Computer Vision News - April 2023

29 MONAI Generative Models Google Colab setup and imports from google.colab import drive drive.mount('/content/gdrive') !python -c "import monai" || pip install -q "monai-weekly[tqdm]" !python -c "import matplotlib" || pip install -q matplotlib %matplotlib inline !git clone https://github.com/Project-MONAI/GenerativeModels.git cd GenerativeModels !python setup.py install import os import shutil import tempfile import time import matplotlib.pyplot as plt import numpy as np import torch import torch.nn.functional as F from monai import transforms from monai.config import print_config from monai.data import CacheDataset, DataLoader from monai.utils import first, set_determinism from torch.cuda.amp import GradScaler, autocast from tqdm import tqdm directory = os.environ.get("MONAI_DATA_DIRECTORY") root_dir = tempfile.mkdtemp() if directory is None else directory print(root_dir) set_determinism(42) device = torch.device("cuda" if torch.cuda.is_available() else "cpu") print(f"Using {device}") Download Decathlon dataset (Brain Tumour) from monai.apps import DecathlonDataset [ transforms.LoadImaged(keys=["image"]), transforms.Lambdad(keys="image", func=lambda x: x[:, :, :, 1]), transforms.AddChanneld(keys=["image"]), transforms.ScaleIntensityd(keys=["image"]), transforms.CenterSpatialCropd(keys=["image"], roi_size=[176, 224, 155]), transforms.Resized(keys=["image"], spatial_size=(32, 48, 32)), ] ) train_ds = DecathlonDataset( root_dir=root_dir, task="Task01_BrainTumour", transform=data_trans- form, section="training", download=True )