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  1. .gitattributes +1 -0
  2. app.py +49 -0
  3. models/models-cunet/noise0_model.bin +3 -0
  4. models/models-cunet/noise0_model.param +61 -0
  5. models/models-cunet/noise0_scale2.0x_model.bin +3 -0
  6. models/models-cunet/noise0_scale2.0x_model.param +61 -0
  7. models/models-cunet/noise1_model.bin +3 -0
  8. models/models-cunet/noise1_model.param +61 -0
  9. models/models-cunet/noise1_scale2.0x_model.bin +3 -0
  10. models/models-cunet/noise1_scale2.0x_model.param +61 -0
  11. models/models-cunet/noise2_model.bin +3 -0
  12. models/models-cunet/noise2_model.param +61 -0
  13. models/models-cunet/noise2_scale2.0x_model.bin +3 -0
  14. models/models-cunet/noise2_scale2.0x_model.param +61 -0
  15. models/models-cunet/noise3_model.bin +3 -0
  16. models/models-cunet/noise3_model.param +61 -0
  17. models/models-cunet/noise3_scale2.0x_model.bin +3 -0
  18. models/models-cunet/noise3_scale2.0x_model.param +61 -0
  19. models/models-cunet/scale2.0x_model.bin +3 -0
  20. models/models-cunet/scale2.0x_model.param +61 -0
  21. models/models-upconv_7_anime_style_art_rgb/noise0_scale2.0x_model.bin +3 -0
  22. models/models-upconv_7_anime_style_art_rgb/noise0_scale2.0x_model.param +10 -0
  23. models/models-upconv_7_anime_style_art_rgb/noise1_scale2.0x_model.bin +3 -0
  24. models/models-upconv_7_anime_style_art_rgb/noise1_scale2.0x_model.param +10 -0
  25. models/models-upconv_7_anime_style_art_rgb/noise2_scale2.0x_model.bin +3 -0
  26. models/models-upconv_7_anime_style_art_rgb/noise2_scale2.0x_model.param +10 -0
  27. models/models-upconv_7_anime_style_art_rgb/noise3_scale2.0x_model.bin +3 -0
  28. models/models-upconv_7_anime_style_art_rgb/noise3_scale2.0x_model.param +10 -0
  29. models/models-upconv_7_anime_style_art_rgb/scale2.0x_model.bin +3 -0
  30. models/models-upconv_7_anime_style_art_rgb/scale2.0x_model.param +10 -0
  31. models/models-upconv_7_photo/noise0_scale2.0x_model.bin +3 -0
  32. models/models-upconv_7_photo/noise0_scale2.0x_model.param +10 -0
  33. models/models-upconv_7_photo/noise1_scale2.0x_model.bin +3 -0
  34. models/models-upconv_7_photo/noise1_scale2.0x_model.param +10 -0
  35. models/models-upconv_7_photo/noise2_scale2.0x_model.bin +3 -0
  36. models/models-upconv_7_photo/noise2_scale2.0x_model.param +10 -0
  37. models/models-upconv_7_photo/noise3_scale2.0x_model.bin +3 -0
  38. models/models-upconv_7_photo/noise3_scale2.0x_model.param +10 -0
  39. models/models-upconv_7_photo/scale2.0x_model.bin +3 -0
  40. models/models-upconv_7_photo/scale2.0x_model.param +10 -0
  41. models/waifu2x-ncnn-vulkan +3 -0
.gitattributes CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
32
  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ models/waifu2x-ncnn-vulkan filter=lfs diff=lfs merge=lfs -text
app.py ADDED
@@ -0,0 +1,49 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import gradio as gr
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+ from PIL import Image, PngImagePlugin
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+ import numpy as np
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+ import os
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+
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+ noisedict = {
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+ "なし": -1,
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+ "低": 0,
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+ "中": 1,
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+ "高": 2,
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+ "最高": 3
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+ }
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+
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+ scaledict = {
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+ "1倍": 1,
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+ "2倍": 2,
17
+ }
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+
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+ formatdict = {
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+ "PNG": "png",
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+ "JPG": "jpg",
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+ "WebP": "webp"
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+ }
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+
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+ def response_greet(image, noise, scale, format):
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+ info = image.info
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+ n = noisedict[noise]
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+ s = scaledict[scale]
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+ f = formatdict[format]
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+ image.save("input.png")
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+ os.system(f"models/waifu2x-ncnn-vulkan -i input.png -o output.{f} -n {n} -s {s} -f {f} -g -1")
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+ image = Image.open(f"output.{f}")
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+ image.info = info
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+ return image
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+
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+ with gr.Blocks() as app:
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+ gr.Markdown("## Waifu2x with png metadata demo")
38
+ with gr.Row():
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+ with gr.Column():
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+ image = gr.Image(label="入力画像", interactive=True, type="pil", )
41
+ noise = gr.Radio(choices=["なし", "低", "中", "高", "最高"], label="ノイズ除去", value="中", interactive=True, type="value"),
42
+ scale = gr.Radio(choices=["1倍", "2倍"], label="拡大", value="2倍", interactive=True, type="value"),
43
+ format = gr.Radio(choices=["PNG", "JPG", "WebP"], label="出力フォーマット(※現時点ではPNGのみ選択できます)", value="PNG", type="value"),
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+ button = gr.Button("送信")
45
+ with gr.Column():
46
+ output = gr.Image(label="出力画像", type="pil")
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+ button.click(fn=response_greet, inputs=[image, noise[0], scale[0], format[0]], outputs=output, api_name="Waifu2xで画像をアップコンバートします。")
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+
49
+ app.launch()
models/models-cunet/noise0_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:b15c356a36bcbf6fb8c2f1404ca016fd917d4e45426bcf41f7a3867022fdd7b0
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+ size 2767568
models/models-cunet/noise0_model.param ADDED
@@ -0,0 +1,61 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ 7767517
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+ 59 71
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+ Input input 0 1 Input1 0=312 1=312 2=3
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+ Convolution Convolution1 1 1 Input1 Convolution1_ReLU1 0=32 1=3 5=1 6=864 9=2 -23310=1,0.100000
5
+ Convolution Convolution2 1 1 Convolution1_ReLU1 Convolution2_ReLU2 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
6
+ Split splitncnn_0 1 2 Convolution2_ReLU2 Convolution2_ReLU2_splitncnn_0 Convolution2_ReLU2_splitncnn_1
7
+ Convolution Convolution3 1 1 Convolution2_ReLU2_splitncnn_1 Convolution3_ReLU3 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
8
+ Convolution Convolution4 1 1 Convolution3_ReLU3 Convolution4_ReLU4 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
9
+ Convolution Convolution5 1 1 Convolution4_ReLU4 Convolution5_ReLU5 0=64 1=3 5=1 6=73728 9=2 -23310=1,0.100000
10
+ Split splitncnn_1 1 2 Convolution5_ReLU5 Convolution5_ReLU5_splitncnn_0 Convolution5_ReLU5_splitncnn_1
11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
12
+ InnerProduct Convolution6 1 1 Pooling1 Convolution6_ReLU6 0=8 1=1 2=512 9=1
13
+ InnerProduct Convolution7 1 1 Convolution6_ReLU6 Flatten1 0=64 1=1 2=512 9=4
14
+ Scale Scale1 2 1 Convolution5_ReLU5_splitncnn_0 Flatten1 Scale1 0=-233
15
+ Deconvolution Deconvolution1 1 1 Scale1 Deconvolution1_ReLU7 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
16
+ Split splitncnn_2 1 2 Deconvolution1_ReLU7 Deconvolution1_ReLU7_splitncnn_0 Deconvolution1_ReLU7_splitncnn_1
17
+ Crop Crop1 2 1 Convolution2_ReLU2_splitncnn_0 Deconvolution1_ReLU7_splitncnn_1 Crop1 0=4 1=4
18
+ Eltwise Eltwise1 2 1 Crop1 Deconvolution1_ReLU7_splitncnn_0 Eltwise1 0=1
19
+ Convolution Convolution8 1 1 Eltwise1 Convolution8_ReLU8 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
20
+ Convolution Convolution9 1 1 Convolution8_ReLU8 Convolution9 0=3 1=3 5=1 6=1728
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+ Split splitncnn_3 1 2 Convolution9 Convolution9_splitncnn_0 Convolution9_splitncnn_1
22
+ Convolution Convolution10 1 1 Convolution9_splitncnn_1 Convolution10_ReLU9 0=32 1=3 5=1 6=864 9=2 -23310=1,0.100000
23
+ Convolution Convolution11 1 1 Convolution10_ReLU9 Convolution11_ReLU10 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
24
+ Split splitncnn_4 1 2 Convolution11_ReLU10 Convolution11_ReLU10_splitncnn_0 Convolution11_ReLU10_splitncnn_1
25
+ Convolution Convolution12 1 1 Convolution11_ReLU10_splitncnn_1 Convolution12_ReLU11 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
26
+ Convolution Convolution13 1 1 Convolution12_ReLU11 Convolution13_ReLU12 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
27
+ Convolution Convolution14 1 1 Convolution13_ReLU12 Convolution14_ReLU13 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
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+ Split splitncnn_5 1 2 Convolution14_ReLU13 Convolution14_ReLU13_splitncnn_0 Convolution14_ReLU13_splitncnn_1
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+ Pooling Pooling2 1 1 Convolution14_ReLU13_splitncnn_1 Pooling2 0=1 4=1
30
+ InnerProduct Convolution15 1 1 Pooling2 Convolution15_ReLU14 0=16 1=1 2=2048 9=1
31
+ InnerProduct Convolution16 1 1 Convolution15_ReLU14 Flatten2 0=128 1=1 2=2048 9=4
32
+ Scale Scale2 2 1 Convolution14_ReLU13_splitncnn_0 Flatten2 Scale2 0=-233
33
+ Split splitncnn_6 1 2 Scale2 Scale2_splitncnn_0 Scale2_splitncnn_1
34
+ Convolution Convolution17 1 1 Scale2_splitncnn_1 Convolution17_ReLU15 0=128 1=2 3=2 5=1 6=65536 9=2 -23310=1,0.100000
35
+ Convolution Convolution18 1 1 Convolution17_ReLU15 Convolution18_ReLU16 0=256 1=3 5=1 6=294912 9=2 -23310=1,0.100000
36
+ Convolution Convolution19 1 1 Convolution18_ReLU16 Convolution19_ReLU17 0=128 1=3 5=1 6=294912 9=2 -23310=1,0.100000
37
+ Split splitncnn_7 1 2 Convolution19_ReLU17 Convolution19_ReLU17_splitncnn_0 Convolution19_ReLU17_splitncnn_1
38
+ Pooling Pooling3 1 1 Convolution19_ReLU17_splitncnn_1 Pooling3 0=1 4=1
39
+ InnerProduct Convolution20 1 1 Pooling3 Convolution20_ReLU18 0=16 1=1 2=2048 9=1
40
+ InnerProduct Convolution21 1 1 Convolution20_ReLU18 Flatten3 0=128 1=1 2=2048 9=4
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+ Scale Scale3 2 1 Convolution19_ReLU17_splitncnn_0 Flatten3 Scale3 0=-233
42
+ Deconvolution Deconvolution2 1 1 Scale3 Deconvolution2_ReLU19 0=128 1=2 3=2 5=1 6=65536 9=2 -23310=1,0.100000
43
+ Split splitncnn_8 1 2 Deconvolution2_ReLU19 Deconvolution2_ReLU19_splitncnn_0 Deconvolution2_ReLU19_splitncnn_1
44
+ Crop Crop2 2 1 Scale2_splitncnn_0 Deconvolution2_ReLU19_splitncnn_1 Crop2 0=4 1=4
45
+ Eltwise Eltwise2 2 1 Crop2 Deconvolution2_ReLU19_splitncnn_0 Eltwise2 0=1
46
+ Convolution Convolution22 1 1 Eltwise2 Convolution22_ReLU20 0=64 1=3 5=1 6=73728 9=2 -23310=1,0.100000
47
+ Convolution Convolution23 1 1 Convolution22_ReLU20 Convolution23_ReLU21 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
48
+ Split splitncnn_9 1 2 Convolution23_ReLU21 Convolution23_ReLU21_splitncnn_0 Convolution23_ReLU21_splitncnn_1
49
+ Pooling Pooling4 1 1 Convolution23_ReLU21_splitncnn_1 Pooling4 0=1 4=1
50
+ InnerProduct Convolution24 1 1 Pooling4 Convolution24_ReLU22 0=8 1=1 2=512 9=1
51
+ InnerProduct Convolution25 1 1 Convolution24_ReLU22 Flatten4 0=64 1=1 2=512 9=4
52
+ Scale Scale4 2 1 Convolution23_ReLU21_splitncnn_0 Flatten4 Scale4 0=-233
53
+ Deconvolution Deconvolution3 1 1 Scale4 Deconvolution3_ReLU23 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
54
+ Split splitncnn_10 1 2 Deconvolution3_ReLU23 Deconvolution3_ReLU23_splitncnn_0 Deconvolution3_ReLU23_splitncnn_1
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+ Crop Crop3 2 1 Convolution11_ReLU10_splitncnn_0 Deconvolution3_ReLU23_splitncnn_1 Crop3 0=16 1=16
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+ Eltwise Eltwise3 2 1 Crop3 Deconvolution3_ReLU23_splitncnn_0 Eltwise3 0=1
57
+ Convolution Convolution26 1 1 Eltwise3 Convolution26_ReLU24 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
58
+ Convolution Convolution27 1 1 Convolution26_ReLU24 Convolution27 0=3 1=3 5=1 6=1728
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+ Split splitncnn_11 1 2 Convolution27 Convolution27_splitncnn_0 Convolution27_splitncnn_1
60
+ Crop Crop4 2 1 Convolution9_splitncnn_0 Convolution27_splitncnn_1 Crop4 0=20 1=20
61
+ Eltwise Eltwise4 2 1 Crop4 Convolution27_splitncnn_0 Eltwise4 0=1
models/models-cunet/noise0_scale2.0x_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:5329a9375c9cfb64a60a2903fd8ae6e2851d9b069556bf025dbab9d0216fb27c
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+ size 2776400
models/models-cunet/noise0_scale2.0x_model.param ADDED
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+ 7767517
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+ 59 71
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+ Input input 0 1 Input1 0=200 1=200 2=3
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+ Convolution Convolution1 1 1 Input1 Convolution1_ReLU1 0=32 1=3 5=1 6=864 9=2 -23310=1,0.100000
5
+ Convolution Convolution2 1 1 Convolution1_ReLU1 Convolution2_ReLU2 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
6
+ Split splitncnn_0 1 2 Convolution2_ReLU2 Convolution2_ReLU2_splitncnn_0 Convolution2_ReLU2_splitncnn_1
7
+ Convolution Convolution3 1 1 Convolution2_ReLU2_splitncnn_1 Convolution3_ReLU3 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
8
+ Convolution Convolution4 1 1 Convolution3_ReLU3 Convolution4_ReLU4 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
9
+ Convolution Convolution5 1 1 Convolution4_ReLU4 Convolution5_ReLU5 0=64 1=3 5=1 6=73728 9=2 -23310=1,0.100000
10
+ Split splitncnn_1 1 2 Convolution5_ReLU5 Convolution5_ReLU5_splitncnn_0 Convolution5_ReLU5_splitncnn_1
11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
12
+ InnerProduct Convolution6 1 1 Pooling1 Convolution6_ReLU6 0=8 1=1 2=512 9=1
13
+ InnerProduct Convolution7 1 1 Convolution6_ReLU6 Flatten1 0=64 1=1 2=512 9=4
14
+ Scale Scale1 2 1 Convolution5_ReLU5_splitncnn_0 Flatten1 Scale1 0=-233
15
+ Deconvolution Deconvolution1 1 1 Scale1 Deconvolution1_ReLU7 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
16
+ Split splitncnn_2 1 2 Deconvolution1_ReLU7 Deconvolution1_ReLU7_splitncnn_0 Deconvolution1_ReLU7_splitncnn_1
17
+ Crop Crop1 2 1 Convolution2_ReLU2_splitncnn_0 Deconvolution1_ReLU7_splitncnn_1 Crop1 0=4 1=4
18
+ Eltwise Eltwise1 2 1 Crop1 Deconvolution1_ReLU7_splitncnn_0 Eltwise1 0=1
19
+ Convolution Convolution8 1 1 Eltwise1 Convolution8_ReLU8 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
20
+ Deconvolution Deconvolution2 1 1 Convolution8_ReLU8 Deconvolution2 0=3 1=4 3=2 4=3 5=1 6=3072
21
+ Split splitncnn_3 1 2 Deconvolution2 Deconvolution2_splitncnn_0 Deconvolution2_splitncnn_1
22
+ Convolution Convolution9 1 1 Deconvolution2_splitncnn_1 Convolution9_ReLU9 0=32 1=3 5=1 6=864 9=2 -23310=1,0.100000
23
+ Convolution Convolution10 1 1 Convolution9_ReLU9 Convolution10_ReLU10 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
24
+ Split splitncnn_4 1 2 Convolution10_ReLU10 Convolution10_ReLU10_splitncnn_0 Convolution10_ReLU10_splitncnn_1
25
+ Convolution Convolution11 1 1 Convolution10_ReLU10_splitncnn_1 Convolution11_ReLU11 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
26
+ Convolution Convolution12 1 1 Convolution11_ReLU11 Convolution12_ReLU12 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
27
+ Convolution Convolution13 1 1 Convolution12_ReLU12 Convolution13_ReLU13 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
28
+ Split splitncnn_5 1 2 Convolution13_ReLU13 Convolution13_ReLU13_splitncnn_0 Convolution13_ReLU13_splitncnn_1
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+ Pooling Pooling2 1 1 Convolution13_ReLU13_splitncnn_1 Pooling2 0=1 4=1
30
+ InnerProduct Convolution14 1 1 Pooling2 Convolution14_ReLU14 0=16 1=1 2=2048 9=1
31
+ InnerProduct Convolution15 1 1 Convolution14_ReLU14 Flatten2 0=128 1=1 2=2048 9=4
32
+ Scale Scale2 2 1 Convolution13_ReLU13_splitncnn_0 Flatten2 Scale2 0=-233
33
+ Split splitncnn_6 1 2 Scale2 Scale2_splitncnn_0 Scale2_splitncnn_1
34
+ Convolution Convolution16 1 1 Scale2_splitncnn_1 Convolution16_ReLU15 0=128 1=2 3=2 5=1 6=65536 9=2 -23310=1,0.100000
35
+ Convolution Convolution17 1 1 Convolution16_ReLU15 Convolution17_ReLU16 0=256 1=3 5=1 6=294912 9=2 -23310=1,0.100000
36
+ Convolution Convolution18 1 1 Convolution17_ReLU16 Convolution18_ReLU17 0=128 1=3 5=1 6=294912 9=2 -23310=1,0.100000
37
+ Split splitncnn_7 1 2 Convolution18_ReLU17 Convolution18_ReLU17_splitncnn_0 Convolution18_ReLU17_splitncnn_1
38
+ Pooling Pooling3 1 1 Convolution18_ReLU17_splitncnn_1 Pooling3 0=1 4=1
39
+ InnerProduct Convolution19 1 1 Pooling3 Convolution19_ReLU18 0=16 1=1 2=2048 9=1
40
+ InnerProduct Convolution20 1 1 Convolution19_ReLU18 Flatten3 0=128 1=1 2=2048 9=4
41
+ Scale Scale3 2 1 Convolution18_ReLU17_splitncnn_0 Flatten3 Scale3 0=-233
42
+ Deconvolution Deconvolution3 1 1 Scale3 Deconvolution3_ReLU19 0=128 1=2 3=2 5=1 6=65536 9=2 -23310=1,0.100000
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+ Split splitncnn_8 1 2 Deconvolution3_ReLU19 Deconvolution3_ReLU19_splitncnn_0 Deconvolution3_ReLU19_splitncnn_1
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+ Crop Crop2 2 1 Scale2_splitncnn_0 Deconvolution3_ReLU19_splitncnn_1 Crop2 0=4 1=4
45
+ Eltwise Eltwise2 2 1 Crop2 Deconvolution3_ReLU19_splitncnn_0 Eltwise2 0=1
46
+ Convolution Convolution21 1 1 Eltwise2 Convolution21_ReLU20 0=64 1=3 5=1 6=73728 9=2 -23310=1,0.100000
47
+ Convolution Convolution22 1 1 Convolution21_ReLU20 Convolution22_ReLU21 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
48
+ Split splitncnn_9 1 2 Convolution22_ReLU21 Convolution22_ReLU21_splitncnn_0 Convolution22_ReLU21_splitncnn_1
49
+ Pooling Pooling4 1 1 Convolution22_ReLU21_splitncnn_1 Pooling4 0=1 4=1
50
+ InnerProduct Convolution23 1 1 Pooling4 Convolution23_ReLU22 0=8 1=1 2=512 9=1
51
+ InnerProduct Convolution24 1 1 Convolution23_ReLU22 Flatten4 0=64 1=1 2=512 9=4
52
+ Scale Scale4 2 1 Convolution22_ReLU21_splitncnn_0 Flatten4 Scale4 0=-233
53
+ Deconvolution Deconvolution4 1 1 Scale4 Deconvolution4_ReLU23 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
54
+ Split splitncnn_10 1 2 Deconvolution4_ReLU23 Deconvolution4_ReLU23_splitncnn_0 Deconvolution4_ReLU23_splitncnn_1
55
+ Crop Crop3 2 1 Convolution10_ReLU10_splitncnn_0 Deconvolution4_ReLU23_splitncnn_1 Crop3 0=16 1=16
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+ Eltwise Eltwise3 2 1 Crop3 Deconvolution4_ReLU23_splitncnn_0 Eltwise3 0=1
57
+ Convolution Convolution25 1 1 Eltwise3 Convolution25_ReLU24 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
58
+ Convolution Convolution26 1 1 Convolution25_ReLU24 Convolution26 0=3 1=3 5=1 6=1728
59
+ Split splitncnn_11 1 2 Convolution26 Convolution26_splitncnn_0 Convolution26_splitncnn_1
60
+ Crop Crop4 2 1 Deconvolution2_splitncnn_0 Convolution26_splitncnn_1 Crop4 0=20 1=20
61
+ Eltwise Eltwise4 2 1 Crop4 Convolution26_splitncnn_0 Eltwise4 0=1
models/models-cunet/noise1_model.bin ADDED
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+ oid sha256:3407cb87c2503cbd69f8a6703b31bc4949a72080a3e1b1e536dba8bdbfad934f
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+ size 2767568
models/models-cunet/noise1_model.param ADDED
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1
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11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
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+ InnerProduct Convolution6 1 1 Pooling1 Convolution6_ReLU6 0=8 1=1 2=512 9=1
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14
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15
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17
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22
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25
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34
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36
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37
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38
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39
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40
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42
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43
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44
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45
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46
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47
+ Convolution Convolution23 1 1 Convolution22_ReLU20 Convolution23_ReLU21 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
48
+ Split splitncnn_9 1 2 Convolution23_ReLU21 Convolution23_ReLU21_splitncnn_0 Convolution23_ReLU21_splitncnn_1
49
+ Pooling Pooling4 1 1 Convolution23_ReLU21_splitncnn_1 Pooling4 0=1 4=1
50
+ InnerProduct Convolution24 1 1 Pooling4 Convolution24_ReLU22 0=8 1=1 2=512 9=1
51
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52
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53
+ Deconvolution Deconvolution3 1 1 Scale4 Deconvolution3_ReLU23 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
54
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55
+ Crop Crop3 2 1 Convolution11_ReLU10_splitncnn_0 Deconvolution3_ReLU23_splitncnn_1 Crop3 0=16 1=16
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57
+ Convolution Convolution26 1 1 Eltwise3 Convolution26_ReLU24 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
58
+ Convolution Convolution27 1 1 Convolution26_ReLU24 Convolution27 0=3 1=3 5=1 6=1728
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+ Split splitncnn_11 1 2 Convolution27 Convolution27_splitncnn_0 Convolution27_splitncnn_1
60
+ Crop Crop4 2 1 Convolution9_splitncnn_0 Convolution27_splitncnn_1 Crop4 0=20 1=20
61
+ Eltwise Eltwise4 2 1 Crop4 Convolution27_splitncnn_0 Eltwise4 0=1
models/models-cunet/noise1_scale2.0x_model.bin ADDED
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models/models-cunet/noise1_scale2.0x_model.param ADDED
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+ Convolution Convolution5 1 1 Convolution4_ReLU4 Convolution5_ReLU5 0=64 1=3 5=1 6=73728 9=2 -23310=1,0.100000
10
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11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
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+ InnerProduct Convolution6 1 1 Pooling1 Convolution6_ReLU6 0=8 1=1 2=512 9=1
13
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14
+ Scale Scale1 2 1 Convolution5_ReLU5_splitncnn_0 Flatten1 Scale1 0=-233
15
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16
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+ Crop Crop1 2 1 Convolution2_ReLU2_splitncnn_0 Deconvolution1_ReLU7_splitncnn_1 Crop1 0=4 1=4
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19
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23
+ Convolution Convolution10 1 1 Convolution9_ReLU9 Convolution10_ReLU10 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
24
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25
+ Convolution Convolution11 1 1 Convolution10_ReLU10_splitncnn_1 Convolution11_ReLU11 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
26
+ Convolution Convolution12 1 1 Convolution11_ReLU11 Convolution12_ReLU12 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
27
+ Convolution Convolution13 1 1 Convolution12_ReLU12 Convolution13_ReLU13 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
28
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+ Pooling Pooling2 1 1 Convolution13_ReLU13_splitncnn_1 Pooling2 0=1 4=1
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+ InnerProduct Convolution14 1 1 Pooling2 Convolution14_ReLU14 0=16 1=1 2=2048 9=1
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33
+ Split splitncnn_6 1 2 Scale2 Scale2_splitncnn_0 Scale2_splitncnn_1
34
+ Convolution Convolution16 1 1 Scale2_splitncnn_1 Convolution16_ReLU15 0=128 1=2 3=2 5=1 6=65536 9=2 -23310=1,0.100000
35
+ Convolution Convolution17 1 1 Convolution16_ReLU15 Convolution17_ReLU16 0=256 1=3 5=1 6=294912 9=2 -23310=1,0.100000
36
+ Convolution Convolution18 1 1 Convolution17_ReLU16 Convolution18_ReLU17 0=128 1=3 5=1 6=294912 9=2 -23310=1,0.100000
37
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38
+ Pooling Pooling3 1 1 Convolution18_ReLU17_splitncnn_1 Pooling3 0=1 4=1
39
+ InnerProduct Convolution19 1 1 Pooling3 Convolution19_ReLU18 0=16 1=1 2=2048 9=1
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+ InnerProduct Convolution20 1 1 Convolution19_ReLU18 Flatten3 0=128 1=1 2=2048 9=4
41
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+ Deconvolution Deconvolution3 1 1 Scale3 Deconvolution3_ReLU19 0=128 1=2 3=2 5=1 6=65536 9=2 -23310=1,0.100000
43
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44
+ Crop Crop2 2 1 Scale2_splitncnn_0 Deconvolution3_ReLU19_splitncnn_1 Crop2 0=4 1=4
45
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46
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47
+ Convolution Convolution22 1 1 Convolution21_ReLU20 Convolution22_ReLU21 0=64 1=3 5=1 6=36864 9=2 -23310=1,0.100000
48
+ Split splitncnn_9 1 2 Convolution22_ReLU21 Convolution22_ReLU21_splitncnn_0 Convolution22_ReLU21_splitncnn_1
49
+ Pooling Pooling4 1 1 Convolution22_ReLU21_splitncnn_1 Pooling4 0=1 4=1
50
+ InnerProduct Convolution23 1 1 Pooling4 Convolution23_ReLU22 0=8 1=1 2=512 9=1
51
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52
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53
+ Deconvolution Deconvolution4 1 1 Scale4 Deconvolution4_ReLU23 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
54
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56
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57
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+ Split splitncnn_11 1 2 Convolution26 Convolution26_splitncnn_0 Convolution26_splitncnn_1
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+ Crop Crop4 2 1 Deconvolution2_splitncnn_0 Convolution26_splitncnn_1 Crop4 0=20 1=20
61
+ Eltwise Eltwise4 2 1 Crop4 Convolution26_splitncnn_0 Eltwise4 0=1
models/models-cunet/noise2_model.bin ADDED
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models/models-cunet/noise2_model.param ADDED
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+ Convolution Convolution1 1 1 Input1 Convolution1_ReLU1 0=32 1=3 5=1 6=864 9=2 -23310=1,0.100000
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+ Convolution Convolution2 1 1 Convolution1_ReLU1 Convolution2_ReLU2 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
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+ Convolution Convolution5 1 1 Convolution4_ReLU4 Convolution5_ReLU5 0=64 1=3 5=1 6=73728 9=2 -23310=1,0.100000
10
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11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
12
+ InnerProduct Convolution6 1 1 Pooling1 Convolution6_ReLU6 0=8 1=1 2=512 9=1
13
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14
+ Scale Scale1 2 1 Convolution5_ReLU5_splitncnn_0 Flatten1 Scale1 0=-233
15
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16
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+ Crop Crop1 2 1 Convolution2_ReLU2_splitncnn_0 Deconvolution1_ReLU7_splitncnn_1 Crop1 0=4 1=4
18
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19
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22
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23
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24
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25
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26
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27
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28
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+ Pooling Pooling2 1 1 Convolution14_ReLU13_splitncnn_1 Pooling2 0=1 4=1
30
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31
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33
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34
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35
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36
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37
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39
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40
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41
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42
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43
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44
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45
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46
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47
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48
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49
+ Pooling Pooling4 1 1 Convolution23_ReLU21_splitncnn_1 Pooling4 0=1 4=1
50
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51
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52
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53
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54
+ Split splitncnn_10 1 2 Deconvolution3_ReLU23 Deconvolution3_ReLU23_splitncnn_0 Deconvolution3_ReLU23_splitncnn_1
55
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56
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57
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58
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59
+ Split splitncnn_11 1 2 Convolution27 Convolution27_splitncnn_0 Convolution27_splitncnn_1
60
+ Crop Crop4 2 1 Convolution9_splitncnn_0 Convolution27_splitncnn_1 Crop4 0=20 1=20
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11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
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15
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+ Convolution Convolution11 1 1 Convolution10_ReLU10_splitncnn_1 Convolution11_ReLU11 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
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34
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48
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+ Pooling Pooling4 1 1 Convolution22_ReLU21_splitncnn_1 Pooling4 0=1 4=1
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+ Crop Crop4 2 1 Deconvolution2_splitncnn_0 Convolution26_splitncnn_1 Crop4 0=20 1=20
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+ Eltwise Eltwise4 2 1 Crop4 Convolution26_splitncnn_0 Eltwise4 0=1
models/models-cunet/noise3_model.bin ADDED
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10
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11
+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
12
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13
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14
+ Scale Scale1 2 1 Convolution5_ReLU5_splitncnn_0 Flatten1 Scale1 0=-233
15
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23
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24
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25
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26
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+ Pooling Pooling2 1 1 Convolution14_ReLU13_splitncnn_1 Pooling2 0=1 4=1
30
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36
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37
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39
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40
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43
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45
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46
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47
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48
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49
+ Pooling Pooling4 1 1 Convolution23_ReLU21_splitncnn_1 Pooling4 0=1 4=1
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51
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+ Crop Crop4 2 1 Convolution9_splitncnn_0 Convolution27_splitncnn_1 Crop4 0=20 1=20
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+ Eltwise Eltwise4 2 1 Crop4 Convolution27_splitncnn_0 Eltwise4 0=1
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+ Pooling Pooling1 1 1 Convolution5_ReLU5_splitncnn_1 Pooling1 0=1 4=1
12
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13
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14
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23
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24
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25
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26
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27
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32
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33
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39
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40
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41
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45
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46
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47
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48
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50
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51
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52
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53
+ Deconvolution Deconvolution4 1 1 Scale4 Deconvolution4_ReLU23 0=64 1=2 3=2 5=1 6=16384 9=2 -23310=1,0.100000
54
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models/models-upconv_7_photo/noise3_scale2.0x_model.param ADDED
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+ Input input 0 1 Input1 0=156 1=156 2=3
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+ Convolution conv2_layer 1 1 conv1_conv1_relu_layer conv2_conv2_relu_layer 0=32 1=3 5=1 6=4608 9=2 -23310=1,0.100000
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+ Convolution conv4_layer 1 1 conv3_conv3_relu_layer conv4_conv4_relu_layer 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
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+ Convolution conv5_layer 1 1 conv4_conv4_relu_layer conv5_conv5_relu_layer 0=128 1=3 5=1 6=147456 9=2 -23310=1,0.100000
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+ Convolution conv6_layer 1 1 conv5_conv5_relu_layer conv6_conv6_relu_layer 0=256 1=3 5=1 6=294912 9=2 -23310=1,0.100000
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+ Deconvolution conv7_layer 1 1 conv6_conv6_relu_layer Eltwise4 0=3 1=4 3=2 4=3 5=1 6=12288
models/models-upconv_7_photo/scale2.0x_model.bin ADDED
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models/models-upconv_7_photo/scale2.0x_model.param ADDED
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+ 7767517
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+ 8 8
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+ Input input 0 1 Input1 0=156 1=156 2=3
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+ Convolution conv1_layer 1 1 Input1 conv1_conv1_relu_layer 0=16 1=3 5=1 6=432 9=2 -23310=1,0.100000
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+ Convolution conv2_layer 1 1 conv1_conv1_relu_layer conv2_conv2_relu_layer 0=32 1=3 5=1 6=4608 9=2 -23310=1,0.100000
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+ Convolution conv3_layer 1 1 conv2_conv2_relu_layer conv3_conv3_relu_layer 0=64 1=3 5=1 6=18432 9=2 -23310=1,0.100000
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+ Convolution conv4_layer 1 1 conv3_conv3_relu_layer conv4_conv4_relu_layer 0=128 1=3 5=1 6=73728 9=2 -23310=1,0.100000
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+ Convolution conv5_layer 1 1 conv4_conv4_relu_layer conv5_conv5_relu_layer 0=128 1=3 5=1 6=147456 9=2 -23310=1,0.100000
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+ Convolution conv6_layer 1 1 conv5_conv5_relu_layer conv6_conv6_relu_layer 0=256 1=3 5=1 6=294912 9=2 -23310=1,0.100000
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+ Deconvolution conv7_layer 1 1 conv6_conv6_relu_layer Eltwise4 0=3 1=4 3=2 4=3 5=1 6=12288
models/waifu2x-ncnn-vulkan ADDED
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