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authorAUTOMATIC1111 <16777216c@gmail.com>2023-01-04 14:40:19 +0000
committerGitHub <noreply@github.com>2023-01-04 14:40:19 +0000
commitda5c1e8a732c173ed8ccda9fa32f9a194ff91ab6 (patch)
treea2eec9c47e820e7ab351337f73c99d874b4b904f /modules/upscaler.py
parentcffc240a7327ae60671ff533469fc4ed4bf605de (diff)
parent47df0849019abac6722c49512f4dd2285bff5b7d (diff)
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Merge branch 'master' into inpaint_textual_inversion
Diffstat (limited to 'modules/upscaler.py')
-rw-r--r--modules/upscaler.py31
1 files changed, 27 insertions, 4 deletions
diff --git a/modules/upscaler.py b/modules/upscaler.py
index 6ab2fb40..231680cb 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
@@ -52,14 +53,22 @@ class Upscaler:
def do_upscale(self, img: PIL.Image, selected_model: str):
return img
- def upscale(self, img: PIL.Image, scale: int, selected_model: str = None):
+ def upscale(self, img: PIL.Image, scale, selected_model: str = None):
self.scale = scale
- dest_w = img.width * scale
- dest_h = img.height * scale
+ dest_w = int(img.width * scale)
+ dest_h = int(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