justinhchae

# install direct from our forked repository: https://github.com/Esri/pytorch3d/tree/multitexture-obj-high-precision
!pip install 'git+https://github.com/Esri/pytorch3d.git@multitexture-obj-high-precision'

from pytorch3d.io import save_obj

# save_obj now allows for saving objs with multiple textures and control over the texture outputs
save_obj(
    f=obj_filename,
    verts=obj[0],
    faces=obj[1].verts_idx,

justinhchae

# install direct from our forked repository: https://github.com/Esri/pytorch3d/tree/multitexture-obj-high-precision
!pip install 'git+https://github.com/Esri/pytorch3d.git@multitexture-obj-high-precision'

from pytorch3d.io import subset_obj

faces_to_subset = <a torch tensor of face indices to subset>

# all obj objects are subset to the selected face indices
obj_subset = subset_obj(
    obj=obj,

justinhchae

# install direct from our forked repository: https://github.com/Esri/pytorch3d/tree/multitexture-obj-high-precision
!pip install 'git+https://github.com/Esri/pytorch3d.git@multitexture-obj-high-precision'

from pytorch3d.ops import sample_points_from_obj

(
    points, # points sampled proportional to face area
    normals, # point normals based on mesh verts
    textures, # point textures sampled from faces
    mappers # an index to each points origin face

justinhchae

# install direct from our forked repository: https://github.com/Esri/pytorch3d/tree/multitexture-obj-high-precision
!pip install 'git+https://github.com/Esri/pytorch3d.git@multitexture-obj-high-precision'

from pytorch3d.io import load_obj

# the current pytorch3d API for load_obj
obj = load_obj(
    path_to_obj_file,
    load_textures=True,
)

justinhchae

# install direct from our forked repository: https://github.com/Esri/pytorch3d/tree/multitexture-obj-high-precision
!pip install 'git+https://github.com/Esri/pytorch3d.git@multitexture-obj-high-precision'

# import the forked pytorch3d library and new functions
from pytorch3d.io import load_obj
from pytorch3d.ops import sample_points_from_obj
from pytorch3d.io import subset_obj, save_obj

justinhchae

'''https://numpy.org/doc/stable/reference/generated/numpy.savez_compressed.html#numpy.savez_compressed
'''


import numpy as np
import os


# number of points in the point cloud
num_points = 10

justinhchae

class Budget2021(BudgetDB.base):
    __tablename__ = "budget2021"
    # uncomment the following line to print out this class as text
    # df = get_vars_main('budget_main.csv')
    id = Column(Integer, primary_key=True)
    fund_type = Column(String)
    # the code is a value like 4355 that means "Department A" -> F key to the table the name of the dept.
    department_code = Column(Integer, ForeignKey("departmentDescription.department_code"))
    fund_code = Column(String, ForeignKey("fundDescription.fund_code"))
    organization_code = Column(Integer)

justinhchae

def get_vars_main(filename):
    """
    a helper function for creating the code for the main table of an sql alchemy schema
    bases on a csv file, extract necessary column names and tables and print the code to terminal
    copy and paste the code into the schema section
    """
    logging.info('get_vars_main() Producing code to make main data table in alchemy.')

    class_name = f'class {db_table_name.title()}({db_class_name}):'
    full_path = os.sep.join([data_folder, filename])

justinhchae

# given a function from fc.py
# https://gist.github.com/justinhchae/a2efee420330a985286e7b88fd049ce5

# in a file called main.py
import pandas as pd
# using the pytorch version of mp
import torch.multiprocessing as mp
# we need partial
from functools import partial
# progress bar

justinhchae

# solution reference:
# https://stackoverflow.com/questions/41707229/tqdm-printing-to-newline

def fc(x, param):
  # inject some waiting to see progress unfold
  time.sleep(1)
  # set up pbar
  pbar = tqdm(x.items(), desc='Exp:', position=0)
  # init a variable for output
  yhat = 0