diff --git a/2d_regression/image_restoration.ipynb b/2d_regression/image_restoration.ipynb new file mode 100644 index 000000000..8848a6230 --- /dev/null +++ b/2d_regression/image_restoration.ipynb @@ -0,0 +1,690 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "DpAWjuE0zX__" + }, + "source": [ + "Copyright (c) MONAI Consortium \n", + "Licensed under the Apache License, Version 2.0 (the \"License\"); \n", + "you may not use this file except in compliance with the License. \n", + "You may obtain a copy of the License at \n", + "    http://www.apache.org/licenses/LICENSE-2.0 \n", + "Unless required by applicable law or agreed to in writing, software \n", + "distributed under the License is distributed on an \"AS IS\" BASIS, \n", + "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n", + "See the License for the specific language governing permissions and \n", + "limitations under the License.\n", + "\n", + "# Image Restoration with Restormer in MONAI\n", + "\n", + "## Introduction\n", + "\n", + "Image restoration is the process of reconstructing a high-quality image by removing degradations (e.g., noise, blur, movement) from a degraded image. Imperfections frequently manifest as speckle, streaks, intensity variations across the image, or motion blur, all of which can mask vital clues. Image restoration aims to remove these imperfections and enhance the image's visual quality and information content. In fields like medical imaging, the ability to refine visual data via restoration is of paramount importance, as enhancing clarity and information content directly impacts the reliability of diagnoses and subsequent treatment planning. \n", + "\n", + "In recent years, data-driven Deep Learning architectures are setting the new benchmark in image restoration, leveraging vast datasets to learn complex patterns, significantly outpacing conventional restoration techniques in performance. A key innovation driving this progress comes from the Transformer architecture, due to its capacity for capturing long-range dependencies. \n", + "\n", + "Building on this foundation, models like Restormer demonstrate how Transformer-based designs can be effectively adapted to understand and reconstruct complex image details during restoration. The Restormer implements a computationally efficient channel attention to tackle image restoration, achieving state-of-the-art performance. Briefly, the Restormer employs a multi-scale architecture, incorporating a Transformer-based encoder-decoder with skip connections and a cross-attention mechanism. This design allows the model to capture both local and global contextual information, making it well-suited for complex image restoration tasks (see [Restormer: Efficient Transformer for High-Resolution Image Restoration](https://arxiv.org/abs/2111.09881)). Thus, we will leverage this model from the MONAI framework to demonstrate its capabilities in image restoration.\n", + "\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Project-MONAI/tutorials/blob/main/2d_regression/image_restoration.ipynb)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lI6G5tLMzqUM" + }, + "source": [ + "## Setup environment\n", + "\n", + "We will install the latest `dev` branch of MONAI where the Restormer is available. Also, we use `pip install` with the `BUILD_MONAI=1` flag. This will fetch the most recent source code from the MONAI repository's development branch, build MONAI's C++/CUDA extensions, and install the package.\n", + "\n", + "Setting `env BUILD_MONAI=1` ensures that when calling the relevant Python modules, MONAI will prefer those extensions instead of the PyTorch/Python native implementations.\n", + "\n", + "(The compilation may take a few to 10+ minutes.)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "7qsy3BznrPsT", + "outputId": "50977b31-1da3-4e53-ff34-dd1a8ddfa9e6" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "env: BUILD_MONAI=1\n" + ] + } + ], + "source": [ + "%env BUILD_MONAI=1\n", + "!python -c \"import monai\" || pip install -q monai-weekly" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HSGmeSK8zy4C" + }, + "source": [ + "## Setup imports" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9a4y9P06TzmR", + "outputId": "fed609e0-8c23-409f-fb9b-7e1f838d46f1" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MONAI version: 1.5.dev2518\n", + "Numpy version: 2.2.5\n", + "Pytorch version: 2.7.0\n", + "MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False\n", + "MONAI rev id: 09b361dbe4c2be5289c7e2d2f6c10c5166eee273\n", + "MONAI __file__: /Users//miniconda3/envs/monai_dev/lib/python3.10/site-packages/monai/__init__.py\n", + "\n", + "Optional dependencies:\n", + "Pytorch Ignite version: 0.4.11\n", + "ITK version: 5.4.3\n", + "Nibabel version: 5.3.2\n", + "scikit-image version: 0.25.2\n", + "scipy version: 1.15.2\n", + "Pillow version: 11.2.1\n", + "Tensorboard version: 2.19.0\n", + "gdown version: 5.2.0\n", + "TorchVision version: 0.22.0\n", + "tqdm version: 4.67.1\n", + "lmdb version: 1.6.2\n", + "psutil version: 7.0.0\n", + "pandas version: 2.2.3\n", + "einops version: 0.8.1\n", + "transformers version: 4.40.2\n", + "mlflow version: 2.22.0\n", + "pynrrd version: 1.1.3\n", + "clearml version: 2.0.0rc0\n", + "\n", + "For details about installing the optional dependencies, please visit:\n", + " https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n", + "\n" + ] + } + ], + "source": [ + "from monai.utils import set_determinism, first\n", + "from monai.transforms import (\n", + " EnsureChannelFirstD,\n", + " Compose,\n", + " LoadImageD,\n", + " ScaleIntensityd,\n", + " RandGaussianNoiseD,\n", + " RandGaussianSmoothD,\n", + ")\n", + "from monai.config import print_config\n", + "from monai.data import DataLoader, Dataset, CacheDataset\n", + "from monai.networks.nets.restormer import Restormer\n", + "from monai.apps import MedNISTDataset\n", + "from monai.losses import SSIMLoss\n", + "\n", + "import os\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "import tempfile\n", + "\n", + "\n", + "print_config()\n", + "set_determinism(42)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IEdRdq0NUQj_" + }, + "source": [ + "# Construct Pairwise Training Inputs for Restoration\n", + "\n", + "We use the `MedNISTDataset` object to download and unzip the actual data files. We select the hand X-ray class for this demonstration.\n", + "\n", + "To create training pairs suitable for an image restoration task, we structure our data dictionaries with two keys: `\"original_hand\"` and `\"noisy_hand\"`. Initially, both keys point to the same clean hand X-ray image path.\n", + "\n", + "During the data loading and transformation pipeline:\n", + "1. The `\"original_hand\"` image serves as the clean, high-quality target image.\n", + "2. The `\"noisy_hand\"` image, initially identical to the original one, undergoes a series of **random synthetic degradations**. For this small example, we apply common degradations like Gaussian noise and Gaussian blur (smoothing) specifically to the `\"noisy_hand\"`. This simulates realistic scenarios where images might be corrupted by sensor noise, motion blur, or varying acquisition settings." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "H9KlURISUxcr", + "outputId": "51492daa-0cc9-41d2-b71f-d0ee4b117da9" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "MedNIST.tar.gz: 59.0MB [00:02, 28.6MB/s] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-22 08:47:35,940 - INFO - Downloaded: /var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST.tar.gz\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-22 08:47:36,048 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n", + "2025-05-22 08:47:36,049 - INFO - Writing into directory: /var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading dataset: 100%|██████████| 47164/47164 [00:00<00:00, 270330.68it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " first training items: [{'original_hand': '/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST/Hand/001727.jpeg', 'noisy_hand': '/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST/Hand/001727.jpeg'}, {'original_hand': '/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST/Hand/009015.jpeg', 'noisy_hand': '/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST/Hand/009015.jpeg'}, {'original_hand': '/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST/Hand/007610.jpeg', 'noisy_hand': '/var/folders/l9/mzf3xz016nn449t2nlqp0k680000gn/T/tmpyd0u90wu/MedNIST/Hand/007610.jpeg'}]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n", + "if directory is not None:\n", + " os.makedirs(directory, exist_ok=True)\n", + "root_dir = tempfile.mkdtemp() if directory is None else directory\n", + "print(root_dir)\n", + "\n", + "train_data = MedNISTDataset(root_dir=root_dir, section=\"training\", download=True, transform=None)\n", + "training_datadict = [\n", + " {\"original_hand\": item[\"image\"], \"noisy_hand\": item[\"image\"]}\n", + " for item in train_data.data\n", + " if item[\"label\"] == 4 # label 4 is for xray hands\n", + "]\n", + "print(\"\\n first training items: \", training_datadict[:3])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "QZJCeerKTu3s" + }, + "outputs": [], + "source": [ + "img_keys = [\"original_hand\", \"noisy_hand\"]\n", + "degradation_key = \"noisy_hand\"\n", + "\n", + "\n", + "train_transforms = Compose(\n", + " [\n", + " LoadImageD(keys=img_keys),\n", + " EnsureChannelFirstD(keys=img_keys),\n", + " ScaleIntensityd(keys=img_keys),\n", + " RandGaussianNoiseD(keys=[degradation_key], prob=0.5, std=0.1),\n", + " RandGaussianSmoothD(keys=[degradation_key], prob=0.5, sigma_x=(0.5, 1.5), sigma_y=(0.5, 1.5)),\n", + " ScaleIntensityd(keys=img_keys),\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vUKGXidL2ViQ" + }, + "source": [ + "## Visualisation of the training pairs" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 402 + }, + "id": "LzFV9LY8VXy1", + "outputId": "1444374e-0f51-4485-8ff8-4e1879fc03a4" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "noisy_image shape: torch.Size([64, 64])\n", + "original_image shape: torch.Size([64, 64])\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "check_ds = Dataset(data=training_datadict, transform=train_transforms)\n", + "check_loader = DataLoader(check_ds, batch_size=1, shuffle=True)\n", + "check_data = first(check_loader)\n", + "original_image = check_data[\"original_hand\"][0][0]\n", + "noisy_image = check_data[\"noisy_hand\"][0][0]\n", + "\n", + "print(f\"noisy_image shape: {noisy_image.shape}\")\n", + "print(f\"original_image shape: {original_image.shape}\")\n", + "\n", + "plt.figure(\"check\", (12, 6))\n", + "plt.subplot(1, 2, 1)\n", + "plt.title(\"noisy_image\")\n", + "plt.imshow(noisy_image, cmap=\"gray\")\n", + "plt.subplot(1, 2, 2)\n", + "plt.title(\"original_image\")\n", + "plt.imshow(original_image, cmap=\"gray\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nwO0Q3Hg2hOJ" + }, + "source": [ + "## Create the training pipelines\n", + "\n", + "We use a `CacheDataset` to capture the training pairs and accelerate the training process. The MedNISTDataset provides pairs of \"noisy\" and \"original\" images. For demonstration purposes, we treat this as an image restoration problem: the \"noisy\" image is a degraded version of the \"original\" reference image (e.g., due to simulated movement or noise). The goal is to restore the noisy image to match the original image.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "DjSwFJJvW7Qc", + "outputId": "d81e0f01-4ec7-4cd4-bd7f-645a1f5dfc9f" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading dataset: 100%|██████████| 1000/1000 [00:00<00:00, 1600.61it/s]\n" + ] + } + ], + "source": [ + "train_ds = CacheDataset(data=training_datadict[:1000], transform=train_transforms, cache_rate=1.0, num_workers=0)\n", + "train_loader = DataLoader(train_ds, batch_size=16, shuffle=True, num_workers=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gx6GD9X_shGO" + }, + "source": [ + "## Model and Training\n", + "\n", + "Now, let's initialize the Restormer model and train it to restore the noisy images. Since this is just a tutorial, we will initialize a small Restormer model with a small size configuration for quick experimentation: \n", + "\n", + "- `dim=32`: the embedding dimension (feature width) at the first stage.\n", + "- `num_blocks=[2, 2]`: 2 encoder and 2 decoder blocks.\n", + "- `num_heads=[2, 2]`: 2 attention heads at each stage.\n", + "- `refinement=1`: 1 refinement block at the bottleneck.\n", + "\n", + "When training image restoration models, common regression losses include `MSELoss`, `PSNRLoss`, and `SSIMLoss`. Here, we use `SSIMLoss` because it encourages the model to focus on matching the structural similarity (shape and details) of the hands, rather than just restoring absolute pixel values.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "zHAj8nuHXG-D", + "outputId": "462d37f3-b59e-4d88-ca18-60224f69076d" + }, + "outputs": [], + "source": [ + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + "elif torch.backends.mps.is_available():\n", + " device = torch.device(\"mps\")\n", + "else:\n", + " device = torch.device(\"cpu\")\n", + "\n", + "model = Restormer(\n", + " spatial_dims=2,\n", + " in_channels=1,\n", + " out_channels=1,\n", + " dim=32,\n", + " num_blocks=[2, 2],\n", + " heads=[2, 2],\n", + " num_refinement_blocks=1,\n", + ").to(device)\n", + "image_loss = SSIMLoss(spatial_dims=2, data_range=1.0)\n", + "optimizer = torch.optim.Adam(model.parameters(), 1e-5)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0a7hoesI29m4" + }, + "source": [ + "## The training loops" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "eyiL4ccmYsjt" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'Epoch': 1, 'Avg Epoch Loss': '0.8336'}\n", + "{'Epoch': 2, 'Avg Epoch Loss': '0.7150'}\n", + "{'Epoch': 3, 'Avg Epoch Loss': '0.6269'}\n", + "{'Epoch': 4, 'Avg Epoch Loss': '0.5621'}\n", + "{'Epoch': 5, 'Avg Epoch Loss': '0.5125'}\n", + "{'Epoch': 6, 'Avg Epoch Loss': '0.4738'}\n", + "{'Epoch': 7, 'Avg Epoch Loss': '0.4314'}\n", + "{'Epoch': 8, 'Avg Epoch Loss': '0.3770'}\n", + "{'Epoch': 9, 'Avg Epoch Loss': '0.2988'}\n", + "{'Epoch': 10, 'Avg Epoch Loss': '0.2397'}\n", + "{'Epoch': 11, 'Avg Epoch Loss': '0.2179'}\n", + "{'Epoch': 12, 'Avg Epoch Loss': '0.2028'}\n", + "{'Epoch': 13, 'Avg Epoch Loss': '0.1915'}\n", + "{'Epoch': 14, 'Avg Epoch Loss': '0.1799'}\n", + "{'Epoch': 15, 'Avg Epoch Loss': '0.1732'}\n", + "{'Epoch': 16, 'Avg Epoch Loss': '0.1634'}\n", + "{'Epoch': 17, 'Avg Epoch Loss': '0.1560'}\n", + "{'Epoch': 18, 'Avg Epoch Loss': '0.1492'}\n", + "{'Epoch': 19, 'Avg Epoch Loss': '0.1438'}\n", + "{'Epoch': 20, 'Avg Epoch Loss': '0.1391'}\n", + "{'Epoch': 21, 'Avg Epoch Loss': '0.1323'}\n", + "{'Epoch': 22, 'Avg Epoch Loss': '0.1317'}\n", + "{'Epoch': 23, 'Avg Epoch Loss': '0.1247'}\n", + "{'Epoch': 24, 'Avg Epoch Loss': '0.1218'}\n", + "{'Epoch': 25, 'Avg Epoch Loss': '0.1203'}\n", + "{'Epoch': 26, 'Avg Epoch Loss': '0.1173'}\n", + "{'Epoch': 27, 'Avg Epoch Loss': '0.1134'}\n", + "{'Epoch': 28, 'Avg Epoch Loss': '0.1142'}\n", + "{'Epoch': 29, 'Avg Epoch Loss': '0.1100'}\n", + "{'Epoch': 30, 'Avg Epoch Loss': '0.1080'}\n", + "{'Epoch': 31, 'Avg Epoch Loss': '0.1066'}\n", + "{'Epoch': 32, 'Avg Epoch Loss': '0.1033'}\n", + "{'Epoch': 33, 'Avg Epoch Loss': '0.1009'}\n", + "{'Epoch': 34, 'Avg Epoch Loss': '0.0987'}\n", + "{'Epoch': 35, 'Avg Epoch Loss': '0.0996'}\n", + "{'Epoch': 36, 'Avg Epoch Loss': '0.0956'}\n", + "{'Epoch': 37, 'Avg Epoch Loss': '0.0948'}\n", + "{'Epoch': 38, 'Avg Epoch Loss': '0.0948'}\n", + "{'Epoch': 39, 'Avg Epoch Loss': '0.0945'}\n", + "{'Epoch': 40, 'Avg Epoch Loss': '0.0928'}\n", + "{'Epoch': 41, 'Avg Epoch Loss': '0.0891'}\n", + "{'Epoch': 42, 'Avg Epoch Loss': '0.0886'}\n", + "{'Epoch': 43, 'Avg Epoch Loss': '0.0870'}\n", + "{'Epoch': 44, 'Avg Epoch Loss': '0.0905'}\n", + "{'Epoch': 45, 'Avg Epoch Loss': '0.0868'}\n", + "{'Epoch': 46, 'Avg Epoch Loss': '0.0874'}\n", + "{'Epoch': 47, 'Avg Epoch Loss': '0.0844'}\n", + "{'Epoch': 48, 'Avg Epoch Loss': '0.0847'}\n", + "{'Epoch': 49, 'Avg Epoch Loss': '0.0834'}\n", + "{'Epoch': 50, 'Avg Epoch Loss': '0.0821'}\n" + ] + } + ], + "source": [ + "max_epochs = 50\n", + "epoch_loss_values = []\n", + "\n", + "\n", + "for epoch in range(max_epochs):\n", + " model.train()\n", + " epoch_loss, step = 0, 0\n", + "\n", + " # No inner tqdm bar here\n", + " for batch_data in train_loader:\n", + " step += 1\n", + " optimizer.zero_grad()\n", + "\n", + " noisy = batch_data[\"noisy_hand\"].to(device)\n", + " original = batch_data[\"original_hand\"].to(device)\n", + " pred_image = model(noisy)\n", + " pred_image = torch.sigmoid(pred_image)\n", + "\n", + " loss = image_loss(input=pred_image, target=original)\n", + " loss.backward()\n", + " optimizer.step()\n", + " current_loss = loss.item()\n", + " epoch_loss += current_loss\n", + "\n", + " epoch_loss /= step\n", + " epoch_loss_values.append(epoch_loss)\n", + "\n", + " # Update the outer bar's postfix with the final average epoch loss\n", + " print({\"Epoch\": epoch + 1, \"Avg Epoch Loss\": f\"{epoch_loss:.4f}\"})" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 282 + }, + "id": "hZYvG_oE32-9", + "outputId": "354e2e53-85ae-4d48-a388-6206bc16e3f9" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "plt.plot(epoch_loss_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dEfFYtwgqy6i" + }, + "source": [ + "# Visualise some validation results\n", + "This section creates a set of previously unseen pairs of noisy vs original hands,\n", + "and use the network to predict the transformation between each pair." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Qgxi6nsQn1om", + "outputId": "5c58700b-39c5-4435-a0b1-2d776e46c46b" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading dataset: 100%|██████████| 500/500 [00:00<00:00, 852.19it/s]\n" + ] + } + ], + "source": [ + "val_ds = CacheDataset(data=training_datadict[2000:2500], transform=train_transforms, cache_rate=1.0, num_workers=0)\n", + "val_loader = DataLoader(val_ds, batch_size=16, num_workers=0)\n", + "model.eval() # Set model to evaluation mode\n", + "\n", + "with torch.no_grad(): # Disable gradient calculation for inference\n", + " for batch_data in val_loader:\n", + " noisy = batch_data[\"noisy_hand\"].to(device)\n", + " original = batch_data[\"original_hand\"].to(device)\n", + " # Pass only the noisy image, consistent with training\n", + " pred_image = model(noisy)\n", + " pred_image = torch.sigmoid(pred_image)\n", + " break # Process only the first batch for visualization\n", + "\n", + "original_image = original.detach().cpu().numpy()[:, 0]\n", + "noisy_image = noisy.detach().cpu().numpy()[:, 0]\n", + "pred_image = pred_image.detach().cpu().numpy()[:, 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 591 + }, + "id": "Sz-lwwv-oIZ6", + "outputId": "b6583ea8-f5e8-418b-f369-ba8dcc851ffe" + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "batch_size = 5\n", + "plt.subplots(batch_size, 3, figsize=(8, 10))\n", + "for b in range(batch_size):\n", + " # noisy image\n", + " plt.subplot(batch_size, 3, b * 3 + 1)\n", + " plt.axis(\"off\")\n", + " plt.title(\"noisy image\")\n", + " plt.imshow(noisy_image[b], cmap=\"gray\")\n", + " # original image\n", + " plt.subplot(batch_size, 3, b * 3 + 2)\n", + " plt.axis(\"off\")\n", + " plt.title(\"original image\")\n", + " plt.imshow(original_image[b], cmap=\"gray\")\n", + " # predicted restored image\n", + " plt.subplot(batch_size, 3, b * 3 + 3)\n", + " plt.axis(\"off\")\n", + " plt.title(\"predicted image\")\n", + " plt.imshow(pred_image[b], cmap=\"gray\")\n", + "plt.axis(\"off\")\n", + "plt.show()" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "name": "registration_simple.ipynb", + "provenance": [], + "toc_visible": true + }, + "kernelspec": { + "display_name": "monai_dev", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.17" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +}