Args: dataset: The dataset returned by ``compute_attr`` Returns: The pairwise distance matrix D """ from sklearn.metrics.pairwise import pairwise_distances as pwdist gA, gY, pA, pY = dataset return pwdist(gA, pA, 'euclidean') if __name__ == '__main__': data = load_data(['CUHKL']) data = decompose(data) dataset = preprocess(data) import cPickle with open('../cache/attr_model.pkl', 'rb') as f: model = cPickle.load(f) dataset = compute_attr(model, dataset) D = compute_distance(dataset) from reid.utils import cmc cmcret = cmc.count(D, dataset[1], dataset[3], 100) print cmcret
R[i] = output_func(X[i:i + 1, :]).ravel() R = numpy.asarray(R) D = cdist(R, Y, 'euclidean') G = numpy.asarray([pid for pid, image in data[0]]) P = numpy.asarray([pid for pid, image in data[1]]) if save_to_cache: with open(_cached_distmat, 'wb') as f: cPickle.dump((D, G, P), f, protocol=cPickle.HIGHEST_PROTOCOL) with open(_cached_output, 'wb') as f: cPickle.dump((X, Y, R), f, protocol=cPickle.HIGHEST_PROTOCOL) return (D, G, P) if __name__ == '__main__': views_data, datasets = _prepare_data(load_from_cache=True, save_to_cache=False) model = _train_model(datasets, load_from_cache=False, save_to_cache=True) distmat, glabels, plabels = _get_distance(model, views_data, load_from_cache=False, save_to_cache=True) print cmc.count(distmat, glabels, plabels, 100)
for i in xrange(X.shape[0]): R[i] = output_func(X[i:i+1, :]).ravel() R = numpy.asarray(R) D = cdist(R, Y, 'euclidean') G = numpy.asarray([pid for pid, image in data[0]]) P = numpy.asarray([pid for pid, image in data[1]]) if save_to_cache: with open(_cached_distmat, 'wb') as f: cPickle.dump((D, G, P), f, protocol=cPickle.HIGHEST_PROTOCOL) with open(_cached_output, 'wb') as f: cPickle.dump((X, Y, R), f, protocol=cPickle.HIGHEST_PROTOCOL) return (D, G, P) if __name__ == '__main__': views_data, datasets = _prepare_data(load_from_cache=True, save_to_cache=False) model = _train_model(datasets, load_from_cache=False, save_to_cache=True) distmat, glabels, plabels = _get_distance(model, views_data, load_from_cache=False, save_to_cache=True) print cmc.count(distmat, glabels, plabels, 100)