remove unused imports

.pre-commit-config.yaml

@@ -2,7 +2,7 @@ default_language_version:
     python: python3.8
 repos:
   - repo: https://github.com/psf/black
-    rev: stable
+    rev: 22.1.0
     hooks:
       - id: black
         language_version: python3.8

calvin_env/camera/camera.py

@@ -46,13 +46,13 @@ def process_rgbd(self, obs, nearval, farval):
     # Reference: world2pixel
     # https://github.com/bulletphysics/bullet3/issues/1952
     def project(self, point):
-        '''
-            Projects a world point in homogeneous coordinates to pixel coordinates
-            Args
-                point: np.array of len 4; indicates the desired point to project
-            Output
-                (x, y): tuple (u, v); pixel coordinates of the projected point
-        '''
+        """
+        Projects a world point in homogeneous coordinates to pixel coordinates
+        Args
+            point: np.array of len 4; indicates the desired point to project
+        Output
+            (x, y): tuple (u, v); pixel coordinates of the projected point
+        """
 
         # reshape to get homogeneus transform
         persp_m = np.array(self.projectionMatrix).reshape((4, 4)).T
@@ -67,16 +67,16 @@ def project(self, point):
         return (x, y)
 
     def deproject(self, point, depth_img, homogeneous=False):
-        '''
-            Deprojects a pixel point to 3D coordinates
-            Args
-                point: tuple (u, v); pixel coordinates of point to deproject
-                depth_img: np.array; depth image used as reference to generate 3D coordinates
-                homogeneous: bool; if true it returns the 3D point in homogeneous coordinates,
-                             else returns the world coordinates (x, y, z) position
-            Output
-                (x, y): np.array; world coordinates of the deprojected point
-        '''
+        """
+        Deprojects a pixel point to 3D coordinates
+        Args
+            point: tuple (u, v); pixel coordinates of point to deproject
+            depth_img: np.array; depth image used as reference to generate 3D coordinates
+            homogeneous: bool; if true it returns the 3D point in homogeneous coordinates,
+                         else returns the world coordinates (x, y, z) position
+        Output
+            (x, y): np.array; world coordinates of the deprojected point
+        """
         T_world_cam = np.linalg.inv(np.array(self.viewMatrix).reshape((4, 4)).T)
 
         u, v = point
@@ -85,7 +85,7 @@ def deproject(self, point, depth_img, homogeneous=False):
         x = (u - self.width // 2) * z / foc
         y = -(v - self.height // 2) * z / foc
         z = -z
-        world_pos = (T_world_cam @ np.array([x, y, z, 1]))
-        if(not homogeneous):
+        world_pos = T_world_cam @ np.array([x, y, z, 1])
+        if not homogeneous:
             world_pos = world_pos[:3]
-        return world_pos
+        return world_pos

calvin_env/camera/tactile_sensor.py

@@ -1,7 +1,6 @@
 import os
 
 import numpy as np
-import pybullet as p
 
 from calvin_env.camera.camera import Camera
 import tacto

calvin_env/datarenderer.py

@@ -170,7 +170,7 @@ def set_static_cams_from_gui(cfg, load_dir, max_frames):
             fov = cam.fov
             while True:
                 file_path = load_dir / f"{frame:012d}.pickle"
-                state_ob, done, info = env.reset_from_storage(file_path)
+                _, _, _ = env.reset_from_storage(file_path)
                 env.p.stepSimulation()
                 frame_rgbs, frame_depths = env.get_camera_obs()
                 rgb_static = frame_rgbs[cam_index]

calvin_env/envs/play_lmp_wrapper.py

@@ -2,7 +2,7 @@
 import os
 from typing import Any, Dict, Tuple, Union
 
-from calvin_agent.datasets.utils.episode_utils import process_actions, process_depth, process_rgb, process_state
+from calvin_agent.datasets.utils.episode_utils import process_depth, process_rgb, process_state
 import gym
 import numpy as np
 import torch

calvin_env/envs/play_table_env.py

@@ -1,4 +1,3 @@
-from copy import deepcopy
 import logging
 from math import pi
 import os
@@ -19,13 +18,15 @@
 import pybullet_utils.bullet_client as bc
 
 import calvin_env
-from calvin_env.utils.utils import FpsController, get_git_commit_hash, timeit
+from calvin_env.utils.utils import FpsController, get_git_commit_hash
 
 # A logger for this file
 log = logging.getLogger(__name__)
 from rich.traceback import install
+
 install(show_locals=True)
 
+
 class PlayTableSimEnv(gym.Env):
     def __init__(
         self,
@@ -262,7 +263,7 @@ def reset_from_storage(self, filename):
         return data["state_obs"], data["done"], data["info"]
 
     def serialize(self):
-        data = {"time": time.time_ns() / (10 ** 9), "robot": self.robot.serialize(), "scene": self.scene.serialize()}
+        data = {"time": time.time_ns() / (10**9), "robot": self.robot.serialize(), "scene": self.scene.serialize()}
         return data
 
 
@@ -294,9 +295,10 @@ def run_env(cfg):
 
     env.reset()
     while True:
-        env.step(np.array((0.,0, 0,0,0, 1)))
+        env.step(np.array((0.0, 0, 0, 0, 0, 1)))
         # env.render()
         time.sleep(0.01)
 
+
 if __name__ == "__main__":
     run_env()

calvin_env/envs/tasks.py

@@ -5,8 +5,6 @@
 from omegaconf import ListConfig
 from scipy.spatial.transform import Rotation as R
 
-from calvin_env.utils.utils import timeit
-
 
 class Tasks:
     def __init__(self, tasks):

calvin_env/robot/IKfast.py

@@ -1,6 +1,5 @@
-from ikfast_franka_panda import get_dof, get_fk, get_free_dof, get_ik
+from ikfast_franka_panda import get_ik
 import numpy as np
-import pybullet as p
 from scipy.spatial.transform import Rotation as R
 
 

calvin_env/robot/robot.py

@@ -1,14 +1,9 @@
 import logging
-import math
-import os
 
-import cv2
 import numpy as np
 import pybullet as p
-import quaternion
 
 from calvin_env.robot.mixed_ik import MixedIK
-from calvin_env.utils.utils import timeit
 
 # A logger for this file
 log = logging.getLogger(__name__)

calvin_env/scene/objects/button.py

@@ -66,7 +66,7 @@ def _is_pressed(self):
             return self.get_state() < self.trigger_threshold
 
     def get_state(self):
-        """ return button joint state """
+        """return button joint state"""
         return float(self.p.getJointState(self.uid, self.joint_index, physicsClientId=self.cid)[0])
 
     def get_info(self):

calvin_env/scene/objects/movable_object.py

@@ -1,7 +1,6 @@
 import logging
 
 import numpy as np
-from omegaconf import ListConfig
 from omegaconf.errors import ConfigKeyError
 
 from calvin_env.scene.objects.base_object import BaseObject

calvin_env/scene/objects/switch.py

@@ -63,7 +63,7 @@ def is_pressed(self):
             return self.get_state() < self.trigger_threshold
 
     def get_state(self):
-        """ return button joint state """
+        """return button joint state"""
         return float(self.p.getJointState(self.uid, self.joint_index, physicsClientId=self.cid)[0])
 
     def get_info(self):

calvin_env/scripts/check_tasks.py

@@ -1,16 +1,10 @@
-from copy import deepcopy
-import glob
-import os
 from pathlib import Path
-import time
 
 import cv2
 import hydra
 import numpy as np
 import pybullet as p
 
-from calvin_env.envs.tasks import Tasks
-
 """
 This script loads a rendered episode and replays it using the recorded actions.
 Optionally, gaussian noise can be added to the actions.

calvin_env/scripts/record_video_icra.py

@@ -1,6 +1,4 @@
 from copy import deepcopy
-import glob
-import os
 from pathlib import Path
 import time
 
@@ -10,7 +8,6 @@
 import numpy as np
 import pybullet as p
 
-from calvin_env.envs.tasks import Tasks
 from calvin_env.utils import utils
 
 """
@@ -81,34 +78,34 @@ def run_env(cfg):
             cv2.imshow("im", im)
             cv2.waitKey(1)
             video.write(im[:, :, ::-1])
-            # video_gripper.write(depth2rgb(obs["depth_obs"][1], minval=0.1, maxval=0.5)[:, :, ::-1])
-            # video_static.write(depth2rgb(obs["depth_obs"][0], minval=3.5, maxval=5)[:, :, ::-1])
+            video_gripper.write(depth2rgb(obs["depth_obs"][1], minval=0.1, maxval=0.5)[:, :, ::-1])
+            video_static.write(depth2rgb(obs["depth_obs"][0], minval=3.5, maxval=5)[:, :, ::-1])
             # action = data["rel_actions"]
-            # action = np.split(data["actions"], [3, 6])
-            # action = noise(action)
+            action = np.split(data["actions"], [3, 6])
+            action = noise(action)
 
-            # rel_actions.append(create_relative_action(data["actions"], data["robot_obs"][:6]))
+            rel_actions.append(utils.to_relative_action(data["actions"], data["robot_obs"][:6]))
             # action = utils.to_relative_action(data["actions"], data["robot_obs"], max_pos=0.04, max_orn=0.1)
             # tcp_pos, tcp_orn = p.getLinkState(env.robot.robot_uid, env.robot.tcp_link_id, physicsClientId=env.cid)[:2]
             # tcp_orn = p.getEulerFromQuaternion(tcp_orn)
-            # action2 = create_relative_action(data["actions"], np.concatenate([tcp_pos, tcp_orn]))
-            # o, _, _, info = env.step(action)
-            # print(info["scene_info"]["lights"]["led"]["logical_state"])
-            # if (i - s) % 32 != 0:
-            #     print(tasks.get_task_info(prev_info, info))
-            # else:
-            #     prev_info = deepcopy(info)
-            # time.sleep(0.01)
-    # video.release()
+            # action2 = utils.to_relative_action(data["actions"], np.concatenate([tcp_pos, tcp_orn]))
+            o, _, _, info = env.step(action)
+            print(info["scene_info"]["lights"]["led"]["logical_state"])
+            if (i - s) % 32 != 0:
+                print(tasks.get_task_info(prev_info, info))
+            else:
+                prev_info = deepcopy(info)
+            time.sleep(0.01)
+    video.release()
     video_static.release()
     video_gripper.release()
     print(time.time() - t1)
-    # rel_actions = np.array(rel_actions)
-    # for j in range(rel_actions.shape[1]):
-    #     plt.figure(j)
-    #     plt.hist(rel_actions[:, j], bins=10)
-    #     plt.plot()
-    #     plt.show()
+    rel_actions = np.array(rel_actions)
+    for j in range(rel_actions.shape[1]):
+        plt.figure(j)
+        plt.hist(rel_actions[:, j], bins=10)
+        plt.plot()
+        plt.show()
 
 
 if __name__ == "__main__":

calvin_env/utils/utils.py

@@ -33,7 +33,7 @@ def timed(*args, **kw):
 
 class FpsController:
     def __init__(self, freq):
-        self.loop_time = (1.0 / freq) * 10 ** 9
+        self.loop_time = (1.0 / freq) * 10**9
         self.prev_time = time.time_ns()
 
     def step(self):

requirements.txt

@@ -13,4 +13,3 @@ pandas
 pybullet
 scipy
 rich
-