def test_crop_per():
crop(scr_folder="images", dest_folder="cper", px=None, per=50)
a_images = glob.glob("./images/*.*")
o_images = glob.glob("./cper/*.*")
im1 = Image.open(o_images[0])
im2 = Image.open(os.path.join("images", o_images[0].split("\\")[-1]))
assert im1.size[0] < im2.size[0]
def main():
#initialize the crop matrix using the following syntax:
crop_matrix = [[crop("NULL") for x in range(5)] for x in range(5)]
seed_list = []
bank_balance = bank(250)
numb_of_seeds = [0,0,0,0,0,0]
seed_list.append(seed("Wheat"))
seed_list.append(seed("Rice"))
seed_list.append(seed("Cotton"))
seed_list.append(seed("Jute"))
seed_list.append(seed("Banana"))
seed_list.append(seed("Apple"))
start_time = time.time()
print(start_time)
print_crop_matrix(crop_matrix,bank_balance,seed_list,numb_of_seeds)
add_seed("Wheat",seed_list,numb_of_seeds,bank_balance)
print_crop_matrix(crop_matrix,bank_balance,seed_list,numb_of_seeds)
add_seed("Cotton",seed_list,numb_of_seeds,bank_balance)
print_crop_matrix(crop_matrix,bank_balance,seed_list,numb_of_seeds)
add_to_crop_matrix("Wheat",0,0,crop_matrix,seed_list,numb_of_seeds)
crop_matrix[0][0].water()
crop_matrix[0][0].water()
crop_matrix[0][0].water()
crop_matrix[0][0].water()
crop_matrix[0][0].water()
crop_matrix[0][0].water()
print_crop_matrix(crop_matrix,bank_balance,seed_list,numb_of_seeds)
crop_matrix[0][0].water()
print_crop_matrix(crop_matrix,bank_balance,seed_list,numb_of_seeds)
crop_matrix[0][0].water()
print_crop_matrix(crop_matrix,bank_balance,seed_list,numb_of_seeds)
print(time.time()-start_time)
x1, y1 = cell_b[1]
b = cropped[(y0 - M):(y1 + M), (x0 - M):(x1 + M)]
tb = cropped[(y0 + P):(y1 - P), (x0 + P):(x1 - P)]
if np.mean(tb) > B: return 0
m = cv2.matchTemplate(a, tb, cv2.TM_CCOEFF_NORMED)
n = cv2.matchTemplate(b, ta, cv2.TM_CCOEFF_NORMED)
return (cv2.minMaxLoc(m)[1] + cv2.minMaxLoc(n)[1]) / 2
if __name__ == '__main__':
a = sys.argv[1]
n = a[:a.find('.')]
original = cv2.imread(a)
cropped = crop(original, m=30, f=6, fast=True)
cells = cells(cropped)
erased = np.copy(cropped)
for column in cells:
for cell in column[1:]:
adjust_borders(erased, cell)
erase_borders(erased, cell, borders_adjusted=True)
highlighted = np.copy(cropped)
for column in cells[1:-1]:
scores = [False] * len(column)
for i in range(2, len(column) - 2):
for j in range(i + 1, len(column) - 1):
import numpy as np
import cv2
import pygame
# modules::
from crop import *
from checkingGrid import *
## Image to calibrate where the grid is located
image_calibration = cv2.imread('Pictures/gridBlob.jpg')
## Image to actually crop (should be the orignal one)
image = cv2.imread('Pictures/test_2.jpg')
crop(image_calibration, image, "Grid_Image.jpg")
# PATH TO NEW IMAGE IS Pictures/Grid_Image.jpg !!
for point in find_shapes('Pictures/Grid_Image.jpg'):
print(point)
for MinMax in shape_positions(image,point):
print(MinMax)
fill_array(MinMax,placementArr)
#PRINTING THE ARRAY< FOR DEBUGGING
for row in placementArr:
print(row)
def detect(filename, folder, file_no):
# print 'in'
img = cv2.imread(filename)
img = cv2.medianBlur(img, 1) #smothing image
# extracting white characters
image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgray = crop(image)
# imgray = image
imgray = cv2.resize(imgray, (880, 100))
(h, w) = imgray.shape
(img_h, img_w) = (h, w)
drawing = noise(imgray, imgray.shape, 1000, 25000)
cv2.imshow('win1', drawing)
cv2.waitKey()
cv2.imwrite('E:\Results\\res.jpg', drawing)
# character recorgnition
image = cv.LoadImage("E:\Results\\res.jpg", cv.CV_LOAD_IMAGE_GRAYSCALE)
lang = ['eng']
result = 0
for i in lang:
data = pytesser.iplimage_to_string(image,
i,
pytesser.PSM_SINGLE_LINE,
makebox=True)
# print data
word = ''
section = [] #all the characters and coordinates in a list
line = []
for i in data:
if i == ' ' or i == '\n':
line.append(word)
word = ''
elif (i != '\n'):
word += i
if i == '\n':
section.append(line)
line = []
coord = []
chars = [] #coordinates of the characters
count = 0
for i in section:
for j in i:
# print count
if j.isdigit() and count < 5 and count > 0:
coord.append(int(j))
count += 1
count = 0
chars.append(coord)
coord = []
# removing all symbols
dele = 0
delete = []
for i in section:
if not i[0].isdigit() and not i[0].isalpha():
delete.append(dele)
dele += 1
delete.reverse()
for i in delete:
section.pop(i)
chars.pop(i)
c = 0
point = []
for i in chars:
cv2.rectangle(drawing, (i[0], i[1]), (i[2], i[3]), (255, 255, 255), 2)
cv2.imshow('rec', drawing)
cv2.waitKey(1)
cv2.imwrite('E:\\report\\res.jpg', drawing)
counter = 0
line_coordinates = [0]
if len(chars) == 1:
for i in chars:
if i[0] > 400:
line_coordinates.append(i[0] / 2)
line_coordinates.append(i[0])
# for debugging, draws box using coordinates received from make box function
for i in chars:
counter += 1
if c == 0:
point.append(i[2])
c = 1
elif c == 1:
point.append(i[0])
line = ((point[0] + point[1]) / 2)
line_coordinates.append(line)
cv2.line(drawing, (line, img_h), (line, 0), (255, 255, 255), 2)
c = 0
point = []
if counter == len(chars):
if img_w - i[2] < 150:
line_coordinates.append(img_w)
else:
line_coordinates.append(i[2])
line_coordinates.append(img_w)
cv2.line(drawing, (i[2], img_h), (i[2], 0), (255, 255, 255), 2)
# spliting image and processing
iterator = 1
id = ''
while iterator < len(line_coordinates):
roi = imgray[0:img_h,
line_coordinates[iterator - 1]:line_coordinates[iterator]]
iterator += 1
corrected = noise(roi, roi.shape, 300, 20000)
cv2.imwrite('E:\Results\\res.jpg', corrected)
cv2.imshow('win1', corrected)
cv2.waitKey(1)
image = cv.LoadImage("E:\Results\\res.jpg", cv.CV_LOAD_IMAGE_GRAYSCALE)
data = pytesser.iplimage_to_string(image, 'enm', 7)
# print data
for i in data:
if i == '!':
i = '1'
if i.isalpha() or i.isdigit():
if i == 'O' or i == 'o':
i = '0'
if i == 'L' or i == 'l':
i = '1'
if i == 'i' or i == 'I':
i = '1'
id = id + i
# print id
if id != '':
print id
sol = check(id)
final = sol[0]
alternative = sol[1]
possible = sol[2]
else:
return None
# print sol
if not final:
os.chdir(folder)
filename = 'error' + str(file_no)
img_name = filename + '.jpg'
txt_name = filename + '.txt'
cv2.imwrite(img_name, img)
if len(alternative) > 1: #storing alternatives in a text file
f = open(txt_name, 'w')
for i in alternative:
f.write(i + '\n')
f.close()
return None
else:
return possible
def remove_from_crop_matrix(i,j,crop_matrix):
crop_matrix[i][j]=crop("null")
def add_to_crop_matrix(crop_name,i,j,crop_matrix,seed_list,numb_of_seeds):
if(check_for_empty_cell_crop_matrix(crop_matrix,i,j)==True):
if(delete_seed(crop_name,seed_list,numb_of_seeds)==True):
crop_matrix[i][j] = crop(crop_name)
def detect(filename, folder, file_no):
# print 'in'
img = cv2.imread(filename)
img = cv2.medianBlur(img, 1) #smothing image
# extracting white characters
image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgray = crop(image)
# imgray = image
imgray = cv2.resize(imgray, (880,100))
(h,w) = imgray.shape
(img_h,img_w) = (h,w)
drawing = noise(imgray, imgray.shape, 1000, 25000)
cv2.imshow('win1', drawing)
cv2.waitKey()
cv2.imwrite('E:\Results\\res.jpg', drawing)
# character recorgnition
image = cv.LoadImage("E:\Results\\res.jpg", cv.CV_LOAD_IMAGE_GRAYSCALE)
lang = ['eng']
result = 0
for i in lang:
data = pytesser.iplimage_to_string(image, i, pytesser.PSM_SINGLE_LINE,makebox=True)
# print data
word = ''
section = [] #all the characters and coordinates in a list
line = []
for i in data:
if i == ' ' or i=='\n':
line.append(word)
word = ''
elif (i!='\n'):
word+=i
if i == '\n':
section.append(line)
line = []
coord = []
chars = [] #coordinates of the characters
count = 0
for i in section:
for j in i:
# print count
if j.isdigit() and count < 5 and count > 0:
coord.append(int(j))
count += 1
count = 0
chars.append(coord)
coord = []
# removing all symbols
dele= 0
delete=[]
for i in section:
if not i[0].isdigit() and not i[0].isalpha():
delete.append(dele)
dele += 1
delete.reverse()
for i in delete:
section.pop(i)
chars.pop(i)
c = 0
point = []
for i in chars:
cv2.rectangle(drawing,(i[0],i[1]),(i[2],i[3]),(255,255,255),2)
cv2.imshow('rec', drawing)
cv2.waitKey(1)
cv2.imwrite('E:\\report\\res.jpg', drawing)
counter = 0
line_coordinates = [0]
if len(chars) == 1:
for i in chars:
if i[0] > 400:
line_coordinates.append(i[0]/2)
line_coordinates.append(i[0])
# for debugging, draws box using coordinates received from make box function
for i in chars:
counter += 1
if c == 0:
point.append(i[2])
c = 1
elif c == 1:
point.append(i[0])
line = ((point[0] + point[1]) / 2)
line_coordinates.append(line)
cv2.line(drawing,(line,img_h),(line,0),(255,255,255),2)
c = 0
point = []
if counter == len(chars):
if img_w - i[2] < 150:
line_coordinates.append(img_w)
else:
line_coordinates.append(i[2])
line_coordinates.append(img_w)
cv2.line(drawing,(i[2],img_h),(i[2],0),(255,255,255),2)
# spliting image and processing
iterator = 1
id = ''
while iterator < len(line_coordinates):
roi = imgray[0:img_h, line_coordinates[iterator-1]:line_coordinates[iterator]]
iterator += 1
corrected = noise(roi, roi.shape, 300, 20000)
cv2.imwrite('E:\Results\\res.jpg', corrected)
cv2.imshow('win1', corrected)
cv2.waitKey(1)
image = cv.LoadImage("E:\Results\\res.jpg", cv.CV_LOAD_IMAGE_GRAYSCALE)
data = pytesser.iplimage_to_string(image, 'enm', 7 )
# print data
for i in data:
if i == '!':
i = '1'
if i.isalpha() or i.isdigit():
if i == 'O' or i =='o':
i = '0'
if i == 'L' or i == 'l':
i = '1'
if i == 'i' or i == 'I':
i = '1'
id = id + i
# print id
if id != '':
print id
sol = check(id)
final = sol[0]
alternative = sol[1]
possible = sol[2]
else:
return None
# print sol
if not final:
os.chdir(folder)
filename = 'error' + str(file_no)
img_name = filename + '.jpg'
txt_name = filename + '.txt'
cv2.imwrite(img_name, img)
if len(alternative) > 1: #storing alternatives in a text file
f = open(txt_name, 'w')
for i in alternative:
f.write(i+'\n')
f.close()
return None
else:
return possible
