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@@ -26,21 +26,33 @@ class Transformation():
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h, w = list(map(int, self.size.split(',')))
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img_reconstructed = reconstruction.svd(img, [begin, end])
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data_array = np.array(img_reconstructed, 'uint8')
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- data = np.array(Image.fromarray(data_array).thumbnail((h, w)))
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+
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+ img_array = Image.fromarray(data_array)
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+ img_array.thumbnail((h, w))
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+
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+ data = np.array(img_array)
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if self.transformation == 'ipca_reconstruction':
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n_components, batch_size = list(map(int, self.param.split(',')))
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h, w = list(map(int, self.size.split(',')))
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img_reconstructed = reconstruction.ipca(img, n_components, batch_size)
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data_array = np.array(img_reconstructed, 'uint8')
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- data = np.array(Image.fromarray(data_array).thumbnail((h, w)))
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+
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+ img_array = Image.fromarray(data_array)
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+ img_array.thumbnail((h, w))
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+
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+ data = np.array(img_array)
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if self.transformation == 'fast_ica_reconstruction':
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n_components = self.param
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h, w = list(map(int, self.size.split(',')))
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img_reconstructed = reconstruction.fast_ica(img, n_components)
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data_array = np.array(img_reconstructed, 'uint8')
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- data = np.array(Image.fromarray(data_array).thumbnail((h, w)))
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+
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+ img_array = Image.fromarray(data_array)
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+ img_array.thumbnail((h, w))
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+
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+ data = np.array(img_array)
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if self.transformation == 'min_diff_filter':
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w_size, h_size = list(map(int, self.param.split(',')))
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@@ -48,13 +60,13 @@ class Transformation():
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# bilateral with window of size (`w_size`, `h_size`)
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lab_img = transform.get_LAB_L(img)
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-
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- lab_img = Image.fromarray(lab_img)
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- lab_img.thumbnail((h, w))
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-
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- diff_img = convolution.convolution2D(lab_img, kernels.min_bilateral_diff, (w_size, h_size))
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-
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- data = np.array(diff_img*255, 'uint8')
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+
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+ img_filter = convolution.convolution2D(lab_img, kernels.min_bilateral_diff, (w_size, h_size))
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+ diff_array = np.array(img_filter*255, 'uint8')
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+ diff_img = Image.fromarray(diff_array)
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+ diff_img.thumbnail((h, w))
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+
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+ data = np.array(diff_img)
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if self.transformation == 'static':
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# static content, we keep input as it is
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