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consider get the models from hugging face #394

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consider get the models from hugging face #394

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models from hugging face
leonelhs Jun 12, 2023
b69c37c
models from hugging face
leonelhs Jun 12, 2023
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22 changes: 11 additions & 11 deletions inference_gfpgan.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,9 +5,13 @@
import os
import torch
from basicsr.utils import imwrite
from huggingface_hub import snapshot_download

from gfpgan import GFPGANer

REALESRGAN_REPO_ID = 'leonelhs/realesrgan'
GFPGAN_REPO_ID = 'leonelhs/gfpgan'


def main():
"""Inference demo for GFPGAN (for users).
Expand Down Expand Up @@ -66,10 +70,12 @@ def main():
else:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
snapshot_folder = snapshot_download(repo_id=REALESRGAN_REPO_ID)
model_path = os.path.join(snapshot_folder, "RealESRGAN_x2plus.pth")
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
bg_upsampler = RealESRGANer(
scale=2,
model_path='https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
model_path=model_path,
model=model,
tile=args.bg_tile,
tile_pad=10,
Expand All @@ -79,41 +85,35 @@ def main():
bg_upsampler = None

# ------------------------ set up GFPGAN restorer ------------------------
snapshot_folder = snapshot_download(repo_id=GFPGAN_REPO_ID)

if args.version == '1':
arch = 'original'
channel_multiplier = 1
model_name = 'GFPGANv1'
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v0.1.0/GFPGANv1.pth'
elif args.version == '1.2':
arch = 'clean'
channel_multiplier = 2
model_name = 'GFPGANCleanv1-NoCE-C2'
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth'
elif args.version == '1.3':
arch = 'clean'
channel_multiplier = 2
model_name = 'GFPGANv1.3'
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth'
elif args.version == '1.4':
arch = 'clean'
channel_multiplier = 2
model_name = 'GFPGANv1.4'
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth'
elif args.version == 'RestoreFormer':
arch = 'RestoreFormer'
channel_multiplier = 2
model_name = 'RestoreFormer'
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth'
else:
raise ValueError(f'Wrong model version {args.version}.')

# determine model paths
model_path = os.path.join('experiments/pretrained_models', model_name + '.pth')
if not os.path.isfile(model_path):
model_path = os.path.join('gfpgan/weights', model_name + '.pth')
model_path = os.path.join(snapshot_folder, model_name + '.pth')
if not os.path.isfile(model_path):
# download pre-trained models from url
model_path = url
raise ValueError(f'Model not found {model_name}.')

restorer = GFPGANer(
model_path=model_path,
Expand Down