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import os |
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import sys |
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import matplotlib.pyplot as plt |
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import numpy as np |
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import pandas as pd |
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from menpo.visualize.viewmatplotlib import sample_colours_from_colourmap |
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from prettytable import PrettyTable |
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from sklearn.metrics import auc |
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from sklearn.metrics import roc_curve |
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with open(sys.argv[1], "r") as f: |
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files = f.readlines() |
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files = [x.strip() for x in files] |
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image_path = "/train_tmp/IJB_release/IJBC" |
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def read_template_pair_list(path): |
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pairs = pd.read_csv(path, sep=" ", header=None).values |
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t1 = pairs[:, 0].astype(np.int) |
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t2 = pairs[:, 1].astype(np.int) |
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label = pairs[:, 2].astype(np.int) |
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return t1, t2, label |
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p1, p2, label = read_template_pair_list(os.path.join("%s/meta" % image_path, "%s_template_pair_label.txt" % "ijbc")) |
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methods = [] |
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scores = [] |
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for file in files: |
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methods.append(file) |
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scores.append(np.load(file)) |
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methods = np.array(methods) |
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scores = dict(zip(methods, scores)) |
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colours = dict(zip(methods, sample_colours_from_colourmap(methods.shape[0], "Set2"))) |
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x_labels = [10**-6, 10**-5, 10**-4, 10**-3, 10**-2, 10**-1] |
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tpr_fpr_table = PrettyTable(["Methods"] + [str(x) for x in x_labels]) |
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fig = plt.figure() |
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for method in methods: |
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fpr, tpr, _ = roc_curve(label, scores[method]) |
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roc_auc = auc(fpr, tpr) |
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fpr = np.flipud(fpr) |
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tpr = np.flipud(tpr) |
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plt.plot( |
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fpr, tpr, color=colours[method], lw=1, label=("[%s (AUC = %0.4f %%)]" % (method.split("-")[-1], roc_auc * 100)) |
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) |
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tpr_fpr_row = [] |
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tpr_fpr_row.append(method) |
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for fpr_iter in np.arange(len(x_labels)): |
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_, min_index = min(list(zip(abs(fpr - x_labels[fpr_iter]), range(len(fpr))))) |
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tpr_fpr_row.append("%.2f" % (tpr[min_index] * 100)) |
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tpr_fpr_table.add_row(tpr_fpr_row) |
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plt.xlim([10**-6, 0.1]) |
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plt.ylim([0.3, 1.0]) |
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plt.grid(linestyle="--", linewidth=1) |
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plt.xticks(x_labels) |
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plt.yticks(np.linspace(0.3, 1.0, 8, endpoint=True)) |
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plt.xscale("log") |
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plt.xlabel("False Positive Rate") |
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plt.ylabel("True Positive Rate") |
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plt.title("ROC on IJB") |
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plt.legend(loc="lower right") |
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print(tpr_fpr_table) |
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