# Path: ravens/tasks/cameras.py
# class RealSenseD415():
# class Oracle():
#   CONFIG = [{
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': front_position,
#       'rotation': front_rotation,
#       'zrange': (0.01, 10.),
#       'noise': False
#   }, {
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': left_position,
#       'rotation': left_rotation,
#       'zrange': (0.01, 10.),
#       'noise': False
#   }, {
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': right_position,
#       'rotation': right_rotation,
#       'zrange': (0.01, 10.),
#       'noise': False
#   }]
#   CONFIG = [{
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': position,
#       'rotation': rotation,
#       'zrange': (999.7, 1001.),
#       'noise': False
#   }]
# 
# Path: ravens/utils/utils.py
# def get_heightmap(points, colors, bounds, pixel_size):
# def get_pointcloud(depth, intrinsics):
# def transform_pointcloud(points, transform):
# def reconstruct_heightmaps(color, depth, configs, bounds, pixel_size):
# def pix_to_xyz(pixel, height, bounds, pixel_size, skip_height=False):
# def xyz_to_pix(position, bounds, pixel_size):
# def unproject_vectorized(uv_coordinates, depth_values,
#                          intrinsic,
#                          distortion):
# def unproject_depth_vectorized(im_depth, depth_dist,
#                                camera_mtx,
#                                camera_dist):
# def sample_distribution(prob, n_samples=1):
# def invert(pose):
# def multiply(pose0, pose1):
# def apply(pose, position):
# def eulerXYZ_to_quatXYZW(rotation):  # pylint: disable=invalid-name
# def quatXYZW_to_eulerXYZ(quaternion_xyzw):  # pylint: disable=invalid-name
# def apply_transform(transform_to_from, points_from):
# def preprocess(img):
# def get_fused_heightmap(obs, configs, bounds, pix_size):
# def get_image_transform(theta, trans, pivot=(0, 0)):
# def check_transform(image, pixel, transform):
# def get_se3_from_image_transform(theta, trans, pivot, heightmap, bounds,
#                                  pixel_size):
# def get_random_image_transform_params(image_size):
# def perturb(input_image, pixels, set_theta_zero=False):
# def plot(fname,  # pylint: disable=dangerous-default-value
#          title,
#          ylabel,
#          xlabel,
#          data,
#          xlim=[-np.inf, 0],
#          xticks=None,
#          ylim=[np.inf, -np.inf],
#          show_std=True):
# def create_visualizer(clear=True):
# def make_frame(vis, name, h, radius, o=1.0):
# def meshcat_visualize(vis, obs, act, info):
# COLORS = {
#     'blue': [078.0 / 255.0, 121.0 / 255.0, 167.0 / 255.0],
#     'red': [255.0 / 255.0, 087.0 / 255.0, 089.0 / 255.0],
#     'green': [089.0 / 255.0, 169.0 / 255.0, 079.0 / 255.0],
#     'orange': [242.0 / 255.0, 142.0 / 255.0, 043.0 / 255.0],
#     'yellow': [237.0 / 255.0, 201.0 / 255.0, 072.0 / 255.0],
#     'purple': [176.0 / 255.0, 122.0 / 255.0, 161.0 / 255.0],
#     'pink': [255.0 / 255.0, 157.0 / 255.0, 167.0 / 255.0],
#     'cyan': [118.0 / 255.0, 183.0 / 255.0, 178.0 / 255.0],
#     'brown': [156.0 / 255.0, 117.0 / 255.0, 095.0 / 255.0],
#     'gray': [186.0 / 255.0, 176.0 / 255.0, 172.0 / 255.0]
# }


import os
import numpy as np
import tensorflow as tf
from ravens.tasks import cameras
from ravens.utils import utils
      # [Optional] Get heightmap from RGB-D images.
      configs = act['camera_config']
      colormap, heightmap = self.get_heightmap(obs, configs)  # pylint: disable=unused-variable

      # Do something here.

      # Compute training loss here.
      loss = 0.
      print(f'Train Iter: {self.total_iter + i} Loss: {loss:.4f}')

    self.total_iter += num_iter
    self.save()

  def act(self, obs, info):
    """Run inference and return best action given visual observations."""
    del info

    act = {'camera_config': self.camera_config, 'primitive': None}
    if not obs:
      return act

    # [Optional] Get heightmap from RGB-D images.
    colormap, heightmap = self.get_heightmap(obs, self.camera_config)  # pylint: disable=unused-variable

    # Do something here.

    # Dummy behavior: move to the middle of the workspace.
    p0_position = (self.bounds[:, 1] - self.bounds[:, 0]) / 2
    p0_position += self.bounds[:, 0]
    p1_position = p0_position

# Path: ravens/tasks/cameras.py
# class RealSenseD415():
# class Oracle():
#   CONFIG = [{
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': front_position,
#       'rotation': front_rotation,
#       'zrange': (0.01, 10.),
#       'noise': False
#   }, {
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': left_position,
#       'rotation': left_rotation,
#       'zrange': (0.01, 10.),
#       'noise': False
#   }, {
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': right_position,
#       'rotation': right_rotation,
#       'zrange': (0.01, 10.),
#       'noise': False
#   }]
#   CONFIG = [{
#       'image_size': image_size,
#       'intrinsics': intrinsics,
#       'position': position,
#       'rotation': rotation,
#       'zrange': (999.7, 1001.),
#       'noise': False
#   }]
# 
# Path: ravens/utils/utils.py
# def get_heightmap(points, colors, bounds, pixel_size):
# def get_pointcloud(depth, intrinsics):
# def transform_pointcloud(points, transform):
# def reconstruct_heightmaps(color, depth, configs, bounds, pixel_size):
# def pix_to_xyz(pixel, height, bounds, pixel_size, skip_height=False):
# def xyz_to_pix(position, bounds, pixel_size):
# def unproject_vectorized(uv_coordinates, depth_values,
#                          intrinsic,
#                          distortion):
# def unproject_depth_vectorized(im_depth, depth_dist,
#                                camera_mtx,
#                                camera_dist):
# def sample_distribution(prob, n_samples=1):
# def invert(pose):
# def multiply(pose0, pose1):
# def apply(pose, position):
# def eulerXYZ_to_quatXYZW(rotation):  # pylint: disable=invalid-name
# def quatXYZW_to_eulerXYZ(quaternion_xyzw):  # pylint: disable=invalid-name
# def apply_transform(transform_to_from, points_from):
# def preprocess(img):
# def get_fused_heightmap(obs, configs, bounds, pix_size):
# def get_image_transform(theta, trans, pivot=(0, 0)):
# def check_transform(image, pixel, transform):
# def get_se3_from_image_transform(theta, trans, pivot, heightmap, bounds,
#                                  pixel_size):
# def get_random_image_transform_params(image_size):
# def perturb(input_image, pixels, set_theta_zero=False):
# def plot(fname,  # pylint: disable=dangerous-default-value
#          title,
#          ylabel,
#          xlabel,
#          data,
#          xlim=[-np.inf, 0],
#          xticks=None,
#          ylim=[np.inf, -np.inf],
#          show_std=True):
# def create_visualizer(clear=True):
# def make_frame(vis, name, h, radius, o=1.0):
# def meshcat_visualize(vis, obs, act, info):
# COLORS = {
#     'blue': [078.0 / 255.0, 121.0 / 255.0, 167.0 / 255.0],
#     'red': [255.0 / 255.0, 087.0 / 255.0, 089.0 / 255.0],
#     'green': [089.0 / 255.0, 169.0 / 255.0, 079.0 / 255.0],
#     'orange': [242.0 / 255.0, 142.0 / 255.0, 043.0 / 255.0],
#     'yellow': [237.0 / 255.0, 201.0 / 255.0, 072.0 / 255.0],
#     'purple': [176.0 / 255.0, 122.0 / 255.0, 161.0 / 255.0],
#     'pink': [255.0 / 255.0, 157.0 / 255.0, 167.0 / 255.0],
#     'cyan': [118.0 / 255.0, 183.0 / 255.0, 178.0 / 255.0],
#     'brown': [156.0 / 255.0, 117.0 / 255.0, 095.0 / 255.0],
#     'gray': [186.0 / 255.0, 176.0 / 255.0, 172.0 / 255.0]
# }


# Path: ravens/agents/dummy.py
import os
import numpy as np
import tensorflow as tf
from ravens.tasks import cameras
from ravens.utils import utils

      # [Optional] Get heightmap from RGB-D images.
      configs = act['camera_config']
      colormap, heightmap = self.get_heightmap(obs, configs)  # pylint: disable=unused-variable

      # Do something here.

      # Compute training loss here.
      loss = 0.
      print(f'Train Iter: {self.total_iter + i} Loss: {loss:.4f}')

    self.total_iter += num_iter
    self.save()

  def act(self, obs, info):
    """Run inference and return best action given visual observations."""
    del info

    act = {'camera_config': self.camera_config, 'primitive': None}
    if not obs:
      return act

    # [Optional] Get heightmap from RGB-D images.
    colormap, heightmap = self.get_heightmap(obs, self.camera_config)  # pylint: disable=unused-variable

    # Do something here.

    # Dummy behavior: move to the middle of the workspace.
    p0_position = (self.bounds[:, 1] - self.bounds[:, 0]) / 2
    p0_position += self.bounds[:, 0]
    p1_position = p0_position

    rotation = utils.eulerXYZ_to_quatXYZW((0, 0, 0))