def detectFire(path_res, info):
b_1s = np.load(path_res + r'\Landsat_'+info+'_B1.npy')
b_2s = np.load(path_res + r'\Landsat_'+info+'_B2.npy')
b_3s = np.load(path_res + r'\Landsat_'+info+'_B3.npy')
b_4s = np.load(path_res + r'\Landsat_'+info+'_B4.npy')
shape = b_1s.shape
L1 = Layer(b_1s)
L2 = Layer(b_2s)
L3 = Layer(b_3s)
L4 = Layer(b_4s)
nw2 = L3 >> L2 | L1 >> L2 & L2 >> L3 & L3 >> L4
L3.arr = None
L3 = None
L2.arr = None
L2 = None
gc.collect()
b_5s = np.load(path_res + r'\Landsat_'+info+'_B5.npy')
b_6s = np.load(path_res + r'\Landsat_'+info+'_B6.npy')
b_7s = np.load(path_res + r'\Landsat_'+info+'_B7.npy')
L5 = Layer(b_5s)
L6 = Layer(b_6s)
L7 = Layer(b_7s)
Sub_1_7 = L1 - L7
nw1 = L4 >> L5 & L5 >> L6 & L6 >> L7 & Sub_1_7 << 0.2
L4.arr = None
L4 = None
Sub_1_7.arr = None
Sub_1_7 = None
gc.collect()
z1 = nw1 & nw2
not_water = ~z1 # logical not
# z1.arr = None
# z1 = None
# gc.collect()
result = np.zeros(shape,dtype = np.uint8)
Div_7_6 = L7/L6
Div_7_5 = L7/L5
Sub_7_5 = L7 - L5
# R75 > 1.8 && ρ7−ρ5 > 0.17
test3 = np.zeros(shape,dtype = np.uint8)
np.putmask(test3, ( Div_7_5 >> 1.8 & Sub_7_5 >> 0.17 & Div_7_6 >> 1.6 ).arr , 3)
Div_7_6.arr = None
Div_7_6 = None
gc.collect()
print("pre-test 3 done")
# R75 > 2.5 && ρ7−ρ5 > 0.3 && ρ7 > 0.5
np.putmask(result, (Div_7_5 >> 2.5 & Sub_7_5 >> 0.3 & L7 >> 0.5).arr, 1)
Div_7_5.arr = None
Div_7_5 = None
Sub_7_5.arr = None
Sub_7_5 = None
gc.collect()
print("test 1 done")
# ===================================
# ρ6 > 0.8 && ρ1 < 0.2 && ( ρ5 > 0.4 || p7 < 0.1 )
np.putmask(result, ( L6 >> 0.8 & L1 << 0.2 & ( L5 >> 0.4 | L7 << 0.1 ) ).arr, 2)
L1.arr = None
L1 = None
L6.arr = None
L6 = None
gc.collect()
print("test 2 done")
inf = open(r'D:\Landsat\experiments\105069\class1.txt', 'w')
inf.write( 'Div_7_5' + ', '+ 'Sub_7_5' + ', ' + 'L7' + '\n')
for i in range(shape[0]):
for j in range(shape[1]):
if result[i][j] == 1:
inf.write( Div_7_5[i][j] + ', '+ Sub_7_5[i][j] + ', ' + L7[i][j] + '\n')
inf.close()
def detectFire(path_res, info):
b_1s = np.load(path_res + r'\Landsat_' + info + '_B1.npy')
b_2s = np.load(path_res + r'\Landsat_' + info + '_B2.npy')
b_3s = np.load(path_res + r'\Landsat_' + info + '_B3.npy')
b_4s = np.load(path_res + r'\Landsat_' + info + '_B4.npy')
shape = b_1s.shape
L1 = Layer(b_1s)
L2 = Layer(b_2s)
L3 = Layer(b_3s)
L4 = Layer(b_4s)
nw2 = L3 >> L2 | L1 >> L2 & L2 >> L3 & L3 >> L4
L3.arr = None
L3 = None
L2.arr = None
L2 = None
gc.collect()
b_5s = np.load(path_res + r'\Landsat_' + info + '_B5.npy')
b_6s = np.load(path_res + r'\Landsat_' + info + '_B6.npy')
b_7s = np.load(path_res + r'\Landsat_' + info + '_B7.npy')
L5 = Layer(b_5s)
L6 = Layer(b_6s)
L7 = Layer(b_7s)
Sub_1_7 = L1 - L7
nw1 = L4 >> L5 & L5 >> L6 & L6 >> L7 & Sub_1_7 << 0.2
L4.arr = None
L4 = None
Sub_1_7.arr = None
Sub_1_7 = None
gc.collect()
z1 = nw1 & nw2
not_water = ~z1 # logical not
# z1.arr = None
# z1 = None
# gc.collect()
result = np.zeros(shape, dtype=np.uint8)
Div_7_6 = L7 / L6
Div_7_5 = L7 / L5
Sub_7_5 = L7 - L5
# R75 > 1.8 && ρ7−ρ5 > 0.17
test3 = np.zeros(shape, dtype=np.uint8)
np.putmask(test3, (Div_7_5 >> 1.8 & Sub_7_5 >> 0.17 & Div_7_6 >> 1.6).arr,
3)
Div_7_6.arr = None
Div_7_6 = None
gc.collect()
print("pre-test 3 done")
# R75 > 2.5 && ρ7−ρ5 > 0.3 && ρ7 > 0.5
np.putmask(result, (Div_7_5 >> 2.5 & Sub_7_5 >> 0.3 & L7 >> 0.5).arr, 1)
Div_7_5.arr = None
Div_7_5 = None
Sub_7_5.arr = None
Sub_7_5 = None
gc.collect()
print("test 1 done")
# ===================================
# ρ6 > 0.8 && ρ1 < 0.2 && ( ρ5 > 0.4 || p7 < 0.1 )
np.putmask(result, (L6 >> 0.8 & L1 << 0.2 & (L5 >> 0.4 | L7 << 0.1)).arr,
2)
L1.arr = None
L1 = None
L6.arr = None
L6 = None
gc.collect()
print("test 2 done")
# ====================================
for i in range(shape[0]):
for j in range(shape[1]):
if test3[i][j] == 3:
b_5_61 = b_5s[i - 30:i + 31, j - 30:j + 31]
b_7_61 = b_7s[i - 30:i + 31, j - 30:j + 31]
not_water61 = not_water[i - 30:i + 31, j - 30:j + 31]
test3_61 = test3[i - 30:i + 31, j - 30:j + 31]
shape61 = b_5_61.shape
arr_7 = []
arr_5 = []
for x in range(shape61[0]):
for y in range(shape61[1]):
if b_7_61[x][y] > 0 and not_water61[x][y] and test3_61[
x][y] == 0:
arr_7.append(b_7_61[x][y])
arr_5.append(b_5_61[x][y])
arr_7 = np.array(arr_7)
arr_5 = np.array(arr_5)
Div_7_5 = arr_7 / arr_5
# print(R75)
Sr_7 = np.mean(arr_7)
Sr_5 = np.mean(arr_5)
Div_Sr7_Sr5 = Sr_7 / Sr_5
STD_7 = np.std(arr_7)
STD_75 = np.std(Div_7_5)
if (L7[i][j] > Sr_7 + max(3 * STD_7, 0.08)) and (
L7[i][j] / L5[i][j] >
Div_Sr7_Sr5 + max(3 * STD_75, 0.8)):
result[i][j] = 3
#===============================================================================
np.save(path_res + r'\fire_mask_' + info, result)
mask = np.zeros(shape, dtype=np.uint8)
np.putmask(mask, result != 0, 1)
k = np.sum(mask)
print(k, 'Points')
for i in range(mask.shape[0]):
for j in range(mask.shape[1]):
if mask[i][j] == 1:
mask[i - 50:i + 51, j - 50:j + 51] = 10
imageio.imwrite(path_res + r'\mask_' + info + '.jpg', mask)
plt.title("result")
plt.imshow(mask, cmap='gray')
return k
