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dlr predict: output with higher quality
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1b5bb14d8f
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1 changed files with 3 additions and 4 deletions
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@ -245,14 +245,14 @@ def get_overlay(image, coloured_mask):
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return overlay
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return overlay
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def plot_samples_matplotlib(filepath, display_list, figsize=(5, 3)):
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def plot_samples_matplotlib(filepath, display_list):
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for i in range(len(display_list)):
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for i in range(len(display_list)):
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plt.subplot(1, len(display_list), i+1)
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plt.subplot(1, len(display_list), i+1)
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if display_list[i].shape[-1] == 3:
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if display_list[i].shape[-1] == 3:
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plt.imshow(tf.keras.preprocessing.image.array_to_img(display_list[i]))
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plt.imshow(tf.keras.preprocessing.image.array_to_img(display_list[i]))
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else:
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else:
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plt.imshow(display_list[i])
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plt.imshow(display_list[i])
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plt.savefig(filepath)
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plt.savefig(filepath, dpi=200)
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def plot_predictions(filepath, input_items, colormap, model):
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def plot_predictions(filepath, input_items, colormap, model):
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@ -270,8 +270,7 @@ def plot_predictions(filepath, input_items, colormap, model):
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# input_tensor,
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# input_tensor,
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input_pair[1], #label_colourmap
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input_pair[1], #label_colourmap
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prediction_colormap
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prediction_colormap
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],
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]
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figsize=(18, 14)
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)
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)
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i += 1
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i += 1
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