# Path: blockplayer/dataset.py
# def advance(skip=1):
# def setup_opencl():
# def load_dataset(pathname):
# def load_gt():
# def load_random_dataset():
# def download():
# 
# Path: blockplayer/grid.py
# def initialize():
# def gt2grid(gtstr, chars='*rR'):
# def grid2gt(occ):
# def initialize_with_groundtruth(GT):
# def window_correction(occA, vacA, occB, vacB):
#     def error(t):
# def xcorr_correction(A, B):
#     def convolve(p1, p2):
#     def best(cc):
# def show_votegrid(vg, color=(1,0,0), opacity=1):
# def has_previous_estimate():
# def apply_correction(grid, bx,bz,rot):
# def center(R_aligned, occ_new, vac_new):
# def nearest(R_previous, R_aligned):
# def align_with_previous(R_aligned, occ_new, vac_new):
# def stencil_carve(depth, rect, R_correct, occ, vac, rgb=None):
# def merge_with_previous(occ_, vac_, occ_stencil, vac_stencil, color_=None):
# def update_previous_estimate(R_correct):
#     B = apply_correction(B, x, z, r)
#     B = apply_correction(B, bx, bz, br)
#     X,Y,Z = np.array(gridmax)-gridmin
#     M = [expmap.axis2rot(np.array([0,-i*np.pi/2,0])) for i in range(4)]
# 
# Path: blockplayer/main.py
# def initialize():
# def update_frame(depth, rgb=None):
#     def from_rect(m,rect):
#     def matrix_slerp(matA, matB, alpha=0.6):


import os
import shutil
import numpy as np
import time
import json
import glob
import cPickle as pickle
import glxcontext
        import re
from blockplayer import dataset
from blockplayer import grid
from blockplayer import main
from OpenGL.GL import glGetString, GL_VERSION



out_path = os.path.join('data/experiments','output')


# Create an offscreen opengl context
glxcontext.makecurrent()
print("GL Version String: ", glGetString(GL_VERSION))


def once():
    depth = dataset.depth
    rgb = dataset.rgb
    main.update_frame(depth, rgb)


def run_grid():
    datasets = glob.glob('data/sets/study_*')
    try:
        os.mkdir(out_path)
    except OSError:
        print "Couldn't make create output directory [%s], it may already exist." % out_path
        print "Remove it and try again."
        return False

    for name in datasets:

# Path: blockplayer/dataset.py
# def advance(skip=1):
# def setup_opencl():
# def load_dataset(pathname):
# def load_gt():
# def load_random_dataset():
# def download():
# 
# Path: blockplayer/grid.py
# def initialize():
# def gt2grid(gtstr, chars='*rR'):
# def grid2gt(occ):
# def initialize_with_groundtruth(GT):
# def window_correction(occA, vacA, occB, vacB):
#     def error(t):
# def xcorr_correction(A, B):
#     def convolve(p1, p2):
#     def best(cc):
# def show_votegrid(vg, color=(1,0,0), opacity=1):
# def has_previous_estimate():
# def apply_correction(grid, bx,bz,rot):
# def center(R_aligned, occ_new, vac_new):
# def nearest(R_previous, R_aligned):
# def align_with_previous(R_aligned, occ_new, vac_new):
# def stencil_carve(depth, rect, R_correct, occ, vac, rgb=None):
# def merge_with_previous(occ_, vac_, occ_stencil, vac_stencil, color_=None):
# def update_previous_estimate(R_correct):
#     B = apply_correction(B, x, z, r)
#     B = apply_correction(B, bx, bz, br)
#     X,Y,Z = np.array(gridmax)-gridmin
#     M = [expmap.axis2rot(np.array([0,-i*np.pi/2,0])) for i in range(4)]
# 
# Path: blockplayer/main.py
# def initialize():
# def update_frame(depth, rgb=None):
#     def from_rect(m,rect):
#     def matrix_slerp(matA, matB, alpha=0.6):


# Path: experiments/make_output.py
import os
import shutil
import numpy as np
import time
import json
import glob
import cPickle as pickle
import glxcontext
        import re
from blockplayer import dataset
from blockplayer import grid
from blockplayer import main
from OpenGL.GL import glGetString, GL_VERSION




out_path = os.path.join('data/experiments','output')


# Create an offscreen opengl context
glxcontext.makecurrent()
print("GL Version String: ", glGetString(GL_VERSION))


def once():
    depth = dataset.depth
    rgb = dataset.rgb
    main.update_frame(depth, rgb)


def run_grid():
    datasets = glob.glob('data/sets/study_*')
    try:
        os.mkdir(out_path)
    except OSError:
        print "Couldn't make create output directory [%s], it may already exist." % out_path
        print "Remove it and try again."
        return False

    for name in datasets:

        dataset.load_dataset(name)