Delete enhance_utils.py

enhance_utils.py

@@ -1,54 +0,0 @@
-import os
-import torch
-import cv2
-import numpy as np
-import subprocess
-
-from PIL import Image
-from gfpgan.utils import GFPGANer
-from basicsr.archs.srvgg_arch import SRVGGNetCompact
-from realesrgan.utils import RealESRGANer
-
-def runcmd(cmd, verbose = False, *args, **kwargs):
-
-    process = subprocess.Popen(
-        cmd,
-        stdout = subprocess.PIPE,
-        stderr = subprocess.PIPE,
-        text = True,
-        shell = True
-    )
-    std_out, std_err = process.communicate()
-    if verbose:
-        print(std_out.strip(), std_err)
-    pass
-
-runcmd("pip freeze")
-if not os.path.exists('GFPGANv1.4.pth'):
-    runcmd("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P .")
-if not os.path.exists('realesr-general-x4v3.pth'):
-    runcmd("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth -P .")
-
-model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
-model_path = 'realesr-general-x4v3.pth'
-half = True if torch.cuda.is_available() else False
-upsampler = RealESRGANer(scale=4, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=half)
-
-face_enhancer = GFPGANer(model_path='GFPGANv1.4.pth', upscale=1, arch='clean', channel_multiplier=2)
-
-def enhance_image(
-    pil_image: Image,
-    enhance_face: bool = False,
-):
-    img = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
-
-    h, w = img.shape[0:2]
-    if h < 300:
-        img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)
-    if enhance_face:
-        _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=True, paste_back=True)
-    else:
-        output, _ = upsampler.enhance(img, outscale=2)
-    pil_output = Image.fromarray(cv2.cvtColor(output, cv2.COLOR_BGR2RGB))
-
-    return pil_output