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Ahsen Khaliq
commited on
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•
504b262
1
Parent(s):
634f264
Update app.py
Browse files
app.py
CHANGED
@@ -108,8 +108,7 @@ class FaceEnhancement(object):
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use_sr = False
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use_cuda = False
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sr_model = 'rrdb_realesrnet_psnr'
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outdir = "."
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faceenhancer = FaceEnhancement(size=size, model=model, use_sr=use_sr, sr_model=sr_model, channel_multiplier=channel_multiplier, narrow=narrow, key=key, device='cuda' if args.use_cuda else 'cpu')
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@@ -118,13 +117,11 @@ class FaceEnhancement(object):
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def inference(
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im = cv2.imread(file, cv2.IMREAD_COLOR)
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img, orig_faces, enhanced_faces = faceenhancer.process(im)
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return enhanced_faces[0]
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os.system("python face_enhancement.py --model GPEN-BFR-512 --size 512 --channel_multiplier 2 --narrow 1 --use_sr --indir examples/imgs --outdir examples/outs-BFR2")
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return "examples/outs-BFR2/"
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title = "GFP-GAN"
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description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
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@@ -132,7 +129,7 @@ article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.040
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gr.Interface(
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inference,
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[gr.inputs.Image(type="filepath", label="Input")],
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gr.outputs.Image(type="
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title=title,
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description=description,
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article=article,
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use_sr = False
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use_cuda = False
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sr_model = 'rrdb_realesrnet_psnr'
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faceenhancer = FaceEnhancement(size=size, model=model, use_sr=use_sr, sr_model=sr_model, channel_multiplier=channel_multiplier, narrow=narrow, key=key, device='cuda' if args.use_cuda else 'cpu')
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def inference(file):
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im = cv2.imread(file, cv2.IMREAD_COLOR)
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img, orig_faces, enhanced_faces = faceenhancer.process(im)
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return enhanced_faces[0]
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title = "GFP-GAN"
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description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
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gr.Interface(
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inference,
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[gr.inputs.Image(type="filepath", label="Input")],
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gr.outputs.Image(type="numpy", label="Output"),
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title=title,
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description=description,
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article=article,
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