{
"cells": [
{
"cell_type": "markdown",
"id": "16c61f54",
"metadata": {},
"source": [
"# 医用画像の超解像"
]
},
{
"cell_type": "markdown",
"id": "bdc23bae",
"metadata": {},
"source": [
"---\n",
"\n",
"\n",
"超解像は、低解像度の画像をより鮮明にするために、画像の質を向上させることを目的とした技術です。\n",
"\n",
"このプロセスは、画像処理の分野で広く研究されています。しかし、研究者がしばしば遭遇するいくつかの問題があります。 一つは、補間を利用した手法に関する問題です。補間ベースの技術は、利用可能な情報を使い、知識や経験に基づいた推測を行うことで、低解像度の画像に欠けている詳細を推定しようとします。残念ながら、このような手法では、強調された画像にシャープさや細かいディテールがなく、ぼやけた出力になってしまうことがしばしばあります。\n",
"\n",
"Stable Diffusion は、AI アルゴリズムを使用して画像のスケールを拡大するため、画像内のギャップを手動で埋めるような作業が不要になります。数百万枚の画像でトレーニングされ、高解像度の画像を正確に予測できるため、従来の画像アップスケーラーと比較してディテールが大幅に向上します。さらに、最近傍などの非深層学習技術とは異なり、Stable Diffusionは画像のコンテキストを考慮し、スケールの拡大プロセスを導くために、テキストのプロンプトを使用します。\n",
"\n",
"このノートブックでは、デモンストレーションとして、CT スキャンで取得した画像を強化する方法を紹介します。\n",
"\n",
"こちらは、中足骨を骨折した、犬の足の CT スキャンです。\n",
"\n",
"![\"CT](\"ctscan_dog.png\")
\n",
"\n",
"SageMaker Python SDK を使用して、最先端の事前学習された Stable Diffusion モデルを用いてアップスケーリングを行います。アップスケーリングは、低解像度の画像と画像を説明するテキストプロンプトが与えられた場合に、高解像度の画像を生成するタスクです。低解像度でぼやけており、ピクセル化してしまった画像を、より滑らで、鮮明で詳細な高解像度画像に変換することができます。アップスケーリングと呼ぶこのプロセスは、実際の画像でも [text-to-image Stable Diffusion モデル](https://aws.amazon.com/blogs/machine-learning/generate-images-from-text-with-the-stable-diffusion-model-on-amazon-sagemaker-jumpstart/) によって生成された画像のどちらにも適用できます。\n",
"\n",
"医療分野では、診断の改善と、放射線学で普及している CAD（Computer Aided Detection）システムによる検出をより強化する目的で、画質を向上させようとする研究が数多く行われています。さらに、アップスケーリングは、高解像度な画面に表示される低解像度画像の視覚的な品質を向上させることができます。\n",
"\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "5db28351",
"metadata": {},
"source": [
"1. [セットアップ](#1.-セットアップ)\n",
"2. [Artifacts の取得とエンドポイントのデプロイ](#2.-Artifactsの取得とエンドポイントのデプロイ)\n",
"3. [エンドポイントへのクエリとレスポンスのパース](#3.-エンドポイントへのクエリとレスポンスのパース)\n",
"4. [エンドポイントのクリーンアップ](#4.-エンドポイントのクリーンアップ)"
]
},
{
"cell_type": "markdown",
"id": "ce462973",
"metadata": {},
"source": [
"Note: このノートブックは Amazon SageMaker Studio の ml.t3.medium インスタンスとPython 3 (Data Science) カーネルを使用した環境、及び Amazon SageMaker Notebook インスタンスの conda_python3 カーネルの環境でテストしました。\n",
"\n",
"Note: ノートブックの実行が終わったら、全てのリソースを必ず削除して、課金が停止するようにしてください。[エンドポイントのクリーンアップ](#4.-エンドポイントのクリーンアップ) のコードは、作成されたモデルとエンドポイントを削除します。"
]
},
{
"cell_type": "markdown",
"id": "9ea47727",
"metadata": {},
"source": [
"### 1. セットアップ"
]
},
{
"cell_type": "markdown",
"id": "35b91e81",
"metadata": {},
"source": [
"---\n",
"ノートブックを実行する前に、セットアップのためにいくつかの初期ステップがあります。このノートブックでは最新版の sagemaker および ipywidegets が必要です。\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "25293522",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
"pytest-astropy 0.8.0 requires pytest-cov>=2.0, which is not installed.\n",
"pytest-astropy 0.8.0 requires pytest-filter-subpackage>=0.1, which is not installed.\n",
"sparkmagic 0.20.4 requires nest-asyncio==1.5.5, but you have nest-asyncio 1.5.6 which is incompatible.\n",
"docker-compose 1.29.2 requires PyYAML<6,>=3.10, but you have pyyaml 6.0 which is incompatible.\n",
"awscli 1.27.111 requires botocore==1.29.111, but you have botocore 1.29.155 which is incompatible.\n",
"awscli 1.27.111 requires PyYAML<5.5,>=3.10, but you have pyyaml 6.0 which is incompatible.\n",
"awscli 1.27.111 requires rsa<4.8,>=3.1.2, but you have rsa 4.9 which is incompatible.\n",
"aiobotocore 2.4.2 requires botocore<1.27.60,>=1.27.59, but you have botocore 1.29.155 which is incompatible.\u001b[0m\u001b[31m\n",
"\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.1.2\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
]
}
],
"source": [
"!pip install sagemaker ipywidgets --upgrade --quiet"
]
},
{
"cell_type": "markdown",
"id": "48370155",
"metadata": {},
"source": [
"#### 権限と環境変数\n",
"\n",
"---\n",
"Amazon SageMaker でモデルをホストするために、AWS サービスを利用するための権限をセットアップする必要があります。ここでは、SageMaker にアクセスできる AWS アカウントのロールとして、ノートブックに関連づけられた実行ロールを利用します。\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "90518e45",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import sagemaker, boto3, json\n",
"from sagemaker import get_execution_role\n",
"\n",
"aws_role = get_execution_role()\n",
"aws_region = boto3.Session().region_name\n",
"sess = sagemaker.Session()"
]
},
{
"cell_type": "markdown",
"id": "8f3ab601",
"metadata": {
"tags": []
},
"source": [
"### 2. Artifactsの取得とエンドポイントのデプロイ\n",
"\n",
"***\n",
"Amazon SageMaker では、Hugging Face モデルを利用した 学習、Fine-tuning、推論が可能です。学習と推論の両方に Hugging Face を利用できます。\n",
"この機能は、Hugging Face AWS Deep Learning コンテナ を通して利用します。これらのコンテナには、Hugging Face Transformers、Tokenizers、Datasets ライブラリが含まれており、学習や推論ジョブのために使用できます。利用可能な Deep Learning コンテナイメージのリストについては、[利用可能な Deep Learning コンテナイメージ](https://github.com/aws/deep-learning-containers/blob/master/available_images.md)をご覧ください。こららのコンテナイメージはメンテナンスされており、セキュリティパッチが定期的に更新されます。\n",
"\n",
"Hugging Face Deep Learning コンテナを SageMaker Python SDKで学習のために利用するには、SageMaker の [Hugging Face Estimator](https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/sagemaker.huggingface.html) をご覧ください。Hugging Face Estimator を利用することで、Hugging Face のモデルを、他の SageMaker Estimator と同様に使用できますが、\n",
"SageMaker Python SDK は 1 つの選択肢であり、AWS CLI と AWS SDK for Python (boto3) を使用して、Hugging Face Deep Learning コンテナの使用を管理することもできます。\n",
"\n",
"このノートブックでは、Stable Diffusion x4 upscaler を使用します。モデルカードは [こちら](https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler) から入手できます。\n",
"\n",
"SageMaker を活用すると、新しいデータセットで最初にFine-tuningを実施しなくとも、事前学習されたモデルで推論を実行できます。まずは、事前学習済みのモデルとして、\n",
"`deploy_image_uri`, `deploy_source_uri`, そして `model_uri` を取得します。このモデルをホストするために、[`sagemaker.model.Model`](https://sagemaker.readthedocs.io/en/stable/api/inference/model.html) を作成し、デプロイします。この処理には、数分間かかります。\n",
"\n",
"***"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a8a79ec9",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"----------!"
]
}
],
"source": [
"from sagemaker import image_uris, model_uris, script_uris, hyperparameters\n",
"from sagemaker.model import Model\n",
"from sagemaker.predictor import Predictor\n",
"from sagemaker.utils import name_from_base\n",
"\n",
"(model_id, model_version,) = (\n",
" \"model-upscaling-stabilityai-stable-diffusion-x4-upscaler-fp16\",\n",
" \"*\",\n",
")\n",
"\n",
"endpoint_name = name_from_base(f\"medical-example-{model_id}\")\n",
"\n",
"# GPUメモリの多いインスタンスほど、より大きな画像の生成が可能です。\n",
"# 非常に大きな画像を生成したい場合、たとえば ml.g5.2xlarge などのインスタンスタイプを選択してください。\n",
"inference_instance_type = \"ml.p3.2xlarge\"\n",
"\n",
"# 推論用の Docker コンテナ URI を取得します。上記モデルのためのベースとなる、HuggingFaceコンテナイメージです。\n",
"deploy_image_uri = image_uris.retrieve(\n",
" region=None,\n",
" framework=None, # automatically inferred from model_id\n",
" image_scope=\"inference\",\n",
" model_id=model_id,\n",
" model_version=model_version,\n",
" instance_type=inference_instance_type,\n",
")\n",
"\n",
"# 推論用のスクリプト URIを取得します。モデルをロードし、推論を実行するためのスクリプトと依存ライブラリが含まれます。\n",
"deploy_source_uri = script_uris.retrieve(\n",
" model_id=model_id, model_version=model_version, script_scope=\"inference\"\n",
")\n",
"\n",
"# モデルのURIを取得します。事前学習済みのモデルとそのパラメータが含まれます。\n",
"model_uri = model_uris.retrieve(\n",
" model_id=model_id, model_version=model_version, model_scope=\"inference\"\n",
")\n",
"\n",
"# SageMakerのモデルを作成します。\n",
"model = Model(\n",
" image_uri=deploy_image_uri,\n",
" source_dir=deploy_source_uri,\n",
" model_data=model_uri,\n",
" entry_point=\"inference.py\", # entry point file in source_dir and present in deploy_source_uri\n",
" role=aws_role,\n",
" predictor_cls=Predictor,\n",
" name=endpoint_name,\n",
")\n",
"\n",
"# モデルをデプロイします。\n",
"# SageMaker APIを通して推論を実行するためには、Modelクラスを通してモデルをデプロイする場合、Predictorクラスを使う必要があります。\n",
"model_predictor = model.deploy(\n",
" initial_instance_count=1,\n",
" instance_type=inference_instance_type,\n",
" predictor_cls=Predictor,\n",
" endpoint_name=endpoint_name,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "665dfbe4-2857-484e-8179-3ad11307822c",
"metadata": {},
"source": [
"### 3. エンドポイントへのクエリとレスポンスのパース\n",
"\n",
"---\n",
"エンドポイントへの入力は、`utf-8` 形式でエンコードされた、プロンプト、低解像度の画像、`json` 形式の画像生成のパラメータです。エンドポイントからの出力は、生成された画像と入力されたプロンプトであり、`json` 形式です。\n",
"\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "7cd63c69-1a6a-4f33-a90e-f73a172b1685",
"metadata": {
"tags": []
},
"source": [
"#### 3.1 低解像度画像のサンプルのダウンロード\n",
"---\n",
"これから修正したい、低解像度の画像を見てみましょう。\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "85c19342-3a7a-4c01-844c-0937828bba7c",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"image/jpeg": 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\n",
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {
"image/jpeg": {
"height": 632,
"width": 632
}
},
"output_type": "execute_result"
}
],
"source": [
"from IPython.display import Image\n",
"\n",
"low_res_img_file_name = \"ctscan.jpg\"\n",
"\n",
"# 元の画像を表示します。\n",
"Image(filename=low_res_img_file_name, width=632, height=632)"
]
},
{
"cell_type": "markdown",
"id": "7fb5f775-c73c-4a19-a581-9f9db30238d6",
"metadata": {},
"source": [
"次に、エンドポイントへのクエリと、レスポンスのパース、生成された画像を表示するための helper関数を記述します。"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "84fb30d0",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"\n",
"def query(model_predictor, payload, content_type, accept):\n",
" \"\"\"Query the model predictor.\"\"\"\n",
"\n",
" query_response = model_predictor.predict(\n",
" payload,\n",
" {\n",
" \"ContentType\": content_type,\n",
" \"Accept\": accept,\n",
" },\n",
" )\n",
" return query_response\n",
"\n",
"\n",
"def parse_response(query_response):\n",
" \"\"\"Parse response and return the generated images and prompt.\"\"\"\n",
"\n",
" response_dict = json.loads(query_response)\n",
" return response_dict[\"generated_images\"], response_dict[\"prompt\"]\n",
"\n",
"\n",
"def display_img_and_prompt(img, prmpt):\n",
" \"\"\"Display the generated image.\"\"\"\n",
" plt.figure(figsize=(12, 12))\n",
" plt.imshow(np.array(img))\n",
" plt.axis(\"off\")\n",
" plt.title(prmpt)\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"id": "aea0434b",
"metadata": {},
"source": [
"---\n",
"以下に、低解像度の画像とプロンプトの例を示します。任意のテキストと画像を入力でき、モデルはアップスケールした画像を生成します。元の画像の 4 倍のサイズの画像を生成することに注意してください。非常に大きな画像を入力すると、CUDAメモリの問題が発生する可能性があります。この問題に対処するには、解像度の低い画像を入力するか、ml.g5.2xlarge のような CUDA メモリが大きいインスタンスタイプを選んでください。\n",
"\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "91227eb6-ca25-49a4-8562-6e2f46180403",
"metadata": {},
"source": [
"#### サポートされるパラメータ\n",
"\n",
"***\n",
"このモデルは、推論を実行する際に以下に示す多くのパラメータをサポートします。\n",
"\n",
"* **prompt**: 画像生成をガイドするプロンプトです。文字列または文字列のリストを指定する必要があります。\n",
"* **num_inference_steps**: 画像生成時のノイズ除去ステップ数です。ステップ数が多いほど高画質になります。正の整数である必要があります。\n",
"* **guidance_scale**: 大きい値を指定すると画質が犠牲にする代わりに、プロンプトに近い画像を生成します。1 以下の guidance_scale は無視されます。\n",
"* **negative_prompt**: このプロンプトに反する様に画像生成をガイドします。文字列または文字列のリストである必要があり、guidance_scaleと共に使用されます。guidance_scaleが無効の場合、negative_promptも無効になります。さらに、promptが文字列のリストである場合、nagetive_promptも文字列のリストである必要があります。 \n",
"* **seed**: 再現性のために、ランダム化された状態を固定します。指定する場合、整数である必要があります。\n",
"* **noise_level**: アップスケールする前に潜在ベクトルにノイズを加えます。指定する場合、整数である必要があります。\n",
"\n",
"***"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "4fd0a997-d41d-48af-851c-740d5f66d55f",
"metadata": {
"pycharm": {
"is_executing": true
},
"tags": []
},
"outputs": [],
"source": [
"import base64\n",
"from PIL import Image\n",
"from io import BytesIO\n",
"\n",
"\n",
"# content_type = 'application/json;jpeg' を指定します。エンドポイントは、低解像度の jpeg 画像を base64.b64 形式でエンコードしたバイト列を含む json を payload として受け取ります。\n",
"# raw画像をエンドポイントに送信するには、content_type = 'application/json' を指定し、encoded_image に np.array(PIL.Image.open('low_res_image.jpg')).tolist() を設定します。\n",
"content_type = \"application/json;jpeg\"\n",
"\n",
"\n",
"# 低解像度画像の高さと幅が 2 の累乗となるように、画像を再スケーリングすることをお勧めします。\n",
"# original_image = Image.open('low_res_image.jpg'); rescaled_image = original_image.rescale((128,128)); rescaled_image.save('rescaled_image.jpg') のように処理できます。\n",
"# このチュートリアルで使用するサンプル画像のサイズは 128x128 です。\n",
"with open(low_res_img_file_name, \"rb\") as f:\n",
" low_res_image_bytes = f.read()\n",
"encoded_image = base64.b64encode(bytearray(low_res_image_bytes)).decode()\n",
"\n",
"payload = {\n",
" \"prompt\": \"xray ct scan\",\n",
" \"image\": encoded_image,\n",
" \"num_inference_steps\": 500,\n",
" \"guidance_scale\": 3,\n",
"}\n",
"\n",
"# accept = 'application/json;jpeg'の場合、エンドポイントはjpeg画像をbase64.b64形式でエンコードしたバイト列として返します。\n",
"# raw 画像を rgb 値で受け取る場合、accept = 'application/json' をセットします。\n",
"accept = \"application/json;jpeg\"\n",
"\n",
"# raw/rgb 値でペイロードを送受信すると、SageMaker の入力ペイロードとレスポンスのサイズの制限に当たる可能性があることに注意してください。\n",
"\n",
"query_response = query(model_predictor, json.dumps(payload).encode(\"utf-8\"), content_type, accept)\n",
"generated_images, prompt = parse_response(query_response)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "93408e6a-9295-4c6a-a759-3e0454983691",
"metadata": {
"pycharm": {
"is_executing": true
},
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"import matplotlib.image as mpimg\n",
"from matplotlib import rcParams\n",
"\n",
"%matplotlib inline\n",
"\n",
"# 図形サイズのオプション\n",
"rcParams['figure.figsize'] = 11 ,8\n",
"\n",
"# 上で言及したように accept = 'application/json;jpeg' のため、画像は base64.b64 形式でエンコードされたバイト列の jpeg です。\n",
"# ここでは、画像をデコードし表示します。\n",
"for generated_image in generated_images:\n",
" generated_image_decoded = BytesIO(base64.b64decode(generated_image.encode()))\n",
" generated_image_rgb = Image.open(generated_image_decoded).convert(\"RGB\")\n",
"\n",
" img_enhanced_name = 'upscaled_ctscan.jpg'\n",
" generated_image_rgb.save(img_enhanced_name)\n",
" # read images\n",
" img_original = mpimg.imread(low_res_img_file_name)\n",
" img_enhanced = mpimg.imread(img_enhanced_name)\n",
"\n",
" # display images\n",
" fig, ax = plt.subplots(1,2)\n",
" ax[0].imshow(img_original)\n",
" ax[0].title.set_text('Original')\n",
" ax[1].imshow(img_enhanced)\n",
" ax[1].title.set_text('Improved Resolution')\n",
" "
]
},
{
"cell_type": "markdown",
"id": "870d1173",
"metadata": {},
"source": [
"### 4. エンドポイントのクリーンアップ\n",
"\n",
"***\n",
"ノートブックを完了したら、コストの発生を停止するため、作成された全てのリソースが削除されたことを確認してください。\n",
"***"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "63cb143b",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# SageMaker endpoint の削除\n",
"#model_predictor.delete_model()\n",
"#model_predictor.delete_endpoint()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "08d74cb8-9859-4cd6-9e7d-23d4e1b2a081",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"availableInstances": [
{
"_defaultOrder": 0,
"_isFastLaunch": true,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 4,
"name": "ml.t3.medium",
"vcpuNum": 2
},
{
"_defaultOrder": 1,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 8,
"name": "ml.t3.large",
"vcpuNum": 2
},
{
"_defaultOrder": 2,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 16,
"name": "ml.t3.xlarge",
"vcpuNum": 4
},
{
"_defaultOrder": 3,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 32,
"name": "ml.t3.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 4,
"_isFastLaunch": true,
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