def training_begin(cap, borders):
seed(5)
start_time = time.time()
ret, frame = cap.read()
frame = cv2.flip(frame, 1) # odbicie lustrzane
points = define_trace(borders)
point1 = points.get()
point2 = points.get()
points.put([10000, 10000])
points.put([10000, 10000])
while (not points.empty()):
ret, frame = cap.read()
frame = cv2.flip(frame, 1) # odbicie lustrzane
bin = binarize_paddles(frame)
if point_reched(point1, frame) and point_reched(
point2, frame) and not points.empty():
point1 = points.get()
point2 = points.get()
if point1[0] < 2000:
frame = cv2.circle(frame, (point1[0], point1[1]), 2, (0, 255, 255),
20)
frame = cv2.circle(frame, (point2[0], point2[1]), 2, (0, 255, 255),
20)
cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("window", cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
cv2.imshow("window", frame)
if cv2.waitKey(1) & 0xFF == ord('e'):
end_time = time.time()
return count_score(start_time, end_time)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
end_time = time.time()
return count_score(start_time, end_time)
def point_reched(point, frame):
bin = binarize_paddles(frame)
reached = False
for x in range(-3, 3):
for y in range(-3, 3):
if bin[point[1] + x, point[0] + y] == 255:
reached = True
return reached
def camera_configured(cap):
training_should_start = False
debug = False
while (not training_should_start):
ret, rawframe = cap.read()
rawframe = cv2.flip(rawframe, 1) # odbicie lustrzane
bin = binarize_paddles(rawframe)
paddles_up = detectPaddlesUp(bin)
if paddles_up:
face_x, face_y = weighted_center_of_face(rawframe)
print(face_x, face_y)
if face_x != -1 and face_y != 0:
human_core_y = face_y + int(round(0.5 * face_y))
human_core_x = face_x
height = len(rawframe)
width = len(rawframe[0])
scale_x = int(1.6 * face_y)
left_point_x = max(human_core_x - scale_x, 0) + 5
left_point_y = 5
right_point_x = min(human_core_x + scale_x, width - 1) - 5
right_point_y = height - 6
if debug:
rawframe = cv2.circle(rawframe, (face_x, face_y), 15,
(255, 0, 0), 2)
rawframe = cv2.circle(rawframe,
(human_core_x, human_core_y), 15,
(255, 255, 0), 2)
rawframe = cv2.rectangle(rawframe,
(left_point_x, left_point_y),
(right_point_x, right_point_y),
(255, 0, 0), 2)
cv2.imshow("window", rawframe)
cv2.waitKey(0)
cv2.destroyAllWindows()
return [
int(round(left_point_x)),
int(round(left_point_y)),
int(round(right_point_x)),
int(round(right_point_y))
]
rawframe = cv2.putText(
rawframe,
"Prosze podniesc paletki do gornej krawedzi ekranu", (45, 50),
cv2.FONT_HERSHEY_COMPLEX,
0.6, (255, 0, 255),
1,
lineType=cv2.LINE_AA)
cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("window", cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
cv2.imshow("window", rawframe)
# cv2.imshow("binary", bin)
if cv2.waitKey(1) & 0xFF == ord('e'):
return [100, 100, 400, 400]
if cv2.waitKey(1) & 0xFF == ord('q'):
break
def hello():
cap = cv2.VideoCapture(0)
seed(2)
cnt = 0
ret, rawframe = cap.read()
frame = cv2.flip(rawframe, 1) #odbicie lustrzane
x_offset = 5
y_offset = 65
cv2.imshow("frame", frame)
width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
height = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
x = randint(x_offset, width - x_offset)
y = randint(y_offset, height - y_offset)
while (True):
#cv2.waitKey(1000)
ret, rawframe = cap.read()
frame = cv2.flip(rawframe, 1) #odbicie lustrzane
pixel = frame[x, y, :]
# Get R, G, B values (This are int from 0 to 255)
red = pixel[2]
green = pixel[1]
blue = pixel[0]
print(red, green, blue)
if red > 200:
x = randint(x_offset, width - x_offset)
y = randint(y_offset, height - y_offset)
print("wchodzę", x, y)
frame = show_point(frame, x, y)
cv2.namedWindow("frame", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("frame", cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
cv2.imshow("frame", binarize_paddles(frame))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cnt += 1
cap.release()
cv2.destroyAllWindows()
import os
import cv2
import time
from paddles import binarize_paddles
directory = '/home/michask/talus/zdjecia/'
for filename in os.listdir(directory):
if filename.endswith(".jpg"):
print(filename)
img = cv2.imread(r'zdjecia/' + filename)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
cv2.imshow('a', img)
cv2.imshow('H', binarize_paddles(img))
cv2.waitKey(1000)
import os
import cv2
import time
from paddles import binarize_paddles
from kalibracja import detectPaddlesUp
from detect_face import weighted_center_of_face
directory = 'zdjecia_kuchnia/'
import math
for filename in os.listdir(directory):
if filename.endswith(".bmp"):
print(filename)
img = cv2.imread(r'zdjecia_kuchnia/' + filename)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
bin = binarize_paddles(img)
is_paddles_up = detectPaddlesUp(bin)
print(is_paddles_up)
if is_paddles_up:
face_x, face_y = weighted_center_of_face(img)
print(face_x, face_y)
if face_x != -1 and face_y != 0:
human_core_y = face_y + int(round(0.5 * face_y))
human_core_x = face_x
height = len(img)
width = len(img[0])
scale_x = int(1.6 * face_y)
left_point_x = max(human_core_x - scale_x, 0)
left_point_y = 0
right_point_x = min(human_core_x + scale_x, width - 1)
right_point_y = height - 1
img = cv2.circle(img, (face_x, face_y), 15, (255, 0, 0), 2)