adjust util.py

pipeline/util.py

@@ -178,46 +178,6 @@ def calculate_overlap(width, height, base_overlap=128):
         return base_overlap, base_overlap * 2
 
 
-# def calculate_overlap(width, height, base_overlap=128, scale=4):
-#     """
-#     Calculates dynamic overlap based on the image's aspect ratio and resolution.
-#     For scales less than 4, the overlap is fixed at 64, 128 (or 128, 256).
-#     For scales 4 or greater, the overlap is adjusted proportionally to the scale.
-
-#     Args:
-#         width (int): Width of the image in pixels.
-#         height (int): Height of the image in pixels.
-#         base_overlap (int, optional): Base overlap value in pixels. Defaults to 128.
-#         scale (int, optional): Scale factor for calculating the overlap. Defaults to 4.
-
-#     Returns:
-#         tuple: A tuple containing:
-#             - row_overlap (int): Overlap between tiles in consecutive rows.
-#             - col_overlap (int): Overlap between tiles in consecutive columns.
-#     """
-#     # Define the base scale (4)
-#     base_scale = 4
-
-#     # If scale is less than 4, use fixed overlap values
-#     if scale < base_scale:
-#         ratio = height / width
-#         if ratio < 1:  # Image is wider than tall
-#             return base_overlap // 2, base_overlap
-#         else:  # Image is taller than wide
-#             return base_overlap, base_overlap * 2
-#     else:
-#         # For scales 4 or greater, adjust overlap proportionally
-#         scaling_factor = scale / base_scale
-#         base_overlap = int(base_overlap * base_scale)
-#         #base_overlap = int(base_overlap * scaling_factor)
-
-#         ratio = height / width
-#         if ratio < 1:  # Image is wider than tall
-#             return base_overlap // 2, base_overlap
-#         else:  # Image is taller than wide
-#             return base_overlap, base_overlap * 2
-
-
 # This function was copied and adapted from https://huggingface.co/spaces/gokaygokay/TileUpscalerV2, licensed under Apache 2.0.
 def progressive_upscale(input_image, target_resolution, steps=3):
     """
@@ -296,9 +256,11 @@ def create_hdr_effect(original_image, hdr):
     # Convert the HDR image to 8-bit format (0-255 range)
     hdr_image_8bit = np.clip(hdr_image * 255, 0, 255).astype("uint8")
 
+    torch_gc()
+    
     # Convert the image back to RGB format and return as a PIL image
     return Image.fromarray(cv2.cvtColor(hdr_image_8bit, cv2.COLOR_BGR2RGB))
-
+    
 
 def torch_gc():
     if torch.cuda.is_available():