From b6396cba77066f2a2344277dc8875b0120b56516 Mon Sep 17 00:00:00 2001 From: Alexandre Boulch Date: Mon, 17 Dec 2018 10:47:51 +0100 Subject: [PATCH] Fix path --- test.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/test.py b/test.py index f363e88..825dfd0 100644 --- a/test.py +++ b/test.py @@ -40,18 +40,18 @@ if scale_number == 1: Ks=np.array([K], dtype=np.int) import models.model_1s as model_1s - model = model_1s.load_model("/media/data/research/normals_HoughCNN/model_1s_boulch_SGP2016/model.pth") - mean = np.load("/media/data/research/normals_HoughCNN/model_1s_boulch_SGP2016/mean.npz")["arr_0"] + model = model_1s.load_model("path_to_model_1s/model.pth") + mean = np.load("path_to_model_1s/mean.npz")["arr_0"] elif scale_number == 3: Ks=np.array([K,K/2,K*2], dtype=np.int) import models.model_3s as model_3s - model = model_3s.load_model("/media/data/research/normals_HoughCNN/model_3s_boulch_SGP2016/model.pth") - mean = np.load("/media/data/research/normals_HoughCNN/model_3s_boulch_SGP2016/mean.npz")["arr_0"] + model = model_3s.load_model("path_to_model_3s/model.pth") + mean = np.load("path_to_model_1s/mean.npz")["arr_0"] elif scale_number == 5: Ks=np.array([K,K/4,K/2,K*2,K*4], dtype=np.int) import models.model_5s as model_5s - model = model_5s.load_model("/media/data/research/normals_HoughCNN/model_5s_boulch_SGP2016/model.pth") - mean = np.load("/media/data/research/normals_HoughCNN/model_5s_boulch_SGP2016/mean.npz")["arr_0"] + model = model_5s.load_model("path_to_model_5s/model.pth") + mean = np.load("path_to_model_5s/mean.npz")["arr_0"] # set the neighborhood size estimator.set_Ks(Ks)