fix_image_resize

diffsynth/data/simple_text_image.py

@@ -1,4 +1,4 @@
-import torch, os
+import torch, os, torchvision
 from torchvision import transforms
 import pandas as pd
 from PIL import Image
@@ -11,9 +11,10 @@ class TextImageDataset(torch.utils.data.Dataset):
         metadata = pd.read_csv(os.path.join(dataset_path, "train/metadata.csv"))
         self.path = [os.path.join(dataset_path, "train", file_name) for file_name in metadata["file_name"]]
         self.text = metadata["text"].to_list()
+        self.height = height
+        self.width = width
         self.image_processor = transforms.Compose(
             [
-                transforms.Resize(max(height, width), interpolation=transforms.InterpolationMode.BILINEAR),
                 transforms.CenterCrop((height, width)) if center_crop else transforms.RandomCrop((height, width)),
                 transforms.RandomHorizontalFlip() if random_flip else transforms.Lambda(lambda x: x),
                 transforms.ToTensor(),
@@ -27,6 +28,11 @@ class TextImageDataset(torch.utils.data.Dataset):
         data_id = (data_id + index) % len(self.path) # For fixed seed.
         text = self.text[data_id]
         image = Image.open(self.path[data_id]).convert("RGB")
+        target_height, target_width = self.height, self.width
+        width, height = image.size
+        scale = max(target_width / width, target_height / height)
+        shape = [round(height*scale),round(width*scale)]
+        image = torchvision.transforms.functional.resize(image,shape,interpolation=transforms.InterpolationMode.BILINEAR)
         image = self.image_processor(image)
         return {"text": text, "image": image}