def init(row, col, win_name):
# win_name = str(x) + str(y)
if win_name in windowses:
return
cv.namedWindow(win_name, cv.WINDOW_NORMAL)
cv.resizeWindow(win_name, WIN_SIZE[0], WIN_SIZE[1])
cv.moveWindow(win_name, col * WIN_SIZE[0], row * WIN_SIZE[1])
windowses.add(win_name)
def main():
img = './../img/clip_field.png'
window_name = 'WindowDAYO'
img = cv2.imread(img)
get_circle_point = GetCirclePoint()
cv2.namedWindow(window_name)
cv2.setMouseCallback(window_name, get_circle_point.drag_and_drop_square,
[window_name, img, get_circle_point])
cv2.imshow(window_name, img)
cv2.moveWindow(window_name, 100, 100) # 左上にウィンドウを出す
cv2.waitKey()
print(get_circle_point.named_points)
cv2.destroyAllWindows()
def run_get_circle_point(self):
img = self.bingo_img
window_name = self.window_name
img = cv2.imread(img)
self.set_get_circle_point(GetCirclePoint(window_name=window_name))
cv2.namedWindow(window_name)
cv2.setMouseCallback(window_name,
self.get_circle_point.drag_and_drop_square,
[window_name, img, self.get_circle_point])
cv2.imshow(window_name, img)
cv2.moveWindow(window_name, 100, 100) # 左上にウィンドウを出す
cv2.waitKey()
print(self.get_circle_point.named_points)
def screen_record():
while (True):
sct.get_pixels(frame)
img = Image.frombytes('RGB', (sct.width, sct.height), sct.image)
new_screen = find_white(img)
winname = "Test"
cv2.namedWindow(winname)
cv2.moveWindow(winname, 1450, 100)
cv2.imshow(winname, new_screen)
n_white_pix = np.sum(new_screen == 255)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
return n_white_pix
def showImageWithBox(dataset):
for row in dataset:
if 'LEFT' in dataset[row]:
if 'CC' in dataset[row]['LEFT']:
whole_image = loadImage(dataset[row]['LEFT']['CC'][0])
list_templates = []
for i in range(1, len(dataset[row]['LEFT']['CC'])):
list_templates.append(
loadImage(dataset[row]['LEFT']['CC'][i][0])),
processImage(dataset[row]['LEFT']['CC'][i][1])
cv2.imshow("imageLeftCc",
resizeImage(searchBox(whole_image, list_templates)))
cv2.moveWindow("imageLeftCc", 500, 50)
cv2.waitKey(0)
if 'MLO' in dataset[row]['LEFT']:
whole_image = loadImage(dataset[row]['LEFT']['MLO'][0])
list_templates = []
for i in range(1, len(dataset[row]['LEFT']['MLO'])):
list_templates.append(
loadImage(dataset[row]['LEFT']['MLO'][i][0]))
processImage(dataset[row]['LEFT']['MLO'][i][1])
cv2.imshow("imageLeftMlo",
resizeImage(searchBox(whole_image, list_templates)))
cv2.moveWindow("imageLeftMlo", 500, 50)
cv2.waitKey(0)
if 'RIGHT' in dataset[row]:
if 'CC' in dataset[row]['RIGHT']:
whole_image = loadImage(dataset[row]['RIGHT']['CC'][0])
list_templates = []
for i in range(1, len(dataset[row]['RIGHT']['CC'])):
list_templates.append(
loadImage(dataset[row]['RIGHT']['CC'][i][0]))
processImage(dataset[row]['RIGHT']['CC'][i][1])
cv2.imshow("imageRightCc",
resizeImage(searchBox(whole_image, list_templates)))
cv2.moveWindow("imageRightCc", 500, 50)
cv2.waitKey(0)
if 'MLO' in dataset[row]['RIGHT']:
whole_image = loadImage(dataset[row]['RIGHT']['MLO'][0])
list_templates = []
for i in range(1, len(dataset[row]['RIGHT']['MLO'])):
list_templates.append(
loadImage(dataset[row]['RIGHT']['MLO'][i][0]))
processImage(dataset[row]['RIGHT']['MLO'][i][1])
cv2.imshow("imageRightMlo",
resizeImage(searchBox(whole_image, list_templates)))
cv2.moveWindow("imageRightMlo", 500, 50)
cv2.waitKey(0)
def main(decay, velocity):
source_img = cv2.imread(source)
target_img = np.zeros_like(source_img)
row, col = source_img.shape[0], source_img.shape[1]
center = [col / 2, row / 2]
x_rel = numpy.matlib.repmat(np.arange(col), row, 1) - center[0]
y_rel = center[1] - np.transpose(
numpy.matlib.repmat(np.arange(row), col, 1))
theta = np.arctan2(y_rel, x_rel)
r = np.sqrt(pow(x_rel, 2) + pow(y_rel, 2)) + decay * col * np.sin(
velocity * np.sqrt(pow(x_rel, 2) + pow(y_rel, 2)))
x_out = r * np.cos(theta) + center[0]
y_out = center[1] - r * np.sin(theta)
for i in range(row):
for j in range(col):
if x_out[i, j] >= 0 and x_out[i, j] <= col - 1 and y_out[
i, j] >= 0 and y_out[i, j] <= row - 1:
target_img[i, j, :] = bilinear(x_out[i, j], y_out[i, j],
source_img)
elif i == 0 and j == 0:
target_img[i, j, :] = [0, 0, 0]
elif i == 0:
target_img[i, j, :] = target_img[i, j - 1, :]
elif j == 0:
target_img[i, j, :] = target_img[i - 1, j, :]
else:
if random.random() < 0.5:
target_img[i, j, :] = target_img[i, j - 1, :]
else:
target_img[i, j, :] = target_img[i - 1, j, :]
# target_img[i, j, :] = target_img[i - 1, j - 1, :]
target_img = target_img.astype(np.uint8)
cv2.namedWindow('Water wave', 0)
cv2.moveWindow('Water wave', 480, 160)
cv2.imwrite('results/wwtemp.png', target_img)
cv2.imshow('Water wave', target_img)
cv2.waitKey()
cv2.destroyAllWindows()
def acquire_images(cam, save_queue: queue.Queue) -> None:
cv2.namedWindow(WINDOW_NAME)
cv2.moveWindow(WINDOW_NAME, 0, 0)
cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous)
cam.BeginAcquisition()
print("Acquisition started.")
print("Press enter to save images. Press escape to exit.")
pixel_format = cam.PixelFormat.GetCurrentEntry().GetSymbolic()
while True:
retrieved_image = get_newest_image(cam, pixel_format)
if retrieved_image is None:
break
cv2.imshow(
WINDOW_NAME,
retrieved_image.get_resized_image(flags.FLAGS.display_width),
)
keypress = cv2.waitKey(1)
if keypress == 27:
# escape key pressed
break
elif cv2.getWindowProperty(WINDOW_NAME, cv2.WND_PROP_VISIBLE) < 1:
# x button clicked
break
elif keypress == 13:
# Enter key pressed
cv2.imshow(
WINDOW_NAME,
retrieved_image.get_highlighted_image(
flags.FLAGS.display_width),
)
save_queue.put(retrieved_image)
cv2.waitKey(500)
save_queue.put(None)
cv2.destroyWindow(WINDOW_NAME)
cam.EndAcquisition()
print("Acquisition Ended.")
def acquire_images(cam, save_queue: queue.Queue) -> None:
cv2.namedWindow(WINDOW_NAME)
cv2.moveWindow(WINDOW_NAME, 0, 0)
cam.start_image_acquisition()
print("Acquisition started.")
print("Press enter to save images. Press escape to exit.")
while True:
retrieved_image = get_newest_image(cam)
if retrieved_image is None:
break
cv2.imshow(
WINDOW_NAME,
retrieved_image.get_resized_image(flags.FLAGS.display_width),
)
keypress = cv2.waitKey(1)
if keypress == 27:
# escape key pressed
break
elif cv2.getWindowProperty(WINDOW_NAME, cv2.WND_PROP_VISIBLE) < 1:
# x button clicked
break
elif keypress == 13:
# Enter key pressed
cv2.imshow(
WINDOW_NAME,
retrieved_image.get_highlighted_image(
flags.FLAGS.display_width),
)
save_queue.put(retrieved_image)
cv2.waitKey(500)
save_queue.put(None)
cv2.destroyWindow(WINDOW_NAME)
cam.stop_image_acquisition()
print("Acquisition Ended.")
def show(image):
result = Recognition().recognize(image)
polygon = []
for qr in result['qr']:
pts = np.array(
list(
map(lambda point: [point.x, point.y],
qr['location'].points)), np.int32).reshape((-1, 1, 2))
polygon.append(pts)
for ring in result['rings']:
cv2.ellipse(img=image,
center=(int(ring.center.x), int(ring.center.y)),
axes=(int(ring.maxLength), int(ring.minLength)),
angle=ring.angle,
color=(0, 255, 255),
startAngle=0,
endAngle=360)
cv2.polylines(image, polygon, True, (0, 255, 255))
cv2.imshow('detected circles', image)
cv2.moveWindow('detected circles', 20, 20)
def run():
read_xml()
flag, end_path = init_pic()
if not flag or not end_path:
print('Init error, not have pictures(filename with .jpg)')
exit(1)
clear_end_pic()
#给随机数一个种子
random.seed(int(time.time()))
luck_filenames = []
#可能会有重复的 多跑十次，还有重复就算了
for i in range(0, luck_num + 10):
for j in range(50):
filename = random_pic_index()
img = cv2.imread(os.getcwd() + '\\' + pictures + '\\' + filename)
cv2.namedWindow("process", cv2.WINDOW_NORMAL)
cv2.moveWindow("process", 600, 200)
cv2.imshow("process", img)
cv2.waitKey(50)
if filename in luck_filenames:
continue
luck_filenames.append(filename)
print('%s picture: %s' % (datetime.datetime.strftime(
datetime.datetime.now(), '%Y-%m-%d %H:%M:%S'), filename))
#拷贝文件
shutil.copyfile(end_path + '\\' + filename,
os.getcwd() + '\\' + end_pic + '\\' + filename)
img = cv2.imread(os.getcwd() + '\\' + end_pic + '\\' + filename)
img = cv2.resize(img, (150, 100))
cv2.namedWindow("result", cv2.WINDOW_NORMAL)
cv2.moveWindow("result", 500, 150)
cv2.imshow("result", img)
cv2.waitKey()
cv2.destroyAllWindows()
if len(luck_filenames) >= luck_num:
break
input('Please enter and then exit!!!')
def display(self) -> None:
cv2.namedWindow(config.Renderer.WINDOW_NAME)
cv2.moveWindow(config.Renderer.WINDOW_NAME, 200, 150)
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
# start the video stream thread
print("[INFO] starting video stream thread...")
vs = FileVideoStream(args["video"]).start()
fileStream = True
vs = VideoStream(src=0).start()
#vs = FileVideoStream(args["video"]).start()
fileStream = False
time.sleep(1.0)
# opening windows to display images and moving them to right positions
cv2.namedWindow('Frame')
cv2.moveWindow('Frame', 0, 0)
cv2.namedWindow('Left Eye')
cv2.moveWindow('Left Eye', 550, 0)
cv2.namedWindow('Equalized Left Eye')
cv2.moveWindow('Equalized Left Eye', 550, 275)
cv2.namedWindow('Minimum Intensity Left Eye')
cv2.moveWindow('Minimum Intensity Left Eye', 550, 500)
cv2.namedWindow('Right Eye')
cv2.moveWindow('Right Eye', 950, 0)
cv2.namedWindow('Equalized Right Eye')
cv2.moveWindow('Equalized Right Eye', 950, 275)
cv2.namedWindow('Minimum Intensity Right Eye')
cv2.moveWindow('Minimum Intensity Right Eye', 950, 500)
def showImage(image, text="image", delay=0):
cv2.namedWindow(text)
cv2.moveWindow(text, 20, 20)
cv2.imshow(text, image)
cv2.waitKey(delay)
def init_window(name, row=0, col=0):
cv.namedWindow(name, cv.WINDOW_NORMAL)
cv.resizeWindow(name, WIN_SIZE[0], WIN_SIZE[1])
cv.moveWindow(name, col * WIN_SIZE[0], row * WIN_SIZE[1])
warmup_img = np.zeros(shape=(IMG_SIZE[1], IMG_SIZE[0], 3), dtype=np.uint8)
show_image(warmup_img, name)
# Usage:
# m.click(0, 0, 1) 使用 X11 坐标
# k.type_string('Hello, World!')
m = PyMouse()
k = PyKeyboard()
# Screen detection
print('[加载]屏幕参数')
x11_x, x11_y = m.screen_size()
pil_x, pil_y = ImageGrab.grab().size
DPI_times = pil_x / x11_x
EMULATOR_HEADER = 39
EMULATOR_BOTTOM = 42
cv2.namedWindow('output', cv2.WINDOW_NORMAL)
cv2.resizeWindow('output', 500, 500)
cv2.moveWindow('output', int(x11_x) - 500, int(x11_y) - 500)
print('[加载]X11 size:', (x11_x, x11_y))
print('[加载]PIL size:', ImageGrab.grab().size)
print('[加载]DPI times:', DPI_times)
# Helpers - 图像处理
screen_data = None
class ScanIter(object):
def __init__(self, startp, endp):
self.start_x, self.start_y = startp
self.end_x, self.end_y = endp
def __iter__(self):
for y in range(self.start_y, self.end_y + 1):
print('[INFO] starting video stream thread...')
vs = FileVideoStream(args['video']).start()
fileStream = True
vs = VideoStream(src=0).start()
# vs = FileVideoStream(args["video"]).start()
fileStream = False
time.sleep(1.0)
# opening windows to display images and moving them to right positions
cv2.namedWindow('Frame')
cv2.moveWindow('Frame', 0, 0)
cv2.namedWindow('Left Eye')
cv2.moveWindow('Left Eye', 550, 0)
cv2.namedWindow('Equalized Left Eye')
cv2.moveWindow('Equalized Left Eye', 550, 300)
cv2.namedWindow('Right Eye')
cv2.moveWindow('Right Eye', 950, 0)
cv2.namedWindow('Equalized Right Eye')
cv2.moveWindow('Equalized Right Eye', 950, 300)
img_no = 0
phone_call_done = 0
flashlight_done = 0
import numpy as np
from cv2 import cv2
color = cv2.imread("butterfly.jpg", 1) #w/o one it will still be default 1
print(color.shape)
height, width, channels = color.shape #Dont messup the order of the height and width
cv2.imshow("Burano Italy", color)
cv2.moveWindow("Burano Italy", 0,
0) #Move window to top right corner of screen
######## split channels ##########
b, g, r = cv2.split(color) #split each channel into new matrix
######## Merge channels ###########
#numpy indexing
# Here we are assigning one width section of rgb_split a value one channel matrix and remaining two channels are kept zero
rgb_split = np.empty([height, width * 3, 3],
'uint8') #Empty uninitialized matrix
rgb_split[:, 0:width,
0] = b #blue channel have b, red have zeros and green have zeros
print("Random blue section pixel (b=value/red=0/green=0) = ",
rgb_split[12, round(width / 2)])
rgb_split[:, width:width * 2, 1] = g
print("Random green section pixel (b=0/red=0/green=value) = ",
rgb_split[12, round(width * 2 / 2)])
rgb_split[:, width * 2:width * 3, 2] = r
print("Random red section pixel (b=0/red=value/green=0) = ",
rgb_split[12, round(width * 3 / 2)])
def showImage(image_path, image):
cv2.imshow(image_path, image)
cv2.moveWindow(image_path, 500, 50)
cv2.waitKey(0)
import numpy as np
from cv2 import cv2
import json
import operator
with open('Output Display/test-result.json', 'r') as f:
result = json.load(f)
num_faces = len(result)
img = cv2.imread("Output Display/test_img.jpeg", 1)
for i in range(num_faces):
start_x = result[i]["faceRectangle"]["left"]
start_y = result[i]["faceRectangle"]["top"]
end_x = start_x + result[i]["faceRectangle"]["width"]
end_y = start_y + result[i]["faceRectangle"]["height"]
cv2.rectangle(img, (start_x, start_y), (end_x, end_y), (0, 0, 255), 2)
emotions_dict = result[i]["faceAttributes"]["emotion"]
highest_emotion = max(emotions_dict.items(), key=operator.itemgetter(1))[0]
cv2.rectangle(img, (start_x, end_y), (end_x, end_y+25),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, highest_emotion, (start_x, end_y+13),
cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 255, 255), 1)
# cv2.putText(img , highest_emotion,(start_x-5,start_y-5),cv2.FONT_HERSHEY_SIMPLEX,0.5,(255,255,255), 2)
cv2.imshow("Image", img)
cv2.moveWindow("Image", 0, 0)
cv2.waitKey(0)
cv2.destroyAllWindows()
#Este for es para mostrar los nombres, lo reemplazo con los cuadritos.
cv2.imshow('Video', frame)
#Funcion para guardar la cara con un click
cv2.setMouseCallback('Video', save_face_click)
cv2.imshow('Video', frame)
#estas 2 lineas son para sacar la barra de la imagen
cv2.namedWindow('Video', cv2.WINDOW_NORMAL)
cv2.setWindowProperty('Video', cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
cv2.moveWindow('Video', -35, -20)
datos_ventana_video = cv2.getWindowImageRect(
'Video') #This will return a tuple of (x, y, w, h)
#Esto es la grilla con fondo negro y datos
cv2.imshow('grilla', grilla)
#estas 2 lineas son para sacar la barra de la imagen
cv2.namedWindow('grilla', cv2.WINDOW_NORMAL)
cv2.setWindowProperty('grilla', cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
#linea para mover la ventana y acomodarlas en la pantalla
cv2.moveWindow('grilla', datos_ventana_video[0] + datos_ventana_video[2],
-20)
def main():
"""main"""
# imgは"ndarray"型
img = cv2.imread('img/sample.jpg')
if img is None:
sys.exit("Could not read the image.")
# unsigned 8 bit format
img = cv2.cvtColor(img, cv2.CV_8U)
# img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
horizontal_line = "=============================================================="
print(horizontal_line)
print("Image Details:")
print(horizontal_line)
print("ndarray.ndim", end="\t\t")
print(img.ndim)
print("ndarray.shape", end="\t\t")
print(img.shape)
print("ndarray.size", end="\t\t")
print(img.size)
print("ndarray.dtype", end="\t\t")
print(img.dtype)
print("ndarray.itemsize", end="\t")
print(img.itemsize)
print("ndarray.data", end="\t\t")
print(img.data)
height, width, n_channels = img.shape
print("HEIGHT (y-axis): " + str(height) + ", WIDTH (x-axis): " +
str(width) + ", COLOR CHANNELS: " + str(n_channels))
print(horizontal_line)
user_input = input(
"Please press 'y' to see pixel information\n(or press any other key to skip): "
)
if user_input == 'y':
h_digit = len(str(height))
w_digit = len(str(width))
for y in range(height):
for x in range(width):
print(f"y = {y:>{h_digit}}, x = {x:>{w_digit}}, BGR = ",
end="")
print(img[y, x])
else:
print("Skipped.")
cv2.namedWindow("Original", cv2.WINDOW_AUTOSIZE)
cv2.moveWindow("Original", 0, 0)
cv2.imshow("Original", img)
cv2.namedWindow("Complementary Color", cv2.WINDOW_AUTOSIZE)
cv2.moveWindow("Complementary Color", 200, 0)
cv2.imshow("Complementary Color", complementary_color(img))
# 画像の左下を原点にするためにx軸を中心に反転
img = cv2.flip(img, 0)
print(horizontal_line)
prompt_str = """Select the Affine transformation to perform:
1 = scale about origin
2 = translate
3 = rotate about origin
4 = rotate about center
5 = skew in x direction
6 = skew in y direction
7 = reflect about x-axis
8 = reflect about y-axis
9 = reflect about y=x line
10 = reflect about origin
"""
while True:
user_input = input(prompt_str)
if user_input == '1':
affine_matrix = get_affine_tx_matrix_scale(2, 2)
break
elif user_input == '2':
affine_matrix = get_affine_tx_matrix_translate(150, 100)
break
elif user_input == '3':
affine_matrix = get_affine_tx_matrix_rotate_origin(45)
break
elif user_input == '4':
affine_matrix = get_affine_tx_matrix_rotate_center(
45, width / 2, height / 2)
break
elif user_input == '5':
affine_matrix = get_affine_tx_matrix_skew_x(15)
break
elif user_input == '6':
affine_matrix = get_affine_tx_matrix_skew_y(15)
break
elif user_input == '7':
affine_matrix = get_affine_tx_matrix_reflect_x()
break
elif user_input == '8':
affine_matrix = get_affine_tx_matrix_reflect_y()
break
elif user_input == '9':
affine_matrix = get_affine_tx_matrix_reflect_yx()
break
elif user_input == '10':
affine_matrix = get_affine_tx_matrix_reflect_origin()
break
else:
pass
print(horizontal_line)
print('Affine Transformation Matrix:')
print(affine_matrix)
print(horizontal_line)
print('Affine Transformation Matrix for cv2.warpAffine:')
# 画像の原点を座標軸の原点に移動
affine_matrix = get_affine_tx_matrix_translate(width,
height) @ affine_matrix
# cv2.warpAffineのMには(3, 3) のアフィン変換行列のうち、3行目を除いた (2, 3) の行列を指定
affine_2x3_matrix = np.delete(affine_matrix, 2, axis=0)
print(affine_2x3_matrix)
print(horizontal_line)
# 背景色（BGR）を指定可能
dst = cv2.warpAffine(img,
M=affine_2x3_matrix,
dsize=(width * 3, height * 3),
borderValue=(0, 255, 255))
dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
fig = plt.figure(figsize=[6.4, 4.8])
# 行、列、場所を設定
ax = fig.add_subplot(1, 1, 1)
# オリジナル画像の矩形を描画
rect = plt.Rectangle((0, 0), width, height, fill=0, edgecolor="gray")
ax.add_patch(rect)
# 原点をデフォルトの左上ではなく左下にして描画
# 左下の座標をマイナスに設定
ax.imshow(dst,
origin='lower',
extent=[-width, width * 2, -height, height * 2])
# plt.imshow(dst, origin='lower')
ax.set_title("Affine Transformation")
ax.set_xlabel("x-axis")
ax.set_ylabel("y-axis")
# グリッド線を灰色＋点線に変更
ax.grid(color="gray", ls=":")
# x軸、y軸を破線に設定
ax.axhline(y=0, color="gray", ls="--")
ax.axvline(x=0, color="gray", ls="--")
plt.show(block=False)
# matplotlibのバックエンドを確認
backend = matplotlib.get_backend()
# print(backend)
if backend == 'TkAgg':
# ウィンドウの位置を設定
# geometry (width x height + x-position + y-position)
mgr = plt.get_current_fig_manager()
mgr.window.wm_geometry("+0+200")
# geom = mgr.window.geometry()
# print(geom)
user_input = input("Press any key to exit: ")
# cv2.imwrite("output.png", img)
cv2.destroyAllWindows()
plt.clf()
plt.close('all')
return 0
def trace_ROI(App):
global parameters, i, drawingROI, drawingCL, selectedLine, ROImask, ROI, cut_lines
def updateSTrackbar(value):
global i
i = value
return
def initialize_mask(parameters):
# global parameters
# Compute the ROI mask once to keep it in memory
roi_norm_str = eval(str(parameters['ROI']))
if roi_norm_str:
roi_norm = np.asarray(roi_norm_str)
roi = (roi_norm * [
parameters['Width_Image'], parameters['Height_Image']
]).astype(int) # scale ROI with image size, round to nearest pixel
roi_mask = np.zeros(
(parameters['Height_Image'], parameters['Width_Image']),
dtype=np.uint8)
ROI_mask = cv2.drawContours(image=roi_mask,
contours=[roi],
contourIdx=0,
color=(255, 255, 255),
thickness=-1)
else:
roi = np.array([[0, 0]], dtype=np.int32) # ROI contour
ROI_mask = np.ones(
(parameters['Height_Image'], parameters['Width_Image']),
dtype=np.uint8)
return roi, ROI_mask
def initialize_cut_line(parameters):
# Builds the cut_lines array from the parameters
# Cut line specified in the parameters file in normalized coordinates
# (x1,y1), (x2,y2): read in, scale into image coordinates
# Get all parameter fields that begin with 'cutLine
cutline_keys = fnmatch.filter(parameters.keys(), 'Cut_Line*')
cut_lines = []
for key in cutline_keys:
cutLine_norm_str = eval(str(parameters[key]))
if cutLine_norm_str:
cutLine_norm = np.asarray(cutLine_norm_str)
cutLine = (cutLine_norm * [
parameters['Width_Image'], parameters['Height_Image']
]).astype(
int
) # scale cut line with image size, round to nearest pixel
else:
cutLine = np.array([[0, 0]],
dtype=np.int32) # default cut line
cut_lines.append(cutLine)
return cut_lines
def selectLine(event, x, y, flags, params):
global drawingROI, drawingCL, selectedLine, ROI, ROImask, cut_lines, parameters
if mode == 'ROI':
if drawingROI:
ROI[-1] = [x, y]
if event == cv2.EVENT_LBUTTONDOWN: # Left click
if not drawingROI:
ROI = np.array([[0, 0]], dtype=np.int32)
ROI[-1] = [x, y]
drawingROI = True
ROI = np.append(ROI, [[x, y]], axis=0)
if event == cv2.EVENT_RBUTTONDOWN: # Right click
# print('ROI (absolu) : \n{}\n'.format([[couple[0],couple[1]] for couple in ROI]))
ROI_rel = np.zeros_like(ROI, dtype=float)
ROI_rel[:,
0] = np.around(ROI[:, 0] / parameters['Width_Image'],
decimals=2)
ROI_rel[:,
1] = np.around(ROI[:, 1] / parameters['Height_Image'],
decimals=2)
strInfo = 'ROI : {}'.format([[couple[0], couple[1]]
for couple in ROI_rel])
print(strInfo + '\n')
try:
App.Info.set(strInfo)
except:
pass
drawingROI = False
ROImask = np.zeros(
(parameters['Height_Image'], parameters['Width_Image']),
dtype=np.uint8)
cv2.drawContours(ROImask, [ROI], 0, (255, 255, 255), -1)
parameters['ROI'] = str([[couple[0], couple[1]]
for couple in ROI_rel]) # + '\n'
if mode == 'CL':
if drawingCL:
cut_lines[selectedLine - 1][-1] = [x, y]
if event == cv2.EVENT_LBUTTONDOWN: # Left click
if not drawingCL:
cut_lines[selectedLine - 1] = np.array([[0, 0]],
dtype=np.int32)
cut_lines[selectedLine - 1][-1] = [x, y]
drawingCL = True
cut_lines[selectedLine - 1] = np.append(
cut_lines[selectedLine - 1], [[x, y]], axis=0)
if event == cv2.EVENT_RBUTTONDOWN:
# print('Ligne de coupe (absolu) : \n{}\n'.format([[couple[0],couple[1]] for couple in cut_line]))
cut_lineRel = np.zeros_like(cut_lines[selectedLine - 1],
dtype=float)
cut_lineRel[:,
0] = np.around(cut_lines[selectedLine - 1][:, 0] /
parameters['Width_Image'],
decimals=2)
cut_lineRel[:,
1] = np.around(cut_lines[selectedLine - 1][:, 1] /
parameters['Height_Image'],
decimals=2)
strInfo = 'Ligne de coupe #{} : {}'.format(
selectedLine,
[[couple[0], couple[1]] for couple in cut_lineRel])
print(strInfo + '\n')
try:
App.Info.set(strInfo)
except:
pass
drawingCL = False
parameters['Cut_Line' + str(selectedLine)] = str(
[[couple[0], couple[1]]
for couple in cut_lineRel]) # + '\n'
drawingROI = False # Tracé du ROI en cours
drawingCL = False # Tracé de la Cut Line en cours
selectedLine = 0 # CutLine selected
mode = 'ROI' # 'ROI' ou 'CL'
showHelp = True
lineColors = [(0, 0, 255), (255, 0, 0), (0, 255, 0),
(255, 0, 255)] # Red / Blue / Green / Violet
parameters = App.parameters.copy()
try:
videoPath = App.VideoPath.get()
excelPath = App.ExcelPath.get()
except:
videoPath = App.VideoPath
excelPath = App.ExcelPath
cap = cv2.VideoCapture(videoPath)
time.sleep(0.5)
if not cap.isOpened():
strInfo = 'Impossible d\'ouvrir : {}'.format(videoPath)
print(strInfo)
try:
App.Info.set(strInfo)
except:
pass
return
tots = cap.get(
cv2.CAP_PROP_FRAME_COUNT) # Set to a negative number for streaming
parameters['Width_Image'] = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
parameters['Height_Image'] = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
cv2.namedWindow('Video Player', cv2.WINDOW_NORMAL)
cv2.resizeWindow('Video Player', parameters['Width_Image'],
parameters['Height_Image'])
cv2.moveWindow('Video Player', 50, 50)
if tots > 0:
cv2.createTrackbar('S', 'Video Player', 0,
int(tots) - 1, updateSTrackbar)
cv2.setMouseCallback('Video Player', selectLine)
status = 'play'
isRunning = True
i = 1
cut_lines = initialize_cut_line(parameters)
ROI, ROImask = initialize_mask(parameters)
# Reading loop
while True:
try:
status = {
ord(' '): 'play/pause',
ord('r'): 'reset',
9: 'switch mode', # Tab
38: 'sel1', # &
49: 'sel1', # 1
233: 'sel2', # é
50: 'sel2', # 2
34: 'sel3', # "
51: 'sel3', # 3
39: 'sel4', # '
52: 'sel4', # 4
ord('h'): 'switch help',
-1: status,
27: 'exit'
}[cv2.waitKey(1)]
if (cv2.getWindowProperty('Video Player', 1)
== -1) & (i > 1): # The user closed the window
status = 'exit'
if status == 'play': # mettre en bas ?
i += 1
i %= tots
if tots > 0: # The two next lines slow down the code a lot !
cap.set(cv2.CAP_PROP_POS_FRAMES, int(i))
cv2.setTrackbarPos('S', 'Video Player', int(i))
_, im = cap.read()
overlay_ROI = im.copy() # for transparency
if np.size(ROI) > 2:
cv2.drawContours(overlay_ROI, [ROI], 0, (255, 255, 255), 2)
if not drawingROI:
overlay_ROI = cv2.bitwise_and(overlay_ROI,
overlay_ROI,
mask=ROImask)
cv2.addWeighted(overlay_ROI, 0.2, im, 1 - 0.2, 0, im)
overlay_CL = im.copy() # for transparency
for ii, cut_line in enumerate(cut_lines):
if np.size(cut_line) > 2:
cv2.polylines(overlay_CL, [cut_line], 0, lineColors[ii], 3)
cv2.addWeighted(overlay_CL, 0.8, im, 1 - 0.8, 0, im)
if mode == 'ROI':
txt = 'Selection du ROI'
elif mode == 'CL':
txt = 'Selection de la ligne de coupe #{}'.format(selectedLine)
textdim, _ = cv2.getTextSize(txt, cv2.FONT_HERSHEY_DUPLEX, 0.5, 1)
cv2.rectangle(im, (5 - 1, 20 + 2),
(5 + textdim[0] + 1, 20 - textdim[1]),
(255, 255, 255), -1)
cv2.putText(im, txt, (5, 20), cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
dy = 20
if showHelp:
if mode == 'ROI':
txt = 'r : remettre a zero le ROI'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 5 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
if not drawingROI:
txt = 'clic gauche : selectionner le premier point du ROI'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 4 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
elif drawingROI:
txt = 'clic gauche : selectionner le point suivant du ROI'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 4 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'clic droit : selectionner le dernier point du ROI'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 3 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'Tab : passer a la selection de la ligne de coupe'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 2 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
elif mode == 'CL':
txt = '1-4 : selectionner la ligne de coupe #1-4'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 6 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'r : remettre a zero la ligne de coupe #{}'.format(
selectedLine)
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 5 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
if not drawingCL:
txt = 'clic gauche : selectionner le premier point de la ligne de coupe'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 4 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
elif drawingCL:
txt = 'clic gauche : selectionner le point suivant de la ligne de coupe'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 4 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'clic droit : selectionner le dernier point de la ligne de coupe'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 3 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'Tab : passer a la selection du ROI'
cv2.putText(im, txt,
(5, parameters['Height_Image'] - 2 * dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'Esc : quitter'
cv2.putText(im, txt, (5, parameters['Height_Image'] - dy),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
txt = 'h : cacher l\'aide'
cv2.putText(im, txt, (5, parameters['Height_Image'] - 1),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
else:
txt = 'h : montrer l\'aide'
cv2.putText(im, txt, (5, parameters['Height_Image'] - 1),
cv2.FONT_HERSHEY_DUPLEX, 0.5, 1, 1)
cv2.imshow('Video Player', im)
if status == 'play':
continue
elif status == 'stay':
i = int(cv2.getTrackbarPos('S', 'Video Player'))
elif status == 'play/pause':
status = 'stay' if isRunning else 'play'
isRunning = not isRunning
elif status == 'reset':
if mode == 'ROI':
parameters['ROI'] = None
ROI, ROImask = initialize_mask(parameters)
elif mode == 'CL':
parameters['Cut_Line' + str(selectedLine)] = None
cut_lines = initialize_cut_line(parameters)
status = 'play' if isRunning else 'stay'
elif status == 'switch mode':
if mode == 'ROI':
mode = 'CL'
selectedLine = 1
else:
mode = 'ROI'
selectedLine = 0
status = 'play' if isRunning else 'stay'
elif status == 'sel1':
if not drawingCL:
selectedLine = 1
mode = 'CL'
status = 'play' if isRunning else 'stay'
elif status == 'sel2':
if not drawingCL:
selectedLine = 2
mode = 'CL'
status = 'play' if isRunning else 'stay'
elif status == 'sel3':
if not drawingCL:
selectedLine = 3
mode = 'CL'
status = 'play' if isRunning else 'stay'
elif status == 'sel4':
if not drawingCL:
selectedLine = 4
mode = 'CL'
status = 'play' if isRunning else 'stay'
elif status == 'switch help':
showHelp = not showHelp
status = 'play' if isRunning else 'stay'
elif status == 'exit':
answer = messagebox.askquestion(
message=
'Voulez vous enregistrer les modifications dans le fichier de paramètres ?',
type='yesnocancel')
if answer == 'cancel':
status = 'play' if isRunning else 'stay'
if answer == 'yes':
App.parameters = parameters # Ecraser les anciens paramètres avec les nouveaux
df = pandas.read_excel(excelPath, header=None)
df.loc[App.comboBoxID.current() + 1, 9] = parameters['ROI']
for ii in range(1, 5):
df.loc[App.comboBoxID.current() + 1,
9 + ii] = parameters['Cut_Line' + str(ii)]
try:
with pandas.ExcelWriter(excelPath) as writer:
df.to_excel(writer,
header=None,
index=False,
sheet_name='All')
writer.save
except PermissionError:
messagebox.showerror(
title='Erreur',
message=
'Impossible d\'enregistrer les modifications, vérifier que le fichier n\'est pas utilisé par une autre application'
)
status = 'play' if isRunning else 'stay'
continue
break
if answer == 'no':
break
except KeyError as e:
print("Invalid Key \"{:s}: {:d}\" was pressed".format(
chr(e.args[0]), e.args[0]))
cv2.destroyAllWindows()
cap.release()
return
left_camera_matrix, left_distortion, right_camera_matrix, right_distortion,
size, R, T)
# 计算更正map
left_map1, left_map2 = cv2.initUndistortRectifyMap(left_camera_matrix,
left_distortion, R1, P1,
size, cv2.CV_16SC2)
right_map1, right_map2 = cv2.initUndistortRectifyMap(right_camera_matrix,
right_distortion, R2, P2,
size, cv2.CV_16SC2)
cv2.namedWindow("left")
cv2.namedWindow("right")
cv2.namedWindow("leftt")
cv2.namedWindow("rightt")
cv2.namedWindow("depth")
cv2.moveWindow("left", 0, 0)
cv2.moveWindow("right", 640, 0)
cv2.moveWindow("leftt", 0, 480)
cv2.moveWindow("rightt", 640, 480)
#cv2.createTrackbar("num", "depth", 0, 10, lambda x: None)
#cv2.createTrackbar("blockSize", "depth", 5, 255, lambda x: None)
videoIn = cv2.VideoCapture(1, cv2.CAP_DSHOW)
videoIn.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
videoIn.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
#cmera2 = cv2.VideoCapture(2)
def draw_min_rect(img, cnt, depth): # conts = contours
img = np.copy(img)
x, y, w, h = cv2.boundingRect(cnt)
