Merge pull request #555 from bghira/main

cv2: error checking for image load when we hit grayscale images | LoRA: save/load refactor from Sayak | arguments: set --inference_noise_scheduler to None by default so that PixArt scheduler is uninterrupted

helpers/arguments.py

@@ -1204,12 +1204,12 @@ def parse_args(input_args=None):
         "--validation_noise_scheduler",
         type=str,
         choices=["ddim", "ddpm", "euler", "euler-a", "unipc"],
-        default="euler",
+        default=None,
         help=(
             "When validating the model at inference time, a different scheduler may be chosen."
             " UniPC can offer better speed, and Euler A can put up with instabilities a bit better."
             " For zero-terminal SNR models, DDIM is the best choice. Choices: ['ddim', 'ddpm', 'euler', 'euler-a', 'unipc'],"
-            " Default: ddim"
+            " Default: None (use the model default)"
         ),
     )
     parser.add_argument(

helpers/data_backend/local.py

@@ -120,15 +120,16 @@ def read_image(self, filepath: str, delete_problematic_images: bool = False):
             import traceback
 
             logger.error(
-                f"Encountered error opening image: {e}, traceback: {traceback.format_exc()}"
+                f"Encountered error opening image {filepath}: {e}, traceback: {traceback.format_exc()}"
             )
             if delete_problematic_images:
                 logger.error(
                     f"Deleting image, because --delete_problematic_images is provided."
                 )
                 self.delete(filepath)
-            exit(1)
-            raise e
+            else:
+                exit(1)
+                raise e
 
     def read_image_batch(
         self, filepaths: list, delete_problematic_images: bool = False

helpers/image_manipulation/load.py

@@ -39,28 +39,28 @@ def decode_image_with_pil(img_data: bytes) -> Image.Image:
 
         # For transparent images, add a white background as this is correct
         # most of the time.
-        if img_pil.mode == 'RGBA':
+        if img_pil.mode == "RGBA":
             canvas = Image.new("RGBA", img_pil.size, (255, 255, 255))
             canvas.alpha_composite(img_pil)
             img_pil = canvas.convert("RGB")
         else:
-            img_pil = img_pil.convert('RGB')
+            img_pil = img_pil.convert("RGB")
     except (OSError, Image.DecompressionBombError, ValueError) as e:
-        logger.warning(f'Error decoding image: {e}')
+        logger.warning(f"Error decoding image: {e}")
         raise
     return img_pil
 
 
 def load_image(img_data: Union[bytes, IO[Any], str]) -> Image.Image:
-    '''
+    """
     Load an image using CV2. If that fails, fall back to PIL.
 
     The image is returned as a PIL object.
-    '''
+    """
     if isinstance(img_data, str):
-        with open(img_data, 'rb') as file:
+        with open(img_data, "rb") as file:
             img_data = file.read()
-    elif hasattr(img_data, 'read'):
+    elif hasattr(img_data, "read"):
         # Check if it's file-like object.
         img_data = img_data.read()
 
@@ -70,7 +70,11 @@ def load_image(img_data: Union[bytes, IO[Any], str]) -> Image.Image:
     nparr = np.frombuffer(img_data, np.uint8)
     image_preload = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
     has_alpha = False
-    if image_preload is not None and image_preload.shape[2] == 4:
+    if (
+        image_preload is not None
+        and len(image_preload.shape) >= 3
+        and image_preload.shape[2] == 4
+    ):
         has_alpha = True
     del image_preload