92 lines
2.7 KiB
Python
92 lines
2.7 KiB
Python
from basicsr.archs.rrdbnet_arch import RRDBNet
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from logging import getLogger
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from os import path
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from PIL import Image
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from realesrgan import RealESRGANer
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from ..onnx import (
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OnnxNet,
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)
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from ..params import (
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ImageParams,
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StageParams,
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UpscaleParams,
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)
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from ..utils import (
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ServerContext,
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)
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import numpy as np
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logger = getLogger(__name__)
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last_pipeline_instance = None
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last_pipeline_params = (None, None)
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def load_resrgan(ctx: ServerContext, params: UpscaleParams, tile=0):
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global last_pipeline_instance
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global last_pipeline_params
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model_file = '%s.%s' % (params.upscale_model, params.format)
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model_path = path.join(ctx.model_path, model_file)
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if not path.isfile(model_path):
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raise Exception('Real ESRGAN model not found at %s' % model_path)
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cache_params = (model_path, params.format)
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if last_pipeline_instance != None and cache_params == last_pipeline_params:
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logger.info('reusing existing Real ESRGAN pipeline')
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return last_pipeline_instance
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# use ONNX acceleration, if available
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if params.format == 'onnx':
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model = OnnxNet(ctx, model_file, provider=params.provider)
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elif params.format == 'pth':
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model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64,
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num_block=23, num_grow_ch=32, scale=params.scale)
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raise Exception('unknown platform %s' % params.format)
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dni_weight = None
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if params.upscale_model == 'realesr-general-x4v3' and params.denoise != 1:
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wdn_model_path = model_path.replace(
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'realesr-general-x4v3', 'realesr-general-wdn-x4v3')
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model_path = [model_path, wdn_model_path]
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dni_weight = [params.denoise, 1 - params.denoise]
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# TODO: shouldn't need the PTH file
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upsampler = RealESRGANer(
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scale=params.scale,
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model_path=path.join(ctx.model_path, '%s.pth' % params.upscale_model),
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dni_weight=dni_weight,
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model=model,
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tile=tile,
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tile_pad=params.tile_pad,
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pre_pad=params.pre_pad,
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half=params.half)
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last_pipeline_instance = upsampler
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last_pipeline_params = cache_params
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return upsampler
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def upscale_resrgan(
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ctx: ServerContext,
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stage: StageParams,
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_params: ImageParams,
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source_image: Image.Image,
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*,
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upscale: UpscaleParams,
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**kwargs,
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) -> Image.Image:
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logger.info('upscaling image with Real ESRGAN', upscale.scale)
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output = np.array(source_image)
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upsampler = load_resrgan(ctx, upscale, tile=stage.tile_size)
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output, _ = upsampler.enhance(output, outscale=upscale.outscale)
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output = Image.fromarray(output, 'RGB')
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logger.info('final output image size', output.size)
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return output
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