RLTracking/fhog_utils.py at master · ShanghaiTechCS/RLTracking · GitHub

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import numpy as np
from numba.pycc import CC
import math

# constant
NUM_SECTOR = 9
FLT_EPSILON = 1e-07

cc = CC('fhog_utils')


@cc.export('func1', '(f4[:,:,:], f4[:,:,:], f4[:], f4[:], f4[:,:], i8[:,:,:], i8,i8,i8)')
def func1(dx, dy, boundary_x, boundary_y, r, alfa, height, width, numChannels):
    for j in xrange(1, height - 1):
        for i in xrange(1, width - 1):
            c = 0
            x = dx[j, i, c]
            y = dy[j, i, c]
            r[j, i] = math.sqrt(x * x + y * y)

            for ch in xrange(1, numChannels):
                tx = dx[j, i, ch]
                ty = dy[j, i, ch]
                magnitude = math.sqrt(tx * tx + ty * ty)
                if (magnitude > r[j, i]):
                    r[j, i] = magnitude
                    c = ch
                    x = tx
                    y = ty

            mmax = boundary_x[0] * x + boundary_y[0] * y
            maxi = 0

            for kk in xrange(0, NUM_SECTOR):
                dotProd = boundary_x[kk] * x + boundary_y[kk] * y
                if (dotProd > mmax):
                    mmax = dotProd
                    maxi = kk
                elif (-dotProd > mmax):
                    mmax = -dotProd
                    maxi = kk + NUM_SECTOR

            alfa[j, i, 0] = maxi % NUM_SECTOR
            alfa[j, i, 1] = maxi


@cc.export('func2', '(f4[:], f4[:], f4[:], f4[:,:], i8[:,:,:], i8[:], f4[:,:], i8,i8,i8,i8,i8,i8,i8)')
def func2(mapp, boundary_x, boundary_y, r, alfa, nearest, w, k, height, width, sizeX, sizeY, p, stringSize):
    for i in xrange(sizeY):
        for j in xrange(sizeX):
            for ii in xrange(k):
                for jj in xrange(k):
                    if ((i * k + ii > 0) and (i * k + ii < height - 1) and (j * k + jj > 0) and (j * k + jj < width - 1)):
                        mapp[i * stringSize + j * p + alfa[k * i + ii, j * k + jj, 0]] += r[k * i + ii, j * k + jj] * w[ii, 0] * w[jj, 0]
                        mapp[i * stringSize + j * p + alfa[k * i + ii, j * k + jj, 1] + NUM_SECTOR] += r[k * i + ii, j * k + jj] * w[ii, 0] * w[jj, 0]
                        if ((i + nearest[ii] >= 0) and (i + nearest[ii] <= sizeY - 1)):
                            mapp[(i + nearest[ii]) * stringSize + j * p + alfa[k * i + ii, j * k + jj, 0]] += r[k * i + ii, j * k + jj] * w[ii, 1] * w[jj, 0]
                            mapp[(i + nearest[ii]) * stringSize + j * p + alfa[k * i + ii, j * k + jj, 1] + NUM_SECTOR] += r[k * i + ii, j * k + jj] * w[
                                ii, 1] * w[jj, 0]
                        if ((j + nearest[jj] >= 0) and (j + nearest[jj] <= sizeX - 1)):
                            mapp[i * stringSize + (j + nearest[jj]) * p + alfa[k * i + ii, j * k + jj, 0]] += r[k * i + ii, j * k + jj] * w[ii, 0] * w[jj, 1]
                            mapp[i * stringSize + (j + nearest[jj]) * p + alfa[k * i + ii, j * k + jj, 1] + NUM_SECTOR] += r[k * i + ii, j * k + jj] * w[
                                ii, 0] * w[jj, 1]
                        if ((i + nearest[ii] >= 0) and (i + nearest[ii] <= sizeY - 1) and (j + nearest[jj] >= 0) and (j + nearest[jj] <= sizeX - 1)):
                            mapp[(i + nearest[ii]) * stringSize + (j + nearest[jj]) * p + alfa[k * i + ii, j * k + jj, 0]] += \
                                r[k * i + ii, j * k + jj] * w[ii, 1] * w[jj, 1]
                            mapp[(i + nearest[ii]) * stringSize + (j + nearest[jj]) * p + alfa[k * i + ii, j * k + jj, 1] + NUM_SECTOR] += \
                                r[k * i + ii, j * k + jj] * w[ii, 1] * w[jj, 1]


@cc.export('func3', '(f4[:], f4[:], f4[:], i8,i8,i8,i8,i8)')
def func3(newData, partOfNorm, mappmap, sizeX, sizeY, p, xp, pp):
    for i in xrange(1, sizeY + 1):
        for j in xrange(1, sizeX + 1):
            pos1 = i * (sizeX + 2) * xp + j * xp
            pos2 = (i - 1) * sizeX * pp + (j - 1) * pp

            valOfNorm = math.sqrt(partOfNorm[(i) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i) * (sizeX + 2) + (j + 1)] +
                                  partOfNorm[(i + 1) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i + 1) * (sizeX + 2) + (j + 1)]) + FLT_EPSILON
            newData[pos2:pos2 + p] = mappmap[pos1:pos1 + p] / valOfNorm
            newData[pos2 + 4 * p:pos2 + 6 * p] = mappmap[pos1 + p:pos1 + 3 * p] / valOfNorm

            valOfNorm = math.sqrt(partOfNorm[(i) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i) * (sizeX + 2) + (j + 1)] +
                                  partOfNorm[(i - 1) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i - 1) * (sizeX + 2) + (j + 1)]) + FLT_EPSILON
            newData[pos2 + p:pos2 + 2 * p] = mappmap[pos1:pos1 + p] / valOfNorm
            newData[pos2 + 6 * p:pos2 + 8 * p] = mappmap[pos1 + p:pos1 + 3 * p] / valOfNorm

            valOfNorm = math.sqrt(partOfNorm[(i) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i) * (sizeX + 2) + (j - 1)] +
                                  partOfNorm[(i + 1) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i + 1) * (sizeX + 2) + (j - 1)]) + FLT_EPSILON
            newData[pos2 + 2 * p:pos2 + 3 * p] = mappmap[pos1:pos1 + p] / valOfNorm
            newData[pos2 + 8 * p:pos2 + 10 * p] = mappmap[pos1 + p:pos1 + 3 * p] / valOfNorm

            valOfNorm = math.sqrt(partOfNorm[(i) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i) * (sizeX + 2) + (j - 1)] +
                                  partOfNorm[(i - 1) * (sizeX + 2) + (j)] +
                                  partOfNorm[(i - 1) * (sizeX + 2) + (j - 1)]) + FLT_EPSILON
            newData[pos2 + 3 * p:pos2 + 4 * p] = mappmap[pos1:pos1 + p] / valOfNorm
            newData[pos2 + 10 * p:pos2 + 12 * p] = mappmap[pos1 + p:pos1 + 3 * p] / valOfNorm


@cc.export('func4', '(f4[:], f4[:], i8,i8,i8,i8,i8,i8,f8,f8)')
def func4(newData, mappmap, p, sizeX, sizeY, pp, yp, xp, nx, ny):
    for i in xrange(sizeY):
        for j in xrange(sizeX):
            pos1 = (i * sizeX + j) * p
            pos2 = (i * sizeX + j) * pp

            for jj in xrange(2 * xp):  # 2*9
                newData[pos2 + jj] = np.sum(mappmap[pos1 + yp * xp + jj: pos1 + 3 * yp * xp + jj: 2 * xp]) * ny
            for jj in xrange(xp):  # 9
                newData[pos2 + 2 * xp + jj] = np.sum(mappmap[pos1 + jj: pos1 + jj + yp * xp: xp]) * ny
            for ii in xrange(yp):  # 4
                newData[pos2 + 3 * xp + ii] = np.sum(mappmap[pos1 + yp * xp + ii * xp * 2: pos1 + yp * xp + ii * xp * 2 + 2 * xp]) * nx


if __name__ == "__main__":
    cc.compile()