visualize_results.py

import h5py
from matplotlib import pyplot as plt
import argparse
import os
import os.path as osp

parser = argparse.ArgumentParser()
parser.add_argument('-p', '--path', type=str, required=True,
                    help="path to h5 file containing summarization results")
args = parser.parse_args()

h5_res = h5py.File(args.path, 'r')
keys = h5_res.keys()

for key in keys:
    score = h5_res[key]['score'][...]
    machine_summary = h5_res[key]['machine_summary'][...]
    gtscore = h5_res[key]['gtscore'][...]
    fm = h5_res[key]['fm'][()]

    # plot score vs gtscore
    fig, axs = plt.subplots(2)
    n = len(gtscore)
    axs[0].plot(range(n), gtscore, color='red')
    axs[0].set_xlim(0, n)
    axs[0].set_yticklabels([])
    axs[0].set_xticklabels([])
    axs[1].set_title("video {} F-score {:.1%}".format(key, fm))
    axs[1].plot(range(n), score, color='blue')
    axs[1].set_xlim(0, n)
    axs[1].set_yticklabels([])
    axs[1].set_xticklabels([])
    fig.savefig(osp.join(osp.dirname(args.path), 'score_' + key + '.png'), bbox_inches='tight')
    plt.close()

    print "Done video {}. # frames {}.".format(key, len(machine_summary))

h5_res.close()