fixed control_image

app.py

@@ -3,11 +3,10 @@ import spaces
 from diffusers import ControlNetUnionModel, AutoencoderKL
 import gradio as gr
 
-from pipeline.mod_controlnet_tile_sr_sdxl import StableDiffusionXLControlNetTileSRPipeline
+from pipeline.mod_controlnet_tile_sr_sdxl import StableDiffusionXLControlNetTileSRPipeline, calculate_overlap
 from pipeline.util import (
     SAMPLERS,
     Platinum,
-    calculate_overlap,
     create_hdr_effect,
     progressive_upscale,
     select_scheduler,
@@ -60,8 +59,9 @@ def predict(
     print(f"Current resolution: H:{original_height} x W:{original_width}")
 
     # Pre-upscale image for tiling
-    control_image = progressive_upscale(image, resolution)
-    control_image = create_hdr_effect(control_image, hdr)
+    control_image = create_hdr_effect(image, hdr)
+    image = progressive_upscale(image, resolution)
+    image = create_hdr_effect(image, hdr)
 
     # Update target height and width
     target_height = control_image.height
@@ -75,8 +75,8 @@ def predict(
     # Image generation
     print("Diffusion kicking in... almost done, coffee's on you!")
     image = pipe(
-        image=control_image,
-        control_image=image,
+        image=image,
+        control_image=control_image,
         control_mode=[6],
         controlnet_conditioning_scale=float(controlnet_strength),
         prompt=prompt,

pipeline/mod_controlnet_tile_sr_sdxl.py

@@ -264,6 +264,26 @@ def retrieve_latents(
     else:
         raise AttributeError("Could not access latents of provided encoder_output")
 
+def calculate_overlap(width, height, base_overlap=128):
+    """
+    Calculates dynamic overlap based on the image's aspect ratio.
+
+    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.
+
+    Returns:
+        tuple: A tuple containing:
+            - row_overlap (int): Overlap between tiles in consecutive rows.
+            - col_overlap (int): Overlap between tiles in consecutive columns.
+    """
+    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
+    
 class TileWeightingMethod(Enum):
         """Mode in which the tile weights will be generated"""
 

pipeline/util.py

@@ -157,27 +157,6 @@ def select_scheduler(pipe, selected_sampler):
     return scheduler.from_config(config, **add_kwargs)
 
 
-def calculate_overlap(width, height, base_overlap=128):
-    """
-    Calculates dynamic overlap based on the image's aspect ratio.
-
-    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.
-
-    Returns:
-        tuple: A tuple containing:
-            - row_overlap (int): Overlap between tiles in consecutive rows.
-            - col_overlap (int): Overlap between tiles in consecutive columns.
-    """
-    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):
     """