update figure labels

monoloco/eval/eval_kitti.py

@@ -23,7 +23,7 @@ class EvalKitti:
     logging.basicConfig(level=logging.INFO)
     logger = logging.getLogger(__name__)
     CLUSTERS = ('easy', 'moderate', 'hard', 'all', '6', '10', '15', '20', '25', '30', '40', '50', '>50')
-    METHODS = ['m3d', 'geom', 'task_error', '3dop', 'our']
+    METHODS = ['m3d', 'md', 'geom', 'task_error', '3dop', 'our']
     HEADERS = ['method', '<0.5', '<1m', '<2m', 'easy', 'moderate', 'hard', 'all']
     CATEGORIES = ['pedestrian']
 
@@ -157,8 +157,8 @@ class EvalKitti:
                 with open(path, "r") as ff:
                     for line in ff:
                         box = [float(x[:-1]) for x in line.split()[0:4]]
-                        delta_h = (box[3] - box[1]) / 10   # TODO Add new value
-                        delta_w = (box[2] - box[0]) / 10
+                        delta_h = (box[3] - box[1]) / 7
+                        delta_w = (box[2] - box[0]) / 3.5
                         assert delta_h > 0 and delta_w > 0, "Bounding box <=0"
                         box[0] -= delta_w
                         box[1] -= delta_h

monoloco/network/process.py

@@ -21,7 +21,6 @@ def preprocess_monoloco(keypoints, kk):
     uv_center = get_keypoints(keypoints, mode='center')
     xy1_center = pixel_to_camera(uv_center, kk, 10)
     xy1_all = pixel_to_camera(keypoints[:, 0:2, :], kk, 10)
-    # xy1_center[:, 1].fill_(0)  #TODO
     kps_norm = xy1_all - xy1_center.unsqueeze(1)  # (m, 17, 3) - (m, 1, 3)
     kps_out = kps_norm[:, :, 0:2].reshape(kps_norm.size()[0], -1)  # no contiguous for view
     return kps_out

monoloco/run.py

@@ -1,5 +1,4 @@
-
-
+# pylint: disable=too-many-branches, too-many-statements
 import argparse
 
 from openpifpaf.network import nets

monoloco/utils/__init__.py

@@ -5,4 +5,4 @@ from .kitti import check_conditions, get_category, split_training, parse_ground_
 from .camera import xyz_from_distance, get_keypoints, pixel_to_camera, project_3d
 from .logs import set_logger
 from .stereo import depth_from_disparity
-from ..utils.nuscenes import select_categories
+from ..utils.nuscenes import select_categories

monoloco/visuals/figures.py

@@ -31,7 +31,7 @@ def show_results(dic_stats, show=False, save=False):
 
     plt.figure(0)
     plt.grid(linewidth=0.2)
-    plt.xlabel("Distance [meters]")
+    plt.xlabel("Ground-truth distance [m]")
     plt.ylabel("Average localization error [m]")
     plt.xlim(x_min, x_max)
     labels = ['Mono3D', 'Geometric Baseline', 'MonoDepth', 'Our MonoLoco', '3DOP (stereo)']
@@ -52,8 +52,10 @@ def show_results(dic_stats, show=False, save=False):
     plt.legend(loc='upper left')
     if show:
         plt.show()
-    else:
-        plt.savefig(os.path.join(dir_out, 'results.png'))
+    if save:
+        path_fig = os.path.join(dir_out, 'results.png')
+        plt.savefig(path_fig)
+        print("Figure of results saved in {}".format(path_fig))
     plt.close()
 
 
@@ -104,13 +106,16 @@ def show_spread(dic_stats, show=False, save=False):
     if show:
         plt.show()
     if save:
-        plt.savefig(os.path.join(dir_out, 'spread_bi.png'))
+        path_fig = os.path.join(dir_out, 'spread.png')
+        plt.savefig(path_fig)
+        print("Figure of confidence intervals saved in {}".format(path_fig))
     plt.close()
 
 
 def show_task_error(show, save):
     """Task error figure"""
     plt.figure(2)
+    dir_out = 'docs'
     xx = np.linspace(0, 40, 100)
     mu_men = 178
     mu_women = 165
@@ -134,20 +139,23 @@ def show_task_error(show, save):
     plt.plot(xx, yy_male, '-.', linewidth=1.7, color='b', label='Adult male')
     plt.xlim(np.min(xx), np.max(xx))
     plt.xlabel("Ground-truth distance from the camera $d_{gt}$ [m]")
-    plt.ylabel("Localization error $\hat{e}$  due to human height variation [m]")
+    plt.ylabel("Localization error $\hat{e}$  due to human height variation [m]")  # pylint: disable=W1401
     plt.legend(loc=(0.01, 0.55))  # Location from 0 to 1 from lower left
     if show:
         plt.show()
     if save:
-        plt.savefig(os.path.join('docs', 'task_error.png'))
+        path_fig = os.path.join(dir_out, 'task_error.png')
+        plt.savefig(path_fig)
+        print("Figure of task error saved in {}".format(path_fig))
+    plt.close()
 
 
-def show_method():
+def show_method(save):
     """ method figure"""
+    dir_out = 'docs'
     std_1 = 0.75
     fig = plt.figure(1)
     ax = fig.add_subplot(1, 1, 1)
-
     ell_3 = Ellipse((0, 2), width=std_1 * 2, height=0.3, angle=-90, color='b', fill=False, linewidth=2.5)
     ell_4 = Ellipse((0, 2), width=std_1 * 3, height=0.3, angle=-90, color='r', fill=False,
                     linestyle='dashed', linewidth=2.5)
@@ -162,7 +170,10 @@ def show_method():
     plt.yticks([])
     plt.xlabel('X [m]')
     plt.ylabel('Z [m]')
-    plt.savefig(os.path.join('docs', 'output_method.png'))
+    if save:
+        path_fig = os.path.join(dir_out, 'output_method.png')
+        plt.savefig(path_fig)
+        print("Figure of method saved in {}".format(path_fig))
 
 
 def target_error(xx, mm):