def results_image(filename):
path = 'images/' + filename
start = datetime.now()
image = path
# calculate size of image
KB = int(math.floor(os.path.getsize(image) / 1024))
# if image size is smaller than 300KB, print this
if KB < 50:
result = "이미지 크기가 {}KB 입니다. 높은 화질의 이미지를 올려주세요.".format(KB)
print(result)
else:
project.plateText(image)
plate_name = 'found_plate.jpg'
plate = cv2.imread(plate_name)
hsv_img = cv2.cvtColor(plate, cv2.COLOR_BGR2HSV) # image color convert to hsv
#################################
# Blue color range -> Electronic Vehicle
blue_mask = cv2.inRange(hsv_img, (85, 80, 20), (125, 255, 255))
blue = cv2.bitwise_and(plate, plate, mask=blue_mask)
count_blue = np.count_nonzero(blue != 0)
##################################
# print('Detected blue points {}'.format( count_blue )) # find blue points as 0
##################################
# Green color -> General Vehicle
green_mask = cv2.inRange(hsv_img, (40, 80, 20), (80, 255, 255))
green = cv2.bitwise_and(plate, plate, mask=green_mask)
count_green = np.count_nonzero(green != 0)
##################################
# print('Detected Green points {}'.format( count_green ))
##################################
# White color -> General Vehicle
white_mask = cv2.inRange(hsv_img, (0, 0, 170), (131, 255, 255))
white = cv2.bitwise_and(plate, plate, mask=white_mask)
count_white = np.count_nonzero(white != 0)
##################################
# print('Detected White points {}'.format( count_white ))
##################################
# yellow color -> Commercial car
yellow_mask = cv2.inRange(hsv_img, (15, 80, 20), (35, 255, 255))
yellow = cv2.bitwise_and(plate, plate, mask=yellow_mask)
count_yellow = np.count_nonzero(yellow != 0)
##################################
# print('Detected Yellow points {}'.format( count_yellow ) )
plate_list = [blue, green, white, yellow]
value_list = [count_blue, count_green, count_white, count_yellow]
max_value = max(value_list)
index = value_list.index(max_value)
car_kinds = ['Electronic Vehicle', 'General Vehicle', 'Commercial Vehicle']
match_result = project.ShowMatches(plate_name)
save = cv2.imread('saved.jpg')
if index == 0:
car = car_kinds[0]
plate_img = project.FindRectangle()
plt.subplot(211)
plt.axis("off")
plt.imshow(cv2.cvtColor(plate_img, cv2.COLOR_BGR2RGB))
plt.subplot(212)
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save.png")
plt.show()
elif index == 1 or index == 2:
car = car_kinds[1]
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save.png")
plt.show()
else:
car = car_kinds[2]
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save.png")
plt.show()
print(car)
# print("This Car is {}".format(car) )
# plt.imshow( cv2.cvtColor(plate_list[index], cv2.COLOR_BGR2RGB) )
print(datetime.now() - start)
return 'finished application'
import matplotlib.pyplot as plt
import project
from datetime import datetime, timedelta
import math
start = datetime.now()
image = 'e23.jpg'
# calculate size of image
KB = int(math.floor(os.path.getsize(image) / 1024))
# if image size is smaller than 300KB, print this
if KB < 50:
result = "이미지 크기가 {}KB 입니다. 높은 화질의 이미지를 올려주세요.".format(KB)
print(result)
else:
project.plateText(image)
plate_name = 'found_plate.jpg'
plate = cv2.imread(plate_name)
hsv_img = cv2.cvtColor(plate,
cv2.COLOR_BGR2HSV) # image color convert to hsv
#################################
# Blue color range -> Electronic Vehicle
blue_mask = cv2.inRange(hsv_img, (85, 80, 20), (125, 255, 255))
blue = cv2.bitwise_and(plate, plate, mask=blue_mask)
count_blue = np.count_nonzero(blue != 0)
##################################
# print('Detected blue points {}'.format( count_blue )) # find blue points as 0
##################################
# Green color -> General Vehicle
def upload():
target = os.path.join(APP_ROOT, 'images/')
# target = os.path.join(APP_ROOT, 'static/')
print(target)
if not os.path.isdir(target):
os.mkdir(target)
else:
print("Couldn't create upload directory: {}".format(target))
print(request.files.getlist("file"))
for upload in request.files.getlist("file"):
print(upload)
print("{} is the file name".format(upload.filename))
filename = upload.filename
destination = "/".join([target, filename])
print("Accept incoming file:", filename)
print("Save it to:", destination)
upload.save(destination)
path = 'images/' + filename
start = datetime.now()
image = path
# calculate size of image
KB = int(math.floor(os.path.getsize(image) / 1024))
# if image size is smaller than 300KB, print this
if KB < 50:
result = "이미지 크기가 {}KB 입니다. 높은 화질의 이미지를 올려주세요.".format(KB)
print(result)
else:
project.plateText(image)
plate_name = 'found_plate.jpg'
plate = cv2.imread(plate_name)
hsv_img = cv2.cvtColor(
plate, cv2.COLOR_BGR2HSV) # image color convert to hsv
#################################
# Blue color range -> Electronic Vehicle
blue_mask = cv2.inRange(hsv_img, (85, 80, 20), (125, 255, 255))
blue = cv2.bitwise_and(plate, plate, mask=blue_mask)
count_blue = np.count_nonzero(blue != 0)
##################################
# print('Detected blue points {}'.format( count_blue )) # find blue points as 0
##################################
# Green color -> General Vehicle
green_mask = cv2.inRange(hsv_img, (40, 80, 20), (80, 255, 255))
green = cv2.bitwise_and(plate, plate, mask=green_mask)
count_green = np.count_nonzero(green != 0)
##################################
# print('Detected Green points {}'.format( count_green ))
##################################
# White color -> General Vehicle
white_mask = cv2.inRange(hsv_img, (0, 0, 170), (131, 255, 255))
white = cv2.bitwise_and(plate, plate, mask=white_mask)
count_white = np.count_nonzero(white != 0)
##################################
# print('Detected White points {}'.format( count_white ))
##################################
# yellow color -> Commercial car
yellow_mask = cv2.inRange(hsv_img, (15, 80, 20), (35, 255, 255))
yellow = cv2.bitwise_and(plate, plate, mask=yellow_mask)
count_yellow = np.count_nonzero(yellow != 0)
##################################
# print('Detected Yellow points {}'.format( count_yellow ) )
plate_list = [blue, green, white, yellow]
value_list = [count_blue, count_green, count_white, count_yellow]
max_value = max(value_list)
index = value_list.index(max_value)
car_kinds = [
'Electronic Vehicle', 'General Vehicle', 'Commercial Vehicle'
]
match_result = project.ShowMatches(plate_name)
save = cv2.imread('saved.jpg')
if index == 0:
car = car_kinds[0]
plate_img = project.FindRectangle()
plt.subplot(211)
plt.axis("off")
plt.imshow(cv2.cvtColor(plate_img, cv2.COLOR_BGR2RGB))
plt.subplot(212)
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save.png")
plt.show()
elif index == 1 or index == 2:
car = car_kinds[1]
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save.png")
plt.show()
else:
car = car_kinds[2]
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save.png")
plt.show()
print(car)
# print("This Car is {}".format(car) )
# plt.imshow( cv2.cvtColor(plate_list[index], cv2.COLOR_BGR2RGB) )
print(datetime.now() - start)
# color detection from BGR -> HSV
# return send_from_directory("images", filename, as_attachment=True)
return render_template("complete.html", image_name=filename)
def upload():
target = os.path.join(APP_ROOT, 'images/')
# target = os.path.join(APP_ROOT, 'static/')
print(target)
if not os.path.isdir(target):
os.mkdir(target)
else:
print("Couldn't create upload directory: {}".format(target))
print(request.files.getlist("file"))
for upload in request.files.getlist("file"):
print(upload)
print("{} is the file name".format(upload.filename))
filename = upload.filename
destination = "/".join([target, filename])
print ("Accept incoming file:", filename)
print ("Save it to:", destination)
upload.save(destination)
################################################################################################################
path = 'images/' + filename
start = datetime.now()
image = path
# calculate size of image
KB = int(math.floor(os.path.getsize(image) / 1024))
# if image size is smaller than 300KB, print this
if KB < 30:
result = "이미지 크기가 {}KB 입니다. 높은 화질의 이미지를 올려주세요.".format(KB)
print(result)
else:
project.plateText(image)
plate_name = 'found_plate.jpg' # saved from platText function
plate = cv2.imread(plate_name)
hsv_img = cv2.cvtColor(plate, cv2.COLOR_BGR2HSV) # image BGR color convert to hsv
#################################
# Blue color range -> Electronic Vehicle
blue_mask = cv2.inRange(hsv_img, (85, 80, 20), (125, 255, 255))
blue = cv2.bitwise_and(plate, plate, mask=blue_mask) # if each point in range, result won't be 0.
count_blue = np.count_nonzero(blue != 0) # count != 0 check how many blue points in Image.
##################################
# print('Detected blue points {}'.format( count_blue )) # find blue points as 0
##################################
# Green color -> General Vehicle
green_mask = cv2.inRange(hsv_img, (40, 80, 20), (80, 255, 255))
green = cv2.bitwise_and(plate, plate, mask=green_mask)
count_green = np.count_nonzero(green != 0)
##################################
# print('Detected Green points {}'.format( count_green ))
##################################
# White color -> General Vehicle
white_mask = cv2.inRange(hsv_img, (0, 0, 170), (131, 255, 255))
white = cv2.bitwise_and(plate, plate, mask=white_mask)
count_white = np.count_nonzero(white != 0)
##################################
# print('Detected White points {}'.format( count_white ))
##################################
# yellow color -> Commercial car
yellow_mask = cv2.inRange(hsv_img, (15, 80, 20), (35, 255, 255))
yellow = cv2.bitwise_and(plate, plate, mask=yellow_mask)
count_yellow = np.count_nonzero(yellow != 0)
##################################
# print('Detected Yellow points {}'.format( count_yellow ) )
plate_list = [blue, green, white, yellow] # each plate Image list.
value_list = [count_blue, count_green, count_white, count_yellow] # each number of points will be list.
max_value = max(value_list) # Find max count in Value list
index = value_list.index(max_value) # Find Index in Value list
car_kinds = ['Electronic Vehicle', 'Not Electronic Vehicle']
match_result, detected = project.ShowMatches(plate_name) # show Feature Matching result
detected = match_result
save = cv2.imread('saved.jpg')
timestr = time.strftime("%Y%m%d-%H%M%S")
time_data = time.strftime("%Y/%m/%d %H:%M:%S")
savename = "results/save" + timestr + ".png"
if detected >= 1:
car = car_kinds[0] # Car will be EV
plate_img = project.FindRectangle()[0]
plt.subplot(211)
plt.axis("off")
plt.imshow(cv2.cvtColor(plate_img, cv2.COLOR_BGR2RGB))
plt.subplot(212)
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save" + timestr + ".png")
plt.show()
else:
if index == 0: # if blue points detected
if FindRectangle()[1] == True: # Double check from Template Matching
car = car_kinds[0] # Car will be EV
plate_img = FindRectangle()[0]
plt.subplot(211)
plt.axis("off")
plt.imshow(cv2.cvtColor(plate_img, cv2.COLOR_BGR2RGB))
plt.subplot(212)
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save" + timestr + ".png")
plt.show()
else: # Color = Blue but nothing detected from Template Matching
car = car_kinds[1]
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save" + timestr + ".png")
plt.show()
else: # When they found White or Green Color.
car = car_kinds[1]
plt.axis("off")
plt.imshow(cv2.cvtColor(save, cv2.COLOR_BGR2RGB))
plt.savefig("static/results/save" + timestr + ".png")
plt.show()
processing = datetime.now() - start
print("This Car is {}".format(car))
# color detection from BGR -> HSV
# return send_from_directory("images", filename, as_attachment=True)
return render_template("complete.html", image_name=filename, car = car, processing = processing, savename = savename, time_data = time_data)