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Update app.py
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app.py
CHANGED
@@ -1,6 +1,7 @@
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import cv2
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import numpy as np
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import paddle
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from Generater import Generater
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import gradio as gr
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@@ -16,10 +17,16 @@ def style_transfer(content_img,style_img):
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g_input = content_img.astype('float32') / 127.5 - 1 # 归一化
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g_input = g_input[np.newaxis, ...].transpose(0, 3, 1, 2) # NHWC -> NCHW
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g_input = paddle.to_tensor(g_input) # numpy -> tensor
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g_input_s = style_img.astype('float32') / 127.5 - 1 # 归一化
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g_input_s = g_input_s[np.newaxis, ...].transpose(0, 3, 1, 2) # NHWC -> NCHW
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g_input_s = paddle.to_tensor(g_input_s) # numpy -> tensor
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i = paddle.to_tensor([1.])
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g_output = generator(g_input,g_input_s,i)
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import cv2
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import numpy as np
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import paddle
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import paddle.nn.functional as F
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from Generater import Generater
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import gradio as gr
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g_input = content_img.astype('float32') / 127.5 - 1 # 归一化
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g_input = g_input[np.newaxis, ...].transpose(0, 3, 1, 2) # NHWC -> NCHW
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g_input = paddle.to_tensor(g_input) # numpy -> tensor
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h,w = g_input.shape[-2:]
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p = max([h,w])
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g_input = F.interpolate(g_input,scale_factor=(256/p))
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g_input_s = style_img.astype('float32') / 127.5 - 1 # 归一化
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g_input_s = g_input_s[np.newaxis, ...].transpose(0, 3, 1, 2) # NHWC -> NCHW
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g_input_s = paddle.to_tensor(g_input_s) # numpy -> tensor
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h,w = g_input_s.shape[-2:]
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p = max([h,w])
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g_input_s = F.interpolate(g_input_s,scale_factor=(256/p))
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i = paddle.to_tensor([1.])
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g_output = generator(g_input,g_input_s,i)
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