b1d-be00-3c8e25bbab96.jpg\"\n",
    "    #image_file: str = \"med_test_2000.png\"    \n",
    "    #query: str = \"What Do Chest X-Rays Show?\"\n",
    "    query: str = \"Anything abnormal in the Chest X-Ray?\"    \n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = 3\n",
    "    num_beams: int = 3\n",
    "    max_new_tokens: int = 256\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result=eval_model(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d2112578-2c8d-44e1-9706-2d82cf93d8bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:17:31.264013Z",
     "iopub.status.busy": "2024-08-28T08:17:31.263923Z",
     "iopub.status.idle": "2024-08-28T08:17:31.266829Z",
     "shell.execute_reply": "2024-08-28T08:17:31.266482Z",
     "shell.execute_reply.started": "2024-08-28T08:17:31.264001Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Yes'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41112da1-433d-417e-8723-0663a7f6f1fa",
   "metadata": {},
   "source": [
    "## Test 5 Captioner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "139b89fe-5669-4c1c-a9a0-7e22f93e1688",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:17:31.267310Z",
     "iopub.status.busy": "2024-08-28T08:17:31.267227Z",
     "iopub.status.idle": "2024-08-28T08:17:45.218976Z",
     "shell.execute_reply": "2024-08-28T08:17:45.218467Z",
     "shell.execute_reply.started": "2024-08-28T08:17:31.267299Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:05<00:00,  1.43s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 26.3 s, sys: 12.2 s, total: 38.5 s\n",
      "Wall time: 13.9 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\"    \n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift_20240817\"\n",
    "    model_base: int = None\n",
    "    #image_file:str = \"https://www.topdoctors.co.uk/files/Image/large/5a536fd0-0d70-4b1d-be00-3c8e25bbab96.jpg\"\n",
    "    image_file: str = \"med_test_2000.png\"    \n",
    "    #query: str = \"What Do Chest X-Rays Show?\"\n",
    "    query: str = \"Give me detailed description of the image, based on coarse caption, lesion region, medical knowledge\"    \n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = None\n",
    "    num_beams: int = 1\n",
    "    max_new_tokens: int = 1024\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result = eval_model(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5e611f74-32a6-412a-bb73-082a29fc0b7c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:18:59.390478Z",
     "iopub.status.busy": "2024-08-28T08:18:59.390350Z",
     "iopub.status.idle": "2024-08-28T08:18:59.393067Z",
     "shell.execute_reply": "2024-08-28T08:18:59.392585Z",
     "shell.execute_reply.started": "2024-08-28T08:18:59.390465Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6ecca2c-ffbf-47d4-8616-fb97d967a601",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b3820fa8-5041-4add-9114-af34f209520d",
   "metadata": {},
   "source": [
    "## Test 6 Slake"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "16a8e17d-8040-44d0-b352-b93b904bc131",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:33:04.636959Z",
     "iopub.status.busy": "2024-08-28T08:33:04.636809Z",
     "iopub.status.idle": "2024-08-28T08:33:13.049416Z",
     "shell.execute_reply": "2024-08-28T08:33:13.049055Z",
     "shell.execute_reply.started": "2024-08-28T08:33:04.636943Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetune-slake_orift\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:03<00:00,  1.19it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 15.5 s, sys: 11.5 s, total: 27 s\n",
      "Wall time: 8.41 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetune-slake_orift\"    \n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift_20240817\"\n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://www.topdoctors.co.uk/files/Image/large/5a536fd0-0d70-4b1d-be00-3c8e25bbab96.jpg\"\n",
    "    #image_file: str = \"med_test_2000.png\"    \n",
    "    #query: str = \"What Do Chest X-Rays Show?\"\n",
    "    query: str = \"provide a detail description for this photo without interpretations\"    \n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = None\n",
    "    num_beams: int = 1\n",
    "    max_new_tokens: int = 1024\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result = eval_model(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "63e6b297-1989-45ff-96e6-84c14d5a4e25",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:33:18.466527Z",
     "iopub.status.busy": "2024-08-28T08:33:18.466304Z",
     "iopub.status.idle": "2024-08-28T08:33:18.470794Z",
     "shell.execute_reply": "2024-08-28T08:33:18.470261Z",
     "shell.execute_reply.started": "2024-08-28T08:33:18.466501Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'X-Ray'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "945546fb-8b88-4381-963d-e24204ad9c81",
   "metadata": {},
   "source": [
    "## Test 7 Default"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16ac33ed-50d1-4211-83bf-000eb76ab58b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:49:17.186839Z",
     "iopub.status.busy": "2024-08-28T08:49:17.186616Z",
     "iopub.status.idle": "2024-08-28T08:50:32.665740Z",
     "shell.execute_reply": "2024-08-28T08:50:32.665303Z",
     "shell.execute_reply.started": "2024-08-28T08:49:17.186813Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/LLaVA-Meta-Llama-3-8B-Instruct-FT-S2\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:03<00:00,  1.08it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 1min 32s, sys: 20.8 s, total: 1min 53s\n",
      "Wall time: 1min 15s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"The image features an X-ray of a person's chest area, showing the individual's rib cage and the organs surrounding it. The x-ray clearly highlights the rib cage, which consists of numerous bones covering the chest area. This detailed structure view provides insight into the human anatomy and can be helpful for medical purposes.\""
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/LLaVA-Meta-Llama-3-8B-Instruct-FT-S2\"    \n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://www.topdoctors.co.uk/files/Image/large/5a536fd0-0d70-4b1d-be00-3c8e25bbab96.jpg\"\n",
    "    #image_file: str = \"med_test_2000.png\"    \n",
    "    #query: str = \"What Do Chest X-Rays Show?\"\n",
    "    query: str = \"provide a detail description for this photo without interpretations\"    \n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = None\n",
    "    num_beams: int = 1\n",
    "    max_new_tokens: int = 1024\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result = eval_model(args)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "451917db-a642-4a93-b5a2-19875eaa3b8b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:17:52.551314Z",
     "iopub.status.busy": "2024-08-28T08:17:52.551223Z",
     "iopub.status.idle": "2024-08-28T08:17:52.553143Z",
     "shell.execute_reply": "2024-08-28T08:17:52.552854Z",
     "shell.execute_reply.started": "2024-08-28T08:17:52.551302Z"
    }
   },
   "outputs": [],
   "source": [
    "#cd MedTrinity-25M\n",
    "#!bash ./scripts/med/llava3_med_eval_batch_vqa_rad.sh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "51d5131b-13e8-48a0-a855-10b0989a053b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-28T08:50:32.666580Z",
     "iopub.status.busy": "2024-08-28T08:50:32.666494Z",
     "iopub.status.idle": "2024-08-28T08:50:48.931547Z",
     "shell.execute_reply": "2024-08-28T08:50:48.931209Z",
     "shell.execute_reply.started": "2024-08-28T08:50:32.666568Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "conversation mode: llama3\n",
      "model name: /home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\n",
      "vision_tower openai/clip-vit-large-patch14-336, is_absolute_path_exists: False, load_delay: True\n",
      "delay load: True\n",
      "delay load and just load the config, is_loaded: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:07<00:00,  1.89s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding pad token as '<pad>'\n",
      "tokenizer's pad token id is:  128256\n",
      "[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is llama3, using llama3\n",
      "CPU times: user 53.4 s, sys: 18 s, total: 1min 11s\n",
      "Wall time: 16.3 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'The image is a chest X-ray showing the heart, diaphragm, and the majority of the lungs. A region of interest is located at left-center part of the image horizontally and middle part of image vertically, occupying approximately 24.7% of the total area. The heart is located centrally and slightly to the left, with the diaphragm beneath it. The lungs are the primary organs visible, with the left lung appearing on the right side of the image and the right lung on the left side due to the perspective of the X-ray. There are no medical lesions visible in the image.\\n\\nThe region of interest, indicated by the annotation, is located within the right lung and appears as an area with abnormal texture and possibly altered density compared to the surrounding lung tissue. This could suggest the presence of a pathological condition such as a mass, consolidation, or other lung lesion.\\n\\nThe abnormal region within the right lung may be related to the surrounding lung tissue in terms of its impact on lung function or its potential to affect adjacent structures. It is possible that the lesion could be causing a local effect on the lung parenchyma or could be indicative of a more widespread pulmonary condition.\\n\\nIn summary, the chest X-ray reveals an abnormal area within the right lung, which may have implications for lung function and could be related to or affect adjacent structures within the lung.'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "from dataclasses import dataclass\n",
    "from PIL import Image\n",
    "\n",
    "@dataclass\n",
    "class Inputs():\n",
    "    model_path: str = \"/home/pop/hosting/medical/med-model/LLaVA-Med-Captioner/llava-llama-med-8b-captioner\"    \n",
    "    #model_path: str = \"/home/pop/hosting/medical/med-model/llava-llama-med-8b-stage2-finetuned-vga_rad_orift_20240817\"\n",
    "    model_base: int = None\n",
    "    image_file:str = \"https://www.topdoctors.co.uk/files/Image/large/5a536fd0-0d70-4b1d-be00-3c8e25bbab96.jpg\"\n",
    "    #query: str = \"What Do Chest X-Rays Show?\"\n",
    "    query: str = \"Give me detailed description of the image, based on coarse caption, lesion region, medical knowledge\"    \n",
    "    conv_mode: str = \"llama3\"\n",
    "    sep: str = \",\"\n",
    "    temperature: float = 1.0\n",
    "    top_p:int = None\n",
    "    num_beams: int = 1\n",
    "    max_new_tokens: int = 1024\n",
    "    \n",
    "args = Inputs()\n",
    "print(f\"conversation mode: {args.conv_mode}\")\n",
    "print(f\"model name: {args.model_path}\")\n",
    "    \n",
    "result = eval_model(args)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8724203b-8d26-444b-ba00-dc2d576813bc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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