thomasweng15

# best run in an interpreter or with a breakpoint
import pickle

fn = ''

with open(fn, 'rb') as f:
  a = pickle.load(f)
  
# make edits
# breakpoint()

thomasweng15

# Save html to the specified path
fig.write_html("plotly_sphere_pts.html")

# Save to wandb (call wandb.init() first)
# html = plotly.io.to_html(fig)
# wandb.log(
#     {
#         f"plotly_sphere_pts": wandb.Html(html),
#     }
# )

thomasweng15

import os
import trimesh
import plotly.graph_objects as go
import plotly.figure_factory as ff
import numpy as np
from voxelized_pointcloud_sampling import create_grid_points_from_bounds
import pickle

"""Load all meshes and inputs into the same plot to make sure everything is aligned. """

thomasweng15

import multiprocessing as mp


def process(arguments, res_q):
    (i,) = arguments
    res_q.put([i])


max_processes = 2
queue = mp.Queue()

thomasweng15

{
      // https://dev.to/adamlombard/how-to-use-the-black-python-code-formatter-in-vscode-3lo0
    "python.formatting.provider": "black",
    "python.formatting.blackPath": "/home/exx/miniconda3/envs/gifs_cloth/bin/black",
    "editor.formatOnSave": true,
}

thomasweng15

// https://stackoverflow.com/questions/17241663/filling-a-queue-and-managing-multiprocessing-in-python
import time
import os
import multiprocessing as mp
from multiprocessing import Queue, Pool

the_queue = Queue()

def worker_main(queue):
    print(f"{os.getpid()} working")

thomasweng15

// Softgym Fabric Touch
{
    "name": "Debug: Sawyer Cloth Env",
    "type": "python",
    "request": "launch",
    "console": "integratedTerminal",
    "cwd": "/home/exx/projects/IDM/softgym_implicit_cloth_proj",
    "python": "/home/exx/miniconda3/envs/softgym-ft/bin/python",
    "program": "/home/exx/projects/IDM/softgym_implicit_cloth_proj/examples/demonstrator.py",
    "env": {

thomasweng15

import os
import sys
import pytorch_lightning as pl
import pytorch_lightning.utilities.seed as seed_utils
from pytorch_lightning import loggers as pl_loggers
from pytorch_lightning.callbacks import ModelCheckpoint

import hydra
import yaml

thomasweng15

import cv2
import rospy
import argparse
import numpy as np
import matplotlib.pyplot as plt
from cv_bridge import CvBridge
from sensor_msgs.msg import Image

class Segmenter():
    def __init__(self, args):

thomasweng15

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import TimedAnimation

class SubplotAnimation(TimedAnimation):
    def __init__(self, num_steps=50):
        fig = plt.figure()
        self.ax1 = fig.add_subplot(2, 1, 1) 
        self.ax2 = fig.add_subplot(2, 1, 2, projection='3d')
        self.ax2.set(xlim3d=(-1, 1), xlabel='X')