5D_Heredero_Louis_TM2022/python/qr_scanner.py

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2022-09-22 11:13:15 +00:00
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This module can be used to scan QR-Codes
(C) 2022 Louis Heredero louis.heredero@edu.vs.ch
"""
import cv2
import numpy as np
from math import sqrt, degrees, atan2, radians, cos, sin
import imutils
DB_WIN = False
TOL_CNT_DIST = 10 # Tolerance distance between finders' centers
MASKS = [
lambda x,y: (x+y)%2 == 0,
lambda x,y: y%2 == 0,
lambda x,y: (x)%3 == 0,
lambda x,y: (x+y)%3 == 0,
lambda x,y: (y//2+x//3)%2 == 0,
lambda x,y: ((x*y)%2 + (x*y)%3) == 0,
lambda x,y: ((x*y)%2 + (x*y)%3)%2 == 0,
lambda x,y: ((x+y)%2 + (x*y)%3)%2 == 0
]
ALIGNMENT_PATTERN_LOCATIONS = [
[],
[6, 18],
[6, 22],
[6, 26],
[6, 30],
[6, 34],
[6, 22, 38],
[6, 24, 42],
[6, 26, 46],
[6, 28, 50],
[6, 30, 54],
[6, 32, 58],
[6, 34, 62],
[6, 26, 46, 66],
[6, 26, 48, 70],
[6, 26, 50, 74],
[6, 30, 54, 78],
[6, 30, 56, 82],
[6, 30, 58, 86],
[6, 34, 62, 90],
[6, 28, 50, 72, 94],
[6, 26, 50, 74, 98],
[6, 30, 54, 78, 102],
[6, 28, 54, 80, 106],
[6, 32, 58, 84, 110],
[6, 30, 58, 86, 114],
[6, 34, 62, 90, 118],
[6, 26, 50, 74, 98, 122],
[6, 30, 54, 78, 102, 126],
[6, 26, 52, 78, 104, 130],
[6, 30, 56, 82, 108, 134],
[6, 34, 60, 86, 112, 138],
[6, 30, 58, 86, 114, 142],
[6, 34, 62, 90, 118, 146],
[6, 30, 54, 78, 102, 126, 150],
[6, 24, 50, 76, 102, 128, 154],
[6, 28, 54, 80, 106, 132, 158],
[6, 32, 58, 84, 110, 136, 162],
[6, 26, 54, 82, 110, 138, 166],
[6, 30, 58, 86, 114, 142, 170]
]
VERSIONS = []
with open("qr_versions.txt", "r") as f:
versions = f.read().split("\n\n")
for v in versions:
lvls = [list(map(int, lvl.split("\t"))) for lvl in v.split("\n")]
VERSIONS.append(lvls)
VERSIONS = np.array(VERSIONS)
ERROR_CORRECTION = []
with open("error_correction.txt", "r") as f:
ecs = f.read().split("\n\n")
for ec in ecs:
lvls = [list(map(int, lvl.split("\t"))) for lvl in ec.split("\n")]
lvls = [lvl + [0]*(6-len(lvl)) for lvl in lvls]
ERROR_CORRECTION.append(lvls)
ERROR_CORRECTION = np.array(ERROR_CORRECTION)
EC_PARAMS = []
with open("ec_params.txt", "r") as f:
ecs = f.read().split("\n\n")
for ec in ecs:
lvls = [list(map(int, lvl.split("\t"))) for lvl in ec.split("\n") if lvl]
EC_PARAMS.append(lvls)
EC_PARAMS = np.array(EC_PARAMS)
ALPHANUM = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ $%*+-./:"
class GF:
def __init__(self, val):
self.val = val
def copy(self):
return GF(self.val)
def __add__(self, n):
return GF(self.val ^ n.val)
def __sub__(self, n):
return GF(self.val ^ n.val)
def __mul__(self, n):
if self.val == 0 or n.val == 0:
return GF(0)
return GF.EXP[GF.LOG[self.val].val + GF.LOG[n.val].val].copy()
def __truediv__(self, n):
if n.val == 0:
raise ZeroDivisionError
if self.val == 0:
return GF(0)
return GF.EXP[(GF.LOG[self.val].val + 255 - GF.LOG[n.val].val)%255].copy()
def __pow__(self, n):
return GF.EXP[(GF.LOG[self.val].val * n.val)%255].copy()
def __repr__(self):
return self.val.__repr__()
def log(self):
return GF.LOG[self.val]
GF.EXP = [GF(0)]*512
GF.LOG = [GF(0)]*256
value = 1
for exponent in range(255):
GF.LOG[value] = GF(exponent)
GF.EXP[exponent] = GF(value)
value = ((value << 1) ^ 285) if value > 127 else value << 1
for i in range(255, 512):
GF.EXP[i] = GF.EXP[i-255].copy()
class Poly:
def __init__(self, coefs):
self.coefs = coefs.copy()
@property
def deg(self):
return len(self.coefs)
def copy(self):
return Poly(self.coefs)
def __add__(self, p):
d1, d2 = self.deg, p.deg
deg = max(d1,d2)
result = [GF(0) for i in range(deg)]
for i in range(d1):
result[i + deg - d1] = self.coefs[i]
for i in range(d2):
result[i + deg - d2] += p.coefs[i]
return Poly(result)
def __mul__(self, p):
result = [GF(0) for i in range(self.deg+p.deg-1)]
for i in range(p.deg):
for j in range(self.deg):
result[i+j] += self.coefs[j] * p.coefs[i]
return Poly(result)
def __truediv__(self, p):
dividend = self.coefs.copy()
dividend += [GF(0) for i in range(p.deg-1)]
quotient = []
for i in range(self.deg):
coef = dividend[i] / p.coefs[0]
quotient.append(coef)
for j in range(p.deg):
dividend[i+j] -= p.coefs[j] * coef
while dividend[0].val == 0:
dividend.pop(0)
return [Poly(quotient), Poly(dividend)]
def __repr__(self):
return f"<Poly {self.coefs}>"
def eval(self, x):
y = GF(0)
for i in range(self.deg):
y += self.coefs[i] * x**GF(self.deg-i-1)
return y
def del_lead_zeros(self):
while len(self.coefs) > 1 and self.coefs[0].val == 0:
self.coefs.pop(0)
if len(self.coefs) == 0:
self.coefs = [GF(0)]
return self
def center(c):
M = cv2.moments(c)
if M["m00"] != 0:
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
return (cX, cY)
return (None, None)
def dist(p1, p2):
return sqrt((p2[0]-p1[0])**2 + (p2[1]-p1[1])**2)
def rotate(o, p, a):
ox, oy = o
px, py = p
a = radians(a)
c, s = cos(a), sin(a)
return [
int(ox + c*(px-ox) - s * (py-oy)),
int(oy + s*(px-ox) + c * (py-oy))
]
def rotate_cnt(cnt, o, a):
c = cnt
pts = c[:, 0, :]
pts = np.array([rotate(o, p, a) for p in pts])
c[:, 0, :] = pts
return c.astype(np.int32)
def is_finder(i, cnts, hrcy):
c1 = cnts[i]
h1 = hrcy[0][i]
cX1, cY1 = center(c1)
if len(c1) != 4:
return False
if cX1 is None:
return False
if h1[2] == -1:
return False
i2 = h1[2]
c2 = cnts[i2]
h2 = hrcy[0][i2]
cX2, cY2 = center(c2)
if cX2 is None:
return False
if len(c2) != 4:
return False
if abs(dist((cX1, cY1), (cX2, cY2))) > TOL_CNT_DIST:
return False
if h2[2] == -1:
return False
i3 = h2[2]
c3 = cnts[i3]
h3 = hrcy[0][i3]
cX3, cY3 = center(c3)
if len(c3) != 4:
return False
if cX3 is None:
return False
if abs(dist((cX1, cY1), (cX3, cY3))) > TOL_CNT_DIST:
return False
return True
def decode(img):
grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
grey = cv2.GaussianBlur(grey, (5,5), 0)
#if DB_WIN: cv2.imshow("grey", grey)
bw = cv2.threshold(grey, np.mean(grey), 255, cv2.THRESH_BINARY)[1]
if DB_WIN: cv2.imshow("bw", bw)
#laplacian = cv2.Laplacian(bw, cv2.CV_8U, 15)
#cv2.imshow("laplacian", laplacian)
contours, hierarchy = cv2.findContours(bw, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
if DB_WIN:
img2 = img.copy()
cv2.drawContours(img2, contours, -1, (0,255,0), 1)
candidates = []
contours = list(contours)
for i, cnt in enumerate(contours):
peri = cv2.arcLength(cnt, True)
contours[i] = cv2.approxPolyDP(cnt, 0.04 * peri, True)
for i in range(len(contours)):
if is_finder(i, contours, hierarchy):
candidates.append(i)
if DB_WIN:
for i in candidates:
cv2.drawContours(img2, contours, i, (0,0,255), 1)
cv2.imshow("contours", img2)
if DB_WIN: img3 = img.copy()
corners = []
corners_cnts = []
for i1 in candidates:
i2 = hierarchy[0][i1][2]
i3 = hierarchy[0][i2][2]
c1 = contours[i1]
c2 = contours[i2]
c3 = contours[i3]
x1, y1 = center(c1)
x2, y2 = center(c2)
x3, y3 = center(c3)
x, y = (x1+x2+x3)/3, (y1+y2+y3)/3
x, y = int(x), int(y)
corners.append((x,y))
corners_cnts.append([c1,c2,c3])
if DB_WIN:
cv2.line(img3, [x, y-10], [x, y+10], (0,255,0), 1)
cv2.line(img3, [x-10, y], [x+10, y], (0,255,0), 1)
#cv2.drawContours(img3, [c1], 0, (255,0,0), 1)
#cv2.drawContours(img3, [c2], 0, (0,255,0), 1)
#cv2.drawContours(img3, [c3], 0, (0,0,255), 1)
if DB_WIN: cv2.imshow("lines", img3)
if len(corners) != 3:
return
d01 = dist(corners[0], corners[1])
d02 = dist(corners[0], corners[2])
d12 = dist(corners[1], corners[2])
diffs = [abs(d01-d02), abs(d01-d12), abs(d02-d12)]
mdiff = min(diffs)
i = diffs.index(mdiff)
a = corners.pop(i)
b, c = corners
V = [img.shape[1], img.shape[0]]
d = [(b[0]+c[0])/2, (b[1]+c[1])/2]
v = [d[0]-a[0], d[1]-a[1]]
C = [img.shape[1]/2, img.shape[0]/2]
angle = degrees(atan2(v[1], v[0]))
angle_diff = angle-45
if DB_WIN:
img4 = img.copy()
cv2.line(img4, a, [int(d[0]), int(d[1])], (0,255,0), 1)
cv2.imshow("vecs", img4)
cA = corners_cnts[i][0]
cA = rotate_cnt(cA, C, -angle_diff)
rA = cv2.boundingRect(cA)
cA2 = corners_cnts[i][1]
cA2 = rotate_cnt(cA2, C, -angle_diff)
rA2 = cv2.boundingRect(cA2)
cB = corners_cnts[i-1][0]
cB = rotate_cnt(cB, C, -angle_diff)
rB = cv2.boundingRect(cB)
cC = corners_cnts[i-2][0]
cC = rotate_cnt(cC, C, -angle_diff)
rC = cv2.boundingRect(cC)
a, b, c = rotate(C, a, -angle_diff), rotate(C, b, -angle_diff), rotate(C, c, -angle_diff)
if DB_WIN:
img5 = img.copy()
img5 = imutils.rotate(img5, angle_diff)
cv2.rectangle(img5, rA, (255,0,0), 1)
cv2.rectangle(img5, rB, (0,255,0), 1)
cv2.rectangle(img5, rC, (0,0,255), 1)
cv2.line(img5, a, b, (255,255,255), 1)
cv2.line(img5, a, c, (255,255,255), 1)
cv2.imshow("rot", img5)
wul = rA[2]
if rB[1] < rC[1]:
wur = rB[2]
else:
wur = rC[2]
if rB[1] < rC[1]:
D = dist(a, b)
else:
D = dist(a, c)
X = (wul + wur)/14
V = (D/X - 10)/4
V = round(V)
size = V*4+17
grid = np.zeros([size, size])
bw_rot = imutils.rotate(bw, angle_diff)
if DB_WIN:
img6 = img.copy()
img6 = imutils.rotate(img6, angle_diff)
OX, OY = (rA[0]+rA2[0])/2, (rA[1]+rA2[1])/2
#Not fully visible
if (OX + size*X+1 >= bw_rot.shape[1]) or (OY + size*X+1 >= bw_rot.shape[0]):
return None
for y in range(size):
for x in range(size):
zone = bw_rot[
int(OY + y*X-1): int(OY + y*X+2),
int(OX + x*X-1): int(OX + x*X+2)
]
grid[y, x] = 1-round(np.mean(zone)/255)
#cv2.circle(img6, [int(OX+x*X), int(OY+y*X)], 3, (0,0,255), 1)
#print(size)
#cv2.rectangle(img6, [int(OX-X/2), int(OY-X/2), int(X), int(X)], (0,255,0), 1)
#cv2.imshow("grid", img6)
if DB_WIN:
cv2.namedWindow("bw_rot", cv2.WINDOW_NORMAL)
cv2.imshow("bw_rot", bw_rot)
#cv2.imshow("code", cv2.resize(grid, [size*10,size*10]))
value = _decode(grid, V)
if value is None:
value = _decode(1-grid, V)
return value
def _decode(grid, V, flipped=None, f2=False):
if not flipped is None:
grid = flipped
lvl, mask_i = get_fmt(grid, f2)
mask = MASKS[mask_i]
unmasked = grid.copy()
mask_area = np.ones(grid.shape)
mask_area[:9, :9] = 0
mask_area[:9, -8:] = 0
mask_area[-8:, :9] = 0
#Add alignment patterns
locations = ALIGNMENT_PATTERN_LOCATIONS[V-1]
if V > 1:
for y in locations:
for x in locations:
#Check if not overlapping with finders
if np.all(mask_area[y-2:y+3, x-2:x+3] == 1):
mask_area[y-2:y+3, x-2:x+3] = 0
mask_area[y-1:y+2, x-1:x+2] = 0
mask_area[y, x] = 0
#Add timing patterns
timing_length = grid.shape[0]-2*8
mask_area[6, 8:-8] = np.zeros([timing_length])
mask_area[8:-8, 6] = np.zeros([timing_length])
if V >= 7:
mask_area[-11:-8, :6] = 0
mask_area[:6, -11:-8] = 0
for y in range(grid.shape[0]):
for x in range(grid.shape[1]):
if mask_area[y,x] == 1 and mask(x,y):
unmasked[y,x] = 1-unmasked[y,x]
if DB_WIN:
cv2.namedWindow("grid", cv2.WINDOW_NORMAL)
cv2.namedWindow("unmasked", cv2.WINDOW_NORMAL)
#cv2.namedWindow("mask_area", cv2.WINDOW_NORMAL)
cv2.imshow("grid", 1-grid)
cv2.imshow("unmasked", 1-unmasked)
#cv2.imshow("mask_area", mask_area)
#Un-place data
dir_ = -1 #-1 = up | 1 = down
x, y = grid.shape[1]-1, grid.shape[0]-1
i = 0
zigzag = 0
final_data_bits = ""
while x >= 0:
if mask_area[y,x] == 1:
final_data_bits += str(int(unmasked[y, x]))
if ((dir_+1)/2 + zigzag)%2 == 0:
x -= 1
else:
y += dir_
x += 1
if y == -1 or y == grid.shape[0]:
dir_ = -dir_
y += dir_
x -= 2
else:
zigzag = 1-zigzag
#Vertical timing pattern
if x == 6:
x -= 1
#Remove remainder bits
if 2 <= V < 7:
final_data_bits = final_data_bits[:-7]
elif 14 <= V < 21 or 28 <= V < 35:
final_data_bits = final_data_bits[:-3]
elif 21 <= V < 28:
final_data_bits = final_data_bits[:-4]
ec = ERROR_CORRECTION[V-1, lvl]
#print(ec)
codewords = [final_data_bits[i:i+8] for i in range(0,len(final_data_bits),8)]
#Only one block
if ec[2]+ec[4] == 1:
data_codewords = codewords[:ec[3]]
ec_codewords = codewords[ec[3]:]
else:
group1, group2 = [], []
group_ec = []
for b in range(ec[2]):
block = []
for i in range(ec[3]):
block.append(codewords[b+i*(ec[2]+ec[4])])
group1.append(block)
if ec[4] > 0:
for b in range(ec[2], ec[2]+ec[4]):
block = []
for i in range(ec[5]):
off = 0
if i >= ec[3]:
off = (i-ec[3]+1)*ec[2]
block.append(codewords[b+i*(ec[2]+ec[4])-off])
group2.append(block)
codewords = codewords[ec[2]*ec[3]+ec[4]*ec[5]:]
for b in range(ec[2]+ec[4]):
block = []
for i in range(ec[1]):
block.append(codewords[b+i*(ec[2]+ec[4])])
group_ec.append(block)
data_codewords = sum(group1, []) + sum(group2, [])
ec_codewords = sum(group_ec, [])
#print(data_codewords)
#print(ec_codewords)
try:
decoded = correct(data_codewords, ec_codewords)
except ReedSolomonException as e:
#print(e)
if not f2:
return _decode(grid, V, flipped, True)
elif flipped is None:
f = grid.copy()
f = np.rot90(np.fliplr(f))
return _decode(grid, V, f, False)
else:
#raise ReedSolomonException("Cannot decode")
return None
decoded = "".join(list(map(lambda c: f"{c.val:08b}", decoded.coefs)))
mode, decoded = decoded[:4], decoded[4:]
MODES = ["0001", "0010", "0100", "1000"]
mode = MODES.index(mode)
if 1 <= V < 10:
char_count_len = [10,9,8,8][mode]
elif 10 <= V < 27:
char_count_len = [12,11,16,10][mode]
elif 27 <= V < 41:
char_count_len = [14,13,16,12][mode]
length, decoded = decoded[:char_count_len], decoded[char_count_len:]
length = int(length, 2)
value = None
if mode == 0:
value = ""
_ = length//3
l = _ * 10
if 10 - _ == 2:
l += 7
else:
l += 4
data = decoded[:l]
groups = [data[i:i+10] for i in range(0, l, 10)]
for group in groups:
value += str(int(group,2))
value = int(value)
elif mode == 1:
value = ""
data = decoded[:length//2 * 11 + (length%2)*6]
for i in range(0, len(data), 11):
s = data[i:i+11]
val = int(s, 2)
if len(s) == 6:
value += ALPHANUM[val]
else:
value += ALPHANUM[val//45]
value += ALPHANUM[val%45]
elif mode == 2:
data = decoded[:length*8]
data = [data[i:i+8] for i in range(0, length*8, 8)]
data = list(map(lambda b: int(b, 2), data))
value = bytes(data).decode("ISO-8859-1")
elif mode == 3:
value = []
data = decoded[:length*13]
for i in range(0, len(data), 13):
val = int(data[i:i+13], 2)
msb = val // 0xc0
lsb = val % 0xc0
dbyte = (msb << 8) + lsb
if 0 <= dbyte <= 0x9ffc - 0x8140:
dbyte += 0x8140
elif 0xe040 - 0xc140 <= dbyte <= 0xebbf - 0xc140:
dbyte += 0xc140
value.append(dbyte >> 8)
value.append(dbyte & 0xff)
value = bytes(value).decode("shift_jis")
#print("value:", value)
return value
# If unreadable
# -> _decode(f2=True)
# -> mirror image
class ReedSolomonException(Exception):
pass
def correct(data, ec):
n = len(ec)
data = Poly([GF(int(cw, 2)) for cw in data+ec])
##print("data", list(map(lambda c:c.val, data.coefs)))
syndrome = [0]*n
corrupted = False
for i in range(n):
syndrome[i] = data.eval(GF.EXP[i])
if syndrome[i].val != 0:
corrupted = True
if not corrupted:
print("No errors")
return data
syndrome = Poly(syndrome[::-1])
#print("syndrome", syndrome)
#Find locator poly
sigma, omega = euclidean_algorithm(Poly([GF(1)]+[GF(0) for i in range(n)]), syndrome, n)
#print("sigma", sigma)
#print("omega", omega)
error_loc = find_error_loc(sigma)
error_mag = find_error_mag(omega, error_loc)
for i in range(len(error_loc)):
pos = GF(error_loc[i]).log()
pos = data.deg - pos.val - 1
if pos < 0:
raise ReedSolomonException("Bad error location")
data.coefs[pos] += GF(error_mag[i])
return data
def euclidean_algorithm(a, b, R):
if a.deg < b.deg:
a, b = b, a
r_last = a
r = b
t_last = Poly([GF(0)])
t = Poly([GF(1)])
while r.deg-1 >= int(R/2):
r_last_last = r_last
t_last_last = t_last
r_last = r
t_last = t
if r_last.coefs[0] == 0:
raise ReedSolomonException("r_{i-1} was zero")
r = r_last_last
q = Poly([GF(0)])
denom_lead_term = r_last.coefs[0]
dlt_inv = denom_lead_term ** GF(-1)
I = 0
while r.deg >= r_last.deg and r.coefs[0] != 0:
I += 1
deg_diff = r.deg - r_last.deg
scale = r.coefs[0] * dlt_inv
q += Poly([scale]+[GF(0) for i in range(deg_diff)])
r += r_last * Poly([scale]+[GF(0) for i in range(deg_diff)])
q.del_lead_zeros()
r.del_lead_zeros()
if I > 100:
raise ReedSolomonException("Too long")
t = (q * t_last).del_lead_zeros() + t_last_last
t.del_lead_zeros()
if r.deg >= r_last.deg:
raise ReedSolomonException("Division algorithm failed to reduce polynomial")
sigma_tilde_at_zero = t.coefs[-1]
if sigma_tilde_at_zero.val == 0:
raise ReedSolomonException("sigma_tilde(0) was zero")
inv = Poly([sigma_tilde_at_zero ** GF(-1)])
sigma = t * inv
omega = r * inv
return [sigma, omega]
def find_error_loc(error_loc):
num_errors = error_loc.deg-1
if num_errors == 1:
return [error_loc.coefs[-2].val]
result = [0]*num_errors
e = 0
i = 1
while i < 256 and e < num_errors:
if error_loc.eval(GF(i)).val == 0:
result[e] = (GF(i) ** GF(-1)).val
e += 1
i += 1
if e != num_errors:
raise ReedSolomonException("Error locator degree does not match number of roots")
return result
def find_error_mag(error_eval, error_loc):
s = len(error_loc)
result = [0]*s
for i in range(s):
xi_inv = GF(error_loc[i]) ** GF(-1)
denom = GF(1)
for j in range(s):
if i != j:
denom *= GF(1) + GF(error_loc[j]) * xi_inv
result[i] = ( error_eval.eval(xi_inv) * (denom ** GF(-1)) ).val
return result
def get_fmt(grid ,f2=False):
fmt1 = list(grid[0:6, 8]) + [grid[7,8], grid[8,8], grid[8,7]] + list(grid[8, 0:6][::-1])
fmt2 = list(grid[8, -8:][::-1]) + list(grid[-7:, 8])
fmt1 = "".join([str(int(b)) for b in fmt1])[::-1]
fmt2 = "".join([str(int(b)) for b in fmt2])[::-1]
if f2:
return decode_fmt(fmt2)
return decode_fmt(fmt1)
def decode_fmt(fmt):
format_data = int(fmt, 2)
format_data ^= 0b101010000010010
format_data = f"{format_data:015b}"
closest = None
with open("./valid_format_str.txt", "r") as f:
for i, format_str in enumerate(f):
diff = sum(1 for a, b in zip(format_data, format_str) if a != b)
if closest is None or diff < closest[1]:
closest = (i, diff)
lvl = closest[0] >> 3
lvl = (5-lvl)%4
mask = closest[0]&0b111
return [lvl, mask]
if __name__ == "__main__":
cam = cv2.VideoCapture(0)
while True:
ret_val, img = cam.read()
if not ret_val:
continue
cv2.imshow("src", img)
try:
value = decode(img)
if not value is None:
print(value)
except Exception as e:
#pass
#raise
print(e)
cv2.waitKey(1)
cv2.destroyAllWindows()