Check whether rescale is requested before checking is_scaled_image (#35439)

examples/modular-transformers/image_processing_new_imgproc_model.py

@@ -247,7 +247,7 @@ class ImgprocModelImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/beit/image_processing_beit.py

@@ -239,7 +239,7 @@ class BeitImageProcessor(BaseImageProcessor):
         """Preprocesses a single image."""
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/bit/image_processing_bit.py

@@ -284,7 +284,7 @@ class BitImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/blip/image_processing_blip.py

@@ -257,7 +257,7 @@ class BlipImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/bridgetower/image_processing_bridgetower.py

@@ -491,7 +491,7 @@ class BridgeTowerImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/chameleon/image_processing_chameleon.py

@@ -302,7 +302,7 @@ class ChameleonImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/chinese_clip/image_processing_chinese_clip.py

@@ -271,7 +271,7 @@ class ChineseCLIPImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/clip/image_processing_clip.py

@@ -309,7 +309,7 @@ class CLIPImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/conditional_detr/image_processing_conditional_detr.py

@@ -1434,7 +1434,7 @@ class ConditionalDetrImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/convnext/image_processing_convnext.py

@@ -282,7 +282,7 @@ class ConvNextImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/deformable_detr/image_processing_deformable_detr.py

@@ -1432,7 +1432,7 @@ class DeformableDetrImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/deit/image_processing_deit.py

@@ -260,7 +260,7 @@ class DeiTImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/deprecated/deta/image_processing_deta.py

@@ -1049,7 +1049,7 @@ class DetaImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/deprecated/efficientformer/image_processing_efficientformer.py

@@ -280,7 +280,7 @@ class EfficientFormerImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/deprecated/tvlt/image_processing_tvlt.py

@@ -251,7 +251,7 @@ class TvltImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/deprecated/vit_hybrid/image_processing_vit_hybrid.py

@@ -302,7 +302,7 @@ class ViTHybridImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/detr/image_processing_detr.py

@@ -1407,7 +1407,7 @@ class DetrImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/donut/image_processing_donut.py

@@ -409,7 +409,7 @@ class DonutImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/dpt/image_processing_dpt.py

@@ -380,7 +380,7 @@ class DPTImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/efficientnet/image_processing_efficientnet.py

@@ -317,7 +317,7 @@ class EfficientNetImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/flava/image_processing_flava.py

@@ -421,7 +421,7 @@ class FlavaImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/fuyu/image_processing_fuyu.py

@@ -464,7 +464,7 @@ class FuyuImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         batch_images = [[to_numpy_array(image) for image in images] for images in batch_images]
 
-        if is_scaled_image(batch_images[0][0]) and do_rescale:
+        if do_rescale and is_scaled_image(batch_images[0][0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/glpn/image_processing_glpn.py

@@ -202,7 +202,7 @@ class GLPNImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(img) for img in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/grounding_dino/image_processing_grounding_dino.py

@@ -1440,7 +1440,7 @@ class GroundingDinoImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/idefics2/image_processing_idefics2.py

@@ -529,7 +529,7 @@ class Idefics2ImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images_list = [[to_numpy_array(image) for image in images] for images in images_list]
 
-        if is_scaled_image(images_list[0][0]) and do_rescale:
+        if do_rescale and is_scaled_image(images_list[0][0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/idefics3/image_processing_idefics3.py

@@ -758,7 +758,7 @@ class Idefics3ImageProcessor(BaseImageProcessor):
                 [np.expand_dims(img, axis=0) if img.ndim == 2 else img for img in images] for images in images_list
             ]
 
-        if is_scaled_image(images_list[0][0]) and do_rescale:
+        if do_rescale and is_scaled_image(images_list[0][0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/imagegpt/image_processing_imagegpt.py

@@ -258,7 +258,7 @@ class ImageGPTImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_normalize:
+        if do_normalize and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If you wish to do this, "
                 "make sure to set `do_normalize` to `False` and that pixel values are between [-1, 1].",

src/transformers/models/instructblipvideo/image_processing_instructblipvideo.py

@@ -324,7 +324,7 @@ class InstructBlipVideoImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled video frames. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/layoutlmv3/image_processing_layoutlmv3.py

@@ -324,7 +324,7 @@ class LayoutLMv3ImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/levit/image_processing_levit.py

@@ -274,7 +274,7 @@ class LevitImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/llava_next/image_processing_llava_next.py

@@ -697,7 +697,7 @@ class LlavaNextImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/llava_next_video/image_processing_llava_next_video.py

@@ -263,7 +263,7 @@ class LlavaNextVideoImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/llava_onevision/image_processing_llava_onevision.py

@@ -657,7 +657,7 @@ class LlavaOnevisionImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/llava_onevision/video_processing_llava_onevision.py

@@ -181,7 +181,7 @@ class LlavaOnevisionVideoProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled videos. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/mask2former/image_processing_mask2former.py

@@ -614,7 +614,7 @@ class Mask2FormerImageProcessor(BaseImageProcessor):
         """Preprocesses a single image."""
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/maskformer/image_processing_maskformer.py

@@ -615,7 +615,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
         """Preprocesses a single image."""
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/mobilenet_v1/image_processing_mobilenet_v1.py

@@ -266,7 +266,7 @@ class MobileNetV1ImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/mobilenet_v2/image_processing_mobilenet_v2.py

@@ -269,7 +269,7 @@ class MobileNetV2ImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/mobilevit/image_processing_mobilevit.py

@@ -234,7 +234,7 @@ class MobileViTImageProcessor(BaseImageProcessor):
         """Preprocesses a single image."""
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/nougat/image_processing_nougat.py

@@ -463,7 +463,7 @@ class NougatImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/oneformer/image_processing_oneformer.py

@@ -617,7 +617,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
         """Preprocesses a single image."""
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/owlv2/image_processing_owlv2.py

@@ -424,7 +424,7 @@ class Owlv2ImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/owlvit/image_processing_owlvit.py

@@ -373,7 +373,7 @@ class OwlViTImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/perceiver/image_processing_perceiver.py

@@ -307,7 +307,7 @@ class PerceiverImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/pixtral/image_processing_pixtral.py

@@ -473,7 +473,7 @@ class PixtralImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images_list = [[to_numpy_array(image) for image in images] for images in images_list]
 
-        if is_scaled_image(images_list[0][0]) and do_rescale:
+        if do_rescale and is_scaled_image(images_list[0][0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/poolformer/image_processing_poolformer.py

@@ -314,7 +314,7 @@ class PoolFormerImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/pvt/image_processing_pvt.py

@@ -237,7 +237,7 @@ class PvtImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/qwen2_vl/image_processing_qwen2_vl.py

@@ -252,7 +252,7 @@ class Qwen2VLImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/rt_detr/image_processing_rt_detr.py

@@ -935,7 +935,7 @@ class RTDetrImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/sam/image_processing_sam.py

@@ -316,7 +316,7 @@ class SamImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/segformer/image_processing_segformer.py

@@ -233,7 +233,7 @@ class SegformerImageProcessor(BaseImageProcessor):
         """Preprocesses a single image."""
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/seggpt/image_processing_seggpt.py

@@ -346,7 +346,7 @@ class SegGptImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/siglip/image_processing_siglip.py

@@ -204,7 +204,7 @@ class SiglipImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/superpoint/image_processing_superpoint.py

@@ -241,7 +241,7 @@ class SuperPointImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/swin2sr/image_processing_swin2sr.py

@@ -176,7 +176,7 @@ class Swin2SRImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/video_llava/image_processing_video_llava.py

@@ -377,7 +377,7 @@ class VideoLlavaImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images/video frames. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/videomae/image_processing_videomae.py

@@ -208,7 +208,7 @@ class VideoMAEImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/vilt/image_processing_vilt.py

@@ -438,7 +438,7 @@ class ViltImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/vit/image_processing_vit.py

@@ -247,7 +247,7 @@ class ViTImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/vitmatte/image_processing_vitmatte.py

@@ -223,7 +223,7 @@ class VitMatteImageProcessor(BaseImageProcessor):
         images = [to_numpy_array(image) for image in images]
         trimaps = [to_numpy_array(trimap) for trimap in trimaps]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/vivit/image_processing_vivit.py

@@ -262,7 +262,7 @@ class VivitImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         image = to_numpy_array(image)
 
-        if is_scaled_image(image) and do_rescale:
+        if do_rescale and is_scaled_image(image):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/yolos/image_processing_yolos.py

@@ -1343,7 +1343,7 @@ class YolosImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."

src/transformers/models/zoedepth/image_processing_zoedepth.py

@@ -404,7 +404,7 @@ class ZoeDepthImageProcessor(BaseImageProcessor):
         # All transformations expect numpy arrays.
         images = [to_numpy_array(image) for image in images]
 
-        if is_scaled_image(images[0]) and do_rescale:
+        if do_rescale and is_scaled_image(images[0]):
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"
                 " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."