format with Black

run.py

@@ -20,11 +20,10 @@ def run(args):
         raise ValueError(f"Cannot find setting file at {setting_file}")
     if args.pose_id < -1:
         raise ValueError(f"Pose index must be -1 or >0")
-
 
     with open(args.settings) as fs:
-         settings_yalm = yaml.safe_load(fs)
-         print("\nAlgorithm " + settings_yalm["SLAM.alg"] + " has been set\n")
+        settings_yalm = yaml.safe_load(fs)
+        print("\nAlgorithm " + settings_yalm["SLAM.alg"] + " has been set\n")
 
     print("Dataset selected: " + os.path.basename(args.dataset) + "\n")
 
@@ -61,24 +60,24 @@ def run(args):
                 raise ValueError(f"failed to load image {image_name}")
 
             image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-           
+
             state = app.process_image_mono(image, timestamps[idx])
 
             # NOTE: we buid a default invalid depth, in the case of system failure
             if state == slampy.State.OK:
-                depth = app.get_depth() 
+                depth = app.get_depth()
                 pose_past_frame_to_current = app.get_pose_to_target(
                     precedent_frame=args.pose_id
                 )
-                name = os.path.splitext(os.path.basename(image_name))[0] 
-                
-                depth_path = os.path.join(dest_depth, name)  
-                save_depth(depth_path, depth) 
+                name = os.path.splitext(os.path.basename(image_name))[0]
+
+                depth_path = os.path.join(dest_depth, name)
+                save_depth(depth_path, depth)
 
                 pose_path = os.path.join(dest_pose, name)
                 save_pose(pose_path, pose_past_frame_to_current)
 
-                curr_pose = app.get_pose_to_target(-1) 
+                curr_pose = app.get_pose_to_target(-1)
                 if curr_pose is not None:
                     save_pose_txt(args, name, curr_pose)
 
@@ -89,12 +88,11 @@ def run(args):
 
             states.append(state)
             pbar.update(1)
-        
-        if args.is_evaluate_depth: 
-            mean_errors = np.array(errors).mean(0) 
+
+        if args.is_evaluate_depth:
+            mean_errors = np.array(errors).mean(0)
             save_results = os.path.join(args.dest, "results.txt")
             save_depth_err_results(save_results, "mean values", mean_errors)
-
 
     # NOTE: final dump of log.txt file
     with open(os.path.join(args.dest, "log.txt"), "w") as f:
@@ -164,7 +162,7 @@ def run(args):
     type=str,
     help="which dataset type",
     default="KITTI_VO",
-    choices=["TUM", "KITTI_VO", "KITTI","OTHERS"],
+    choices=["TUM", "KITTI_VO", "KITTI", "OTHERS"],
 )
 
 parser.add_argument(

run_MONO_IMU.py

@@ -20,11 +20,10 @@ def run(args):
         raise ValueError(f"Cannot find setting file at {setting_file}")
     if args.pose_id < -1:
         raise ValueError(f"Pose index must be -1 or >0")
-
 
     with open(args.settings) as fs:
-         settings_yalm = yaml.safe_load(fs)
-         print("\nAlgorithm " + settings_yalm["SLAM.alg"] + " has been set\n")
+        settings_yalm = yaml.safe_load(fs)
+        print("\nAlgorithm " + settings_yalm["SLAM.alg"] + " has been set\n")
 
     print("Dataset selected: " + os.path.basename(args.dataset) + "\n")
 
@@ -41,7 +40,7 @@ def run(args):
 
     num_images = len(image_filenames)
 
-    if args.data_type == "TUM_VI" or args.data_type =="EUROC":
+    if args.data_type == "TUM_VI" or args.data_type == "EUROC":
         acc_data, gyro_data, IMUtimestamps = load_IMU_datas_TUM_VI(args.dataset)
 
     dest_depth = os.path.join(args.dest, "depth")
@@ -53,14 +52,15 @@ def run(args):
     states = []
     errors = []
 
-
-    #finds first useful imu data, assuming imu starts recording way before camera
-    firstIMU=0
-    while(IMUtimestamps[firstIMU]<=timestamps[0]):
+    # finds first useful imu data, assuming imu starts recording way before camera
+    firstIMU = 0
+    while IMUtimestamps[firstIMU] <= timestamps[0]:
         firstIMU += 1
     firstIMU -= 1
-
-    imu = [] # array of valid imu measurments: one imu measure is 7 floats [acc x, acc y, acc z, gyro x, gyro y, gyro z, timestamp]
+
+    imu = (
+        []
+    )  # array of valid imu measurments: one imu measure is 7 floats [acc x, acc y, acc z, gyro x, gyro y, gyro z, timestamp]
 
     with tqdm(total=num_images) as pbar:
         for idx, image_name in enumerate(image_filenames):
@@ -71,34 +71,34 @@ def run(args):
 
             image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
-            imu.clear() #clear imu measures from last frame
-
-
+            imu.clear()  # clear imu measures from last frame
 
-            if idx > 0:  #select only those imu meas that occour in time before the current frame
-                while(IMUtimestamps[firstIMU]<=timestamps[idx]):                 
-                    imu_valid_meas = (acc_data[firstIMU] + gyro_data[firstIMU])
+            if (
+                idx > 0
+            ):  # select only those imu meas that occour in time before the current frame
+                while IMUtimestamps[firstIMU] <= timestamps[idx]:
+                    imu_valid_meas = acc_data[firstIMU] + gyro_data[firstIMU]
                     imu_valid_meas.append(IMUtimestamps[firstIMU])
                     imu.append(imu_valid_meas)
                     firstIMU += 1
-          
+
             state = app.process_image_imu_mono(image, timestamps[idx], np.array(imu))
 
             # NOTE: we buid a default invalid depth, in the case of system failure
             if state == slampy.State.OK:
-                depth = app.get_depth() 
+                depth = app.get_depth()
                 pose_past_frame_to_current = app.get_pose_to_target(
                     precedent_frame=args.pose_id
                 )
-                name = os.path.splitext(os.path.basename(image_name))[0] 
-                
-                depth_path = os.path.join(dest_depth, name)  
-                save_depth(depth_path, depth) 
+                name = os.path.splitext(os.path.basename(image_name))[0]
+
+                depth_path = os.path.join(dest_depth, name)
+                save_depth(depth_path, depth)
 
                 pose_path = os.path.join(dest_pose, name)
                 save_pose(pose_path, pose_past_frame_to_current)
 
-                curr_pose = app.get_pose_to_target(-1) 
+                curr_pose = app.get_pose_to_target(-1)
                 if curr_pose is not None:
                     save_pose_txt(args, name, curr_pose)
 
@@ -109,12 +109,11 @@ def run(args):
 
             states.append(state)
             pbar.update(1)
-        
-        if args.is_evaluate_depth: 
-            mean_errors = np.array(errors).mean(0) 
+
+        if args.is_evaluate_depth:
+            mean_errors = np.array(errors).mean(0)
             save_results = os.path.join(args.dest, "results.txt")
             save_depth_err_results(save_results, "mean values", mean_errors)
-
 
     # NOTE: final dump of log.txt file
     with open(os.path.join(args.dest, "log.txt"), "w") as f:
@@ -126,7 +125,7 @@ def run(args):
         evaluate_pose(args)
         eval_tool = KittiEvalOdom()
         eval_tool.eval(args)
-    
+
     app.shutdown()
 
 
@@ -186,7 +185,7 @@ def run(args):
     type=str,
     help="which dataset type",
     default="KITTI_VO",
-    choices=["TUM", "KITTI_VO", "KITTI","OTHERS","TUM_VI","EUROC"],
+    choices=["TUM", "KITTI_VO", "KITTI", "OTHERS", "TUM_VI", "EUROC"],
 )
 
 parser.add_argument(

slam_method/OrbSlam3.py

@@ -75,7 +75,8 @@ def process_image_imu_mono(self, image, tframe, imu):
     def process_image_imu_stereo(self, image_left, image_right, tframe, imu):
         if self.sensor_type == Sensor.STEREO_IMU:
             self.slam.process_image_imu_stereo(
-                image_left, image_right, tframe, "0", imu)
+                image_left, image_right, tframe, "0", imu
+            )
         else:
             raise Exception("The sensor type is not STREO_IMU")