cyclegan

ML/Pytorch/GANs/CycleGAN/dataset.py

@@ -0,0 +1,41 @@
+from PIL import Image
+import os
+from torch.utils.data import Dataset
+import numpy as np
+
+class HorseZebraDataset(Dataset):
+    def __init__(self, root_zebra, root_horse, transform=None):
+        self.root_zebra = root_zebra
+        self.root_horse = root_horse
+        self.transform = transform
+
+        self.zebra_images = os.listdir(root_zebra)
+        self.horse_images = os.listdir(root_horse)
+        self.length_dataset = max(len(self.zebra_images), len(self.horse_images)) # 1000, 1500
+        self.zebra_len = len(self.zebra_images)
+        self.horse_len = len(self.horse_images)
+
+    def __len__(self):
+        return self.length_dataset
+
+    def __getitem__(self, index):
+        zebra_img = self.zebra_images[index % self.zebra_len]
+        horse_img = self.horse_images[index % self.horse_len]
+
+        zebra_path = os.path.join(self.root_zebra, zebra_img)
+        horse_path = os.path.join(self.root_horse, horse_img)
+
+        zebra_img = np.array(Image.open(zebra_path).convert("RGB"))
+        horse_img = np.array(Image.open(horse_path).convert("RGB"))
+
+        if self.transform:
+            augmentations = self.transform(image=zebra_img, image0=horse_img)
+            zebra_img = augmentations["image"]
+            horse_img = augmentations["image0"]
+
+        return zebra_img, horse_img
+
+
+
+
+