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add lora controlnet train/gen temporarily
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@@ -1743,6 +1743,9 @@ class ControlNetDataset(BaseDataset):
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self.bucket_manager = self.dreambooth_dataset_delegate.bucket_manager
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self.buckets_indices = self.dreambooth_dataset_delegate.buckets_indices
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def cache_latents(self, vae, vae_batch_size=1, cache_to_disk=False, is_main_process=True):
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return self.dreambooth_dataset_delegate.cache_latents(vae, vae_batch_size, cache_to_disk, is_main_process)
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def __len__(self):
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return self.dreambooth_dataset_delegate.__len__()
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@@ -1775,9 +1778,14 @@ class ControlNetDataset(BaseDataset):
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h, w = target_size_hw
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cond_img = cond_img[ct : ct + h, cl : cl + w]
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else:
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assert (
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cond_img.shape[0] == self.height and cond_img.shape[1] == self.width
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), f"image size is small / 画像サイズが小さいようです: {image_info.absolute_path}"
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# assert (
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# cond_img.shape[0] == self.height and cond_img.shape[1] == self.width
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# ), f"image size is small / 画像サイズが小さいようです: {image_info.absolute_path}"
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# resize to target
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if cond_img.shape[0] != target_size_hw[0] or cond_img.shape[1] != target_size_hw[1]:
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cond_img = cv2.resize(
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cond_img, (int(target_size_hw[1]), int(target_size_hw[0])), interpolation=cv2.INTER_LANCZOS4
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)
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if flipped:
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cond_img = cond_img[:, ::-1, :].copy() # copy to avoid negative stride
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