48 lines
978 B
Python
48 lines
978 B
Python
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from m import *
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from matplotlib import pyplot as plt
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def __prep_conf_matr(data):
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output_matrix = np.zeros([2, 2])
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for p, r in zip(*data):
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print(p, r)
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output_matrix[np.argmax(p)][np.argmax(r)] += 1
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return output_matrix
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def __plot_conf_matr(data):
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matr = __prep_conf_matr(data)
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_, ax = plt.subplots()
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ax.matshow(matr, cmap = plt.cm.Blues)
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for i, x in enumerate(matr):
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for j, y in enumerate(x):
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ax.text(i,
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j,
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str(round(y)),
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va = "center",
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ha = "center")
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plt.show()
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ds = tf.keras.preprocessing.image_dataset_from_directory(
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'../dataset-orig-aug-1-mini-1/',
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labels = 'inferred',
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label_mode = 'categorical',
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color_mode = 'rgb',
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image_size = (300, 300),
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batch_size = 32,
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verbose = True
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)
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#ds_short = ds.take(1)
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p = mod.predict(ds)
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r = np.concatenate([y for x, y in ds])
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__plot_conf_matr([p, r])
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