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-rw-r--r--modules/upscaler.py25
1 files changed, 24 insertions, 1 deletions
diff --git a/modules/upscaler.py b/modules/upscaler.py
index 6ab2fb40..c4e6e6bd 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -10,6 +10,7 @@ import modules.shared
from modules import modelloader, shared
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
+NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST)
from modules.paths import models_path
@@ -56,10 +57,18 @@ class Upscaler:
self.scale = scale
dest_w = img.width * scale
dest_h = img.height * scale
+
for i in range(3):
+ shape = (img.width, img.height)
+
+ img = self.do_upscale(img, selected_model)
+
+ if shape == (img.width, img.height):
+ break
+
if img.width >= dest_w and img.height >= dest_h:
break
- img = self.do_upscale(img, selected_model)
+
if img.width != dest_w or img.height != dest_h:
img = img.resize((int(dest_w), int(dest_h)), resample=LANCZOS)
@@ -120,3 +129,17 @@ class UpscalerLanczos(Upscaler):
self.name = "Lanczos"
self.scalers = [UpscalerData("Lanczos", None, self)]
+
+class UpscalerNearest(Upscaler):
+ scalers = []
+
+ def do_upscale(self, img, selected_model=None):
+ return img.resize((int(img.width * self.scale), int(img.height * self.scale)), resample=NEAREST)
+
+ def load_model(self, _):
+ pass
+
+ def __init__(self, dirname=None):
+ super().__init__(False)
+ self.name = "Nearest"
+ self.scalers = [UpscalerData("Nearest", None, self)] \ No newline at end of file