init app

.gitignore

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+*.png
+*.jpg
+.idea/
+__pycache__/
+flagged
+gfpgan
+output
+

app.py

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+import os
+
+import gradio as gr
+import torch
+from basicsr.archs.srvgg_arch import SRVGGNetCompact
+from gfpgan.utils import GFPGANer
+from huggingface_hub import hf_hub_download
+from realesrgan.utils import RealESRGANer
+
+REALESRGAN_REPO_ID = 'leonelhs/realesrgan'
+GFPGAN_REPO_ID = 'leonelhs/gfpgan'
+
+os.system("pip freeze")
+
+# background enhancer with RealESRGAN
+model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
+model_path = hf_hub_download(repo_id=REALESRGAN_REPO_ID, filename='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)
+
+
+def download_model(file):
+    return hf_hub_download(repo_id=GFPGAN_REPO_ID, filename=file)
+
+
+def predict(image, version, scale):
+    scale = int(scale)
+    face_enhancer = None
+
+    if version == 'v1.2':
+        path = download_model('GFPGANv1.2.pth')
+        face_enhancer = GFPGANer(
+            model_path=path, upscale=scale, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
+    elif version == 'v1.3':
+        path = download_model('GFPGANv1.3.pth')
+        face_enhancer = GFPGANer(
+            model_path=path, upscale=scale, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
+    elif version == 'v1.4':
+        path = download_model('GFPGANv1.4.pth')
+        face_enhancer = GFPGANer(
+            model_path=path, upscale=scale, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
+    elif version == 'RestoreFormer':
+        path = download_model('RestoreFormer.pth')
+        face_enhancer = GFPGANer(
+            model_path=path, upscale=scale, arch='RestoreFormer', channel_multiplier=2, bg_upsampler=upsampler)
+
+    _, _, output = face_enhancer.enhance(image, has_aligned=False, only_center_face=False, paste_back=True)
+
+    return output
+
+
+title = "GFPGAN"
+description = r"""
+<b>Practical Face Restoration Algorithm</b>
+"""
+article = r"""
+<center><span>[email protected] or [email protected]</span></center>
+</br>
+<center><a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo ⭐ </a> are welcome</center>
+"""
+
+demo = gr.Interface(
+    predict, [
+        gr.Image(type="numpy", label="Input"),
+        gr.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer'], type="value", value='v1.4', label='version'),
+        gr.Dropdown(["1", "2", "3", "4"], value="2", label="Rescaling factor")
+    ], [
+        gr.Image(type="numpy", label="Output", interactive=False)
+    ],
+    title=title,
+    description=description,
+    article=article)
+
+demo.queue().launch()

packages.txt

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+ffmpeg
+libsm6
+libxext6

requirements.txt

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+torch>=2.0.1
+basicsr>=1.4.2
+facexlib>=0.3.0
+gfpgan>=1.3.8
+realesrgan>=0.3.0
+numpy
+opencv-python
+torchvision
+scipy
+tqdm
+lmdb
+pyyaml
+yapf