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feat(backend): rename realesrgan class & upscale method

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psychedelicious 2023-11-28 07:37:39 +11:00
parent 46a2d83b84
commit 7653d21cf5
2 changed files with 5 additions and 5 deletions
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6
invokeai/app/invocations/upscale.py
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@ -11,7 +11,7 @@ from pydantic import ConfigDict
from invokeai.app.invocations.primitives import ImageField, ImageOutput from invokeai.app.invocations.primitives import ImageField, ImageOutput
from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGANer from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
from invokeai.backend.util.devices import choose_torch_device from invokeai.backend.util.devices import choose_torch_device
from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, WithWorkflow, invocation from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, WithWorkflow, invocation
@ -92,7 +92,7 @@ class ESRGANInvocation(BaseInvocation, WithWorkflow, WithMetadata):
esrgan_model_path = Path(f"core/upscaling/realesrgan/{self.model_name}") esrgan_model_path = Path(f"core/upscaling/realesrgan/{self.model_name}")
upsampler = RealESRGANer( upscaler = RealESRGAN(
scale=netscale, scale=netscale,
model_path=models_path / esrgan_model_path, model_path=models_path / esrgan_model_path,
model=rrdbnet_model, model=rrdbnet_model,
@ -107,7 +107,7 @@ class ESRGANInvocation(BaseInvocation, WithWorkflow, WithMetadata):
# We can pass an `outscale` value here, but it just resizes the image by that factor after # We can pass an `outscale` value here, but it just resizes the image by that factor after
# upscaling, so it's kinda pointless for our purposes. If you want something other than 4x # upscaling, so it's kinda pointless for our purposes. If you want something other than 4x
# upscaling, you'll need to add a resize node after this one. # upscaling, you'll need to add a resize node after this one.
upscaled_image = upsampler.enhance(cv2_image) upscaled_image = upscaler.upscale(cv2_image)
# back to PIL # back to PIL
pil_image = Image.fromarray(cv2.cvtColor(upscaled_image, cv2.COLOR_BGR2RGB)).convert("RGBA") pil_image = Image.fromarray(cv2.cvtColor(upscaled_image, cv2.COLOR_BGR2RGB)).convert("RGBA")

4
invokeai/backend/image_util/realesrgan/realesrgan.py
View File

@ -32,7 +32,7 @@ class ImageMode(str, Enum):
RGBA = "RGBA" RGBA = "RGBA"
class RealESRGANer: class RealESRGAN:
"""A helper class for upsampling images with RealESRGAN. """A helper class for upsampling images with RealESRGAN.
Args: Args:
@ -202,7 +202,7 @@ class RealESRGANer:
return self.output return self.output
@torch.no_grad() @torch.no_grad()
def enhance(self, img: MatLike, esrgan_alpha_upscale: bool = True) -> npt.NDArray[Any]: def upscale(self, img: MatLike, esrgan_alpha_upscale: bool = True) -> npt.NDArray[Any]:
np_img = img.astype(np.float32) np_img = img.astype(np.float32)
alpha: Optional[np.ndarray] = None alpha: Optional[np.ndarray] = None
if np.max(np_img) > 256: if np.max(np_img) > 256: