add

.gitattributes

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+GFPGANv1.3.pth filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.8.4-slim
+
+WORKDIR /app
+
+COPY requirements.txt /app
+
+RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple/ 
+
+RUN apt-get update && \
+    apt-get upgrade -y && \
+    apt-get install -y git
+
+RUN apt-get install -y tk
+
+RUN pip3 install --trusted-host pypi.python.org -r requirements.txt 
+
+COPY . /app
+
+CMD ["python", "app.py"]

app.py

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+#超分辨率重建
+import os
+import cv2
+import gradio as gr
+import torch
+from basicsr.archs.srvgg_arch import SRVGGNetCompact
+from gfpgan.utils import GFPGANer
+from realesrgan.utils import RealESRGANer
+from gradio.themes.utils import sizes
+
+
+theme = gr.themes.Default(radius_size=sizes.radius_none).set(
+    block_label_text_color = '#4D63FF',
+    block_title_text_color = '#4D63FF',
+    button_primary_text_color = '#4D63FF',
+    button_primary_background_fill='#FFFFFF',
+    button_primary_border_color='#4D63FF',
+    button_primary_background_fill_hover='#EDEFFF',
+)
+
+
+# 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 = '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)
+
+# Use GFPGAN for face enhancement
+face_enhancer_v3 = GFPGANer(
+    model_path='GFPGANv1.3.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
+
+os.makedirs('output', exist_ok=True)
+
+
+def inference(img):
+    scale = 2
+    try:
+        img = cv2.imread(img, cv2.IMREAD_UNCHANGED)
+        if len(img.shape) == 3 and img.shape[2] == 4:
+            img_mode = 'RGBA'
+        else:
+            img_mode = None
+
+        h, w = img.shape[0:2]
+        if h < 300:
+            img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)
+
+        face_enhancer = face_enhancer_v3
+        
+        try:
+            _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
+        except RuntimeError as error:
+            print('Error', error)
+        else:
+            extension = 'png'
+
+        try:
+            if scale != 2:
+                interpolation = cv2.INTER_AREA if scale < 2 else cv2.INTER_LANCZOS4
+                h, w = img.shape[0:2]
+                output = cv2.resize(output, (int(w * scale / 2), int(h * scale / 2)), interpolation=interpolation)
+        except Exception as error:
+            print('wrong scale input.', error)
+        if img_mode == 'RGBA':  # RGBA images should be saved in png format
+            extension = 'png'
+        else:
+            extension = 'jpg'
+        save_path = f'output/out.{extension}'
+        cv2.imwrite(save_path, output)
+
+        output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
+        return output
+    except Exception as error:
+        print('global exception', error)
+        return None
+
+
+with gr.Blocks(theme=theme, css="footer {visibility: hidden}") as demo:
+    gr.Markdown("""
+    <div align='center' ><font size='60'>图像超分辨率重建</font></div>
+    """)
+    with gr.Row():
+        with gr.Column():
+            image = gr.Image(label="图片", type="filepath")
+            with gr.Row():
+                button = gr.Button("提交", variant="primary")
+        box2 = gr.Image(label="图片")
+
+    button.click(fn=inference, inputs=[image], outputs=box2)
+    examples = gr.Examples(examples=[['1.jpg'], ['2.jpg'], ['4.jpg']],  inputs=[image], label="例子")
+
+
+if __name__ == '__main__':
+    demo.queue().launch(server_name = "0.0.0.0")

requirements.txt

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+gradio
+torch
+basicsr
+gfpgan
+realesrgan
+opencv-python-headless==4.5.3.56
+pillow
+numpy
+