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import os
import random
import torch
from PIL import Image
from concurrent.futures import ThreadPoolExecutor
class PlipDataProcess(torch.utils.data.Dataset):
def __init__(self, root_dir, files, df, img_processor=None, num_tiles_per_patient=128, max_workers=64, save_dir='processed_tile_data'):
self.root_dir = root_dir
self.files = files
self.df = df
self.img_processor = img_processor
self.num_tiles_per_patient = num_tiles_per_patient
self.max_workers = max_workers
self.save_dir = save_dir
if not os.path.exists(self.save_dir):
os.makedirs(self.save_dir)
def __len__(self):
return len(self.files)
def load_and_process_image(self, tile_path):
image = Image.open(tile_path)
return self.img_processor.preprocess(image)['pixel_values']
def save_individual_tile_data(self, tile_data, file_data, file_name, tile_name):
save_path = os.path.join(self.save_dir, file_name, f"{tile_name}.pt")
os.makedirs(os.path.dirname(save_path), exist_ok=True)
torch.save({'tile_data': tile_data, 'file_data': file_data}, save_path)
def __getitem__(self, idx):
file = self.files[idx]
tiles_path = os.path.join(self.root_dir, file,)
tiles = [tile for tile in os.listdir(tiles_path) if tile != '.ipynb_checkpoints']
selected_tiles = random.sample(tiles, min(self.num_tiles_per_patient, len(tiles)))
#file_data = torch.tensor(self.df.loc[f'{file}-01'].values, dtype=torch.float32)
try:
file_data = torch.tensor(self.df.loc[f'{file}-01'].values, dtype=torch.float32)
except KeyError:
# If the file is not found in the dataframe, create a tensor of zeros
# Shape is inferred from the other rows in the dataframe
num_features = self.df.shape[1]
file_data = torch.zeros(num_features, dtype=torch.float32)
with ThreadPoolExecutor(max_workers=self.max_workers) as executor:
for tile_name in selected_tiles:
tile_path = os.path.join(tiles_path, tile_name)
executor.submit(self.process_and_save_tile, tile_path, file_data, file, tile_name)
return idx
def process_and_save_tile(self, tile_path, file_data, file_name, tile_name):
tile_data = self.load_and_process_image(tile_path)
self.save_individual_tile_data(tile_data, file_data, file_name, tile_name)
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