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-rw-r--r--extensions-builtin/LDSR/scripts/ldsr_model.py13
-rw-r--r--extensions-builtin/ScuNET/scripts/scunet_model.py16
-rw-r--r--extensions-builtin/SwinIR/scripts/swinir_model.py40
-rw-r--r--modules/esrgan_model.py14
-rw-r--r--modules/realesrgan_model.py33
5 files changed, 52 insertions, 64 deletions
diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py
index bf9b6de2..bd78dece 100644
--- a/extensions-builtin/LDSR/scripts/ldsr_model.py
+++ b/extensions-builtin/LDSR/scripts/ldsr_model.py
@@ -46,16 +46,13 @@ class UpscalerLDSR(Upscaler):
yaml = local_yaml_path or load_file_from_url(self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml")
- try:
- return LDSR(model, yaml)
- except Exception:
- errors.report("Error importing LDSR", exc_info=True)
- return None
+ return LDSR(model, yaml)
def do_upscale(self, img, path):
- ldsr = self.load_model(path)
- if ldsr is None:
- print("NO LDSR!")
+ try:
+ ldsr = self.load_model(path)
+ except Exception:
+ errors.report(f"Failed loading LDSR model {path}", exc_info=True)
return img
ddim_steps = shared.opts.ldsr_steps
return ldsr.super_resolution(img, ddim_steps, self.scale)
diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py
index da74a829..ffef26b2 100644
--- a/extensions-builtin/ScuNET/scripts/scunet_model.py
+++ b/extensions-builtin/ScuNET/scripts/scunet_model.py
@@ -1,4 +1,3 @@
-import os.path
import sys
import PIL.Image
@@ -8,7 +7,7 @@ from tqdm import tqdm
import modules.upscaler
from modules import devices, modelloader, script_callbacks, errors
-from scunet_model_arch import SCUNet as net
+from scunet_model_arch import SCUNet
from modules.modelloader import load_file_from_url
from modules.shared import opts
@@ -88,9 +87,10 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
torch.cuda.empty_cache()
- model = self.load_model(selected_file)
- if model is None:
- print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr)
+ try:
+ model = self.load_model(selected_file)
+ except Exception as e:
+ print(f"ScuNET: Unable to load model from {selected_file}: {e}", file=sys.stderr)
return img
device = devices.get_device_for('scunet')
@@ -123,11 +123,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth")
else:
filename = path
- if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None:
- print(f"ScuNET: Unable to load model from {filename}", file=sys.stderr)
- return None
-
- model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
+ model = SCUNet(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
model.load_state_dict(torch.load(filename), strict=True)
model.eval()
for _, v in model.named_parameters():
diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index 4551761d..3ce622d9 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -1,4 +1,4 @@
-import os
+import sys
import numpy as np
import torch
@@ -7,8 +7,8 @@ from tqdm import tqdm
from modules import modelloader, devices, script_callbacks, shared
from modules.shared import opts, state
-from swinir_model_arch import SwinIR as net
-from swinir_model_arch_v2 import Swin2SR as net2
+from swinir_model_arch import SwinIR
+from swinir_model_arch_v2 import Swin2SR
from modules.upscaler import Upscaler, UpscalerData
@@ -36,8 +36,10 @@ class UpscalerSwinIR(Upscaler):
self.scalers = scalers
def do_upscale(self, img, model_file):
- model = self.load_model(model_file)
- if model is None:
+ try:
+ model = self.load_model(model_file)
+ except Exception as e:
+ print(f"Failed loading SwinIR model {model_file}: {e}", file=sys.stderr)
return img
model = model.to(device_swinir, dtype=devices.dtype)
img = upscale(img, model)
@@ -56,25 +58,23 @@ class UpscalerSwinIR(Upscaler):
)
else:
filename = path
- if filename is None or not os.path.exists(filename):
- return None
if filename.endswith(".v2.pth"):
- model = net2(
- upscale=scale,
- in_chans=3,
- img_size=64,
- window_size=8,
- img_range=1.0,
- depths=[6, 6, 6, 6, 6, 6],
- embed_dim=180,
- num_heads=[6, 6, 6, 6, 6, 6],
- mlp_ratio=2,
- upsampler="nearest+conv",
- resi_connection="1conv",
+ model = Swin2SR(
+ upscale=scale,
+ in_chans=3,
+ img_size=64,
+ window_size=8,
+ img_range=1.0,
+ depths=[6, 6, 6, 6, 6, 6],
+ embed_dim=180,
+ num_heads=[6, 6, 6, 6, 6, 6],
+ mlp_ratio=2,
+ upsampler="nearest+conv",
+ resi_connection="1conv",
)
params = None
else:
- model = net(
+ model = SwinIR(
upscale=scale,
in_chans=3,
img_size=64,
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index a20e8d91..02a1727d 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -1,4 +1,4 @@
-import os
+import sys
import numpy as np
import torch
@@ -6,9 +6,8 @@ from PIL import Image
import modules.esrgan_model_arch as arch
from modules import modelloader, images, devices
-from modules.upscaler import Upscaler, UpscalerData
from modules.shared import opts
-
+from modules.upscaler import Upscaler, UpscalerData
def mod2normal(state_dict):
@@ -142,8 +141,10 @@ class UpscalerESRGAN(Upscaler):
self.scalers.append(scaler_data)
def do_upscale(self, img, selected_model):
- model = self.load_model(selected_model)
- if model is None:
+ try:
+ model = self.load_model(selected_model)
+ except Exception as e:
+ print(f"Unable to load ESRGAN model {selected_model}: {e}", file=sys.stderr)
return img
model.to(devices.device_esrgan)
img = esrgan_upscale(model, img)
@@ -159,9 +160,6 @@ class UpscalerESRGAN(Upscaler):
)
else:
filename = path
- if not os.path.exists(filename) or filename is None:
- print(f"Unable to load {self.model_path} from {filename}")
- return None
state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None)
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py
index 0d9c2e48..0700b853 100644
--- a/modules/realesrgan_model.py
+++ b/modules/realesrgan_model.py
@@ -9,7 +9,6 @@ from modules.shared import cmd_opts, opts
from modules import modelloader, errors
-
class UpscalerRealESRGAN(Upscaler):
def __init__(self, path):
self.name = "RealESRGAN"
@@ -43,9 +42,10 @@ class UpscalerRealESRGAN(Upscaler):
if not self.enable:
return img
- info = self.load_model(path)
- if not os.path.exists(info.local_data_path):
- print(f"Unable to load RealESRGAN model: {info.name}")
+ try:
+ info = self.load_model(path)
+ except Exception:
+ errors.report(f"Unable to load RealESRGAN model {path}", exc_info=True)
return img
upsampler = RealESRGANer(
@@ -63,20 +63,17 @@ class UpscalerRealESRGAN(Upscaler):
return image
def load_model(self, path):
- try:
- info = next(iter([scaler for scaler in self.scalers if scaler.data_path == path]), None)
-
- if info is None:
- print(f"Unable to find model info: {path}")
- return None
-
- if info.local_data_path.startswith("http"):
- info.local_data_path = modelloader.load_file_from_url(info.data_path, model_dir=self.model_download_path)
-
- return info
- except Exception:
- errors.report("Error making Real-ESRGAN models list", exc_info=True)
- return None
+ for scaler in self.scalers:
+ if scaler.data_path == path:
+ if scaler.local_data_path.startswith("http"):
+ scaler.local_data_path = modelloader.load_file_from_url(
+ scaler.data_path,
+ model_dir=self.model_download_path,
+ )
+ if not os.path.exists(scaler.local_data_path):
+ raise FileNotFoundError(f"RealESRGAN data missing: {scaler.local_data_path}")
+ return scaler
+ raise ValueError(f"Unable to find model info: {path}")
def load_models(self, _):
return get_realesrgan_models(self)
generated by cgit v1.2.3 (git 2.25.1) at 2025-04-28 15:28:39 +0000