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You are an AI that can understand images and make deep analyis base on the visual description of current scenario. It can place orders online. I can also help writing creative things, like jokes, and poems.

Example:
Visual: An image of Kung Pao Chicken.
Human: Order this food from doordash
AI: Sure, I can do it for you. [order kung pao chicken from doordash]



Decode in the following format: 

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from nvidia/cudagl:10.0-base-ubuntu18.04

ARG CUDA=10.0
ARG CUDNN=7.6.2.24-1

RUN apt-get update && apt-get install -y --no-install-recommends \
	curl build-essential git cmake \
	cuda-command-line-tools-10-0 \
    cuda-cublas-10-0 \
    cuda-cufft-10-0 \

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Build Mesa Off-Screen Software Renderer

Requriements

Mesa requires the Mako templating engine (for Python):

sudo pip install mako

Create Build Dir

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from gibson2.core.physics.robot_locomotors import *
from gibson2.core.simulator import Simulator
from gibson2.core.physics.scene import *
import gibson2
from gibson2.utils.utils import parse_config, rotate_vector_3d, l2_distance, quatToXYZW
from gibson2.envs.base_env import BaseEnv
from transforms3d.euler import euler2quat
from collections import OrderedDict
from gibson2.envs.locomotor_env import *
import atexit

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import os,sys
import numpy as np

fns = []
data_dir = 'data_pose_new'
for fn in os.listdir(data_dir):
	fns.append(os.path.join(data_dir, fn))

for fn in fns:
	data =  np.load(fn)["arr_0"].item()

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# GL interoperability example, by Peter Berrington.
# Draws a rotating teapot, using cuda to invert the RGB value
# each frame

from OpenGL.GL import *
from OpenGL.GLUT import *
from OpenGL.GLU import *
from OpenGL.GL.ARB.vertex_buffer_object import *
from OpenGL.GL.ARB.pixel_buffer_object import *

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Code

https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4

Setup

I'm using Ubuntu 16.04 with a GTX 1060

install CUDA

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#!/usr/bin/python
import argparse
import os
import rospy
from std_msgs.msg import Float32, Int64
from geometry_msgs.msg import Twist
from sensor_msgs.msg import Image, CameraInfo
from nav_msgs.msg import Odometry
import rospkg
import numpy as np

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import os
import numpy as np
import matplotlib.pyplot as plt
import sys
from tqdm import tqdm
import pandas as pd

main_ukbb_file = sys.argv[1]
other_ukbb_files = sys.argv[1:]

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import sys
import numpy as np
from tqdm import tqdm

from scipy.spatial import ConvexHull

filename = sys.argv[1]

vs = []
fs = []