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# pylint: disable-all
import torch.nn as nn
from torch.nn import functional as F
import torch

def time_to_batch(x):
    t, n = x.size()[:2]
    x = x.view(n * t, *x.size()[2:])
    return x, n

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from __future__ import print_function
import numpy as np
import imutils
import cv2

"""
Homecooked RANSAC, we will see if we manage to replace cv2.findHomography(..., cv2.RANSAC)
"""
def ransac(data, model, n, k, t, d):
    bestfit = None

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import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import matplotlib.pyplot as plt
import numpy as np
import random


def bce_loss_with_logits(x, y):

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from __future__ import print_function
import time
import numpy as np
import cv2
from prophesee_utils.td_video import ChronoVideo

if __name__ == '__main__':
    delay = 1
    base_delay = 1
    stop = False

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#!/usr/bin/python
from __future__ import print_function

"""
 * World To Camera & Back  (projective equations of pinhole cameras)    *
 * --------------------                                                 *
 * The OpenCV reference frame:                                          *
 * (or sometimes called "Camera Reference Frame"):                      *
 * Z points towards the direction of forward motion of the camera       *
 * X points right wrt Y                                                 *

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# Differentiable plasticity: binary pattern memorization and reconstruction
#
# Copyright (c) 2018 Uber Technologies, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#

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import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable
from ranger import Ranger

import numpy as np
import random
import cv2

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"""
Local Convolutions in pytorch
"""
import torch
import torch.nn.functional as F


b,c,h,w = 2,3,32,32
d = 3
n = h*w

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"""
binary dilation in numba cuda
>> python cuda_binary_dilate_3d.py 512 512 512 1
>>> runtime: 0.001s on a Nvidia TitanXP. 
"""
import numba
import numpy as np
import time
from numba import cuda 

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import matplotlib.pyplot as plt
plt.switch_backend('tkagg')

import torch as th
import torch.nn.functional as F
import numpy as np
import cv2
from scipy.spatial.transform import Rotation