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Running
on
Zero
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# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENT
# except for the third-party components listed below.
# Hunyuan 3D does not impose any additional limitations beyond what is outlined
# in the repsective licenses of these third-party components.
# Users must comply with all terms and conditions of original licenses of these third-party
# components and must ensure that the usage of the third party components adheres to
# all relevant laws and regulations.
# For avoidance of doubts, Hunyuan 3D means the large language models and
# their software and algorithms, including trained model weights, parameters (including
# optimizer states), machine-learning model code, inference-enabling code, training-enabling code,
# fine-tuning enabling code and other elements of the foregoing made publicly available
# by Tencent in accordance with TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT.
import numpy as np
from PIL import Image
class imageSuperNet:
def __init__(self, config) -> None:
from realesrgan import RealESRGANer
from basicsr.archs.rrdbnet_arch import RRDBNet
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
upsampler = RealESRGANer(
scale=4,
model_path=config.realesrgan_ckpt_path,
dni_weight=None,
model=model,
tile=0,
tile_pad=10,
pre_pad=0,
half=True,
gpu_id=None,
)
self.upsampler = upsampler
def __call__(self, image):
output, _ = self.upsampler.enhance(np.array(image))
output = Image.fromarray(output)
return output
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