[IF super res] correctly normalize PIL input (huggingface#3536)

* [IF super res] correctl normalize PIL input * 175 -> 127.5
tbergman · May 26, 2023 · bdc75e7 · bdc75e7
1 parent 1d1f648
commit bdc75e7
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Showing 3 changed files with 3 additions and 3 deletions.
diff --git a/src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py b/src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py
@@ -759,7 +759,7 @@ def preprocess_image(self, image: PIL.Image.Image, num_images_per_prompt, device
             image = [image]
 
         if isinstance(image[0], PIL.Image.Image):
-            image = [np.array(i).astype(np.float32) / 255.0 for i in image]
+            image = [np.array(i).astype(np.float32) / 127.5 - 1.0 for i in image]
 
             image = np.stack(image, axis=0)  # to np
             image = torch.from_numpy(image.transpose(0, 3, 1, 2))

diff --git a/src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting_superresolution.py b/src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting_superresolution.py
@@ -795,7 +795,7 @@ def preprocess_image(self, image: PIL.Image.Image, num_images_per_prompt, device
             image = [image]
 
         if isinstance(image[0], PIL.Image.Image):
-            image = [np.array(i).astype(np.float32) / 255.0 for i in image]
+            image = [np.array(i).astype(np.float32) / 127.5 - 1.0 for i in image]
 
             image = np.stack(image, axis=0)  # to np
             image = torch.from_numpy(image.transpose(0, 3, 1, 2))

diff --git a/src/diffusers/pipelines/deepfloyd_if/pipeline_if_superresolution.py b/src/diffusers/pipelines/deepfloyd_if/pipeline_if_superresolution.py
@@ -664,7 +664,7 @@ def preprocess_image(self, image, num_images_per_prompt, device):
             image = [image]
 
         if isinstance(image[0], PIL.Image.Image):
-            image = [np.array(i).astype(np.float32) / 255.0 for i in image]
+            image = [np.array(i).astype(np.float32) / 127.5 - 1.0 for i in image]
 
             image = np.stack(image, axis=0)  # to np
             image = torch.from_numpy(image.transpose(0, 3, 1, 2))