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import cv2
import numpy as np
from loguru import logger
from iopaint.helper import download_model
from iopaint.plugins.base_plugin import BasePlugin
from iopaint.schema import RunPluginRequest
class RestoreFormerPlugin(BasePlugin):
name = "RestoreFormer"
support_gen_image = True
def __init__(self, device, upscaler=None):
super().__init__()
from .gfpganer import MyGFPGANer
url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth"
model_md5 = "eaeeff6c4a1caa1673977cb374e6f699"
model_path = download_model(url, model_md5)
logger.info(f"RestoreFormer model path: {model_path}")
import facexlib
if hasattr(facexlib.detection.retinaface, "device"):
facexlib.detection.retinaface.device = device
self.face_enhancer = MyGFPGANer(
model_path=model_path,
upscale=1,
arch="RestoreFormer",
channel_multiplier=2,
device=device,
bg_upsampler=upscaler.model if upscaler is not None else None,
)
def gen_image(self, rgb_np_img, req: RunPluginRequest) -> np.ndarray:
weight = 0.5
bgr_np_img = cv2.cvtColor(rgb_np_img, cv2.COLOR_RGB2BGR)
logger.info(f"RestoreFormer input shape: {bgr_np_img.shape}")
_, _, bgr_output = self.face_enhancer.enhance(
bgr_np_img,
has_aligned=False,
only_center_face=False,
paste_back=True,
weight=weight,
)
logger.info(f"RestoreFormer output shape: {bgr_output.shape}")
return bgr_output
def check_dep(self):
try:
import gfpgan
except ImportError:
return (
"gfpgan is not installed, please install it first. pip install gfpgan"
)
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