def add_mrz_overlay(img: np.ndarray,
text: str,
times: int,
width: float,
bottom: bool = False) -> np.ndarray:
line_spacing = 1.5
font = cv2.FONT_HERSHEY_SIMPLEX
font_color = (0, 0, 0)
line_type = 2
text_width_s1, _ = cv2.getTextSize(text, font, 1, line_type)[0]
font_scale = int(img.shape[1] * width) / text_width_s1
text_width, text_height = cv2.getTextSize(text, font, font_scale,
line_type)[0]
if bottom:
coords = (img.shape[1] - text_width) // 2, int(img.shape[0] -
text_height * times *
line_spacing)
else:
coords = (img.shape[1] - text_width) // 2, (img.shape[0] +
text_height) // 2
for i in range(times):
cv2.putText(
img,
text,
(coords[0], coords[1] + int(line_spacing * i * text_height)),
font,
font_scale,
font_color,
line_type,
)
return img
def setLabel(image, str, contour):
(text_width, text_height), baseline = cv2.getTextSize(str, cv2.FONT_HERSHEY_SIMPLEX, 0.7, 1)
x, y, width, height = cv2.boundingRect(contour)
pt_x = x+int((width-text_width)/2)
pt_y = y+int((height + text_height)/2)
cv2.rectangle(image, (pt_x, pt_y+baseline), (pt_x+text_width, pt_y-text_height), (200,200,200), cv2.FILLED)
cv2.putText(image, str, (pt_x, pt_y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,0), 1, 8)
def plot_one_box(box, img, color=None, label=None, line_thickness=None):
"""Plots one bounding box on image img
:param box: [x1, y1, x2, y2]
:param img: image
:param color: True or Float
:param label: label
:param line_thickness: line_thickness
:return: image with bounding box
"""
line_thick = line_thickness or round(
0.002 * (img.shape[0] + img.shape[1]) / 2) + 1 # line/font thickness
color = color or [random.randint(0, 255) for _ in range(3)]
pt1, pt2 = (int(box[0]), int(box[1])), (int(box[2]), int(box[3]))
cv2.rectangle(img,
pt1,
pt2,
color,
thickness=line_thick,
lineType=cv2.LINE_AA)
if label:
font_thick = max(line_thick - 1, 1) # font thickness
t_size = cv2.getTextSize(label,
0,
fontScale=line_thick / 3,
thickness=font_thick)[0]
pt2 = pt1[0] + t_size[0], pt1[1] - t_size[1] - 3
cv2.rectangle(img, pt1, pt2, color, -1, cv2.LINE_AA) # filled
cv2.putText(img,
label, (pt1[0], pt1[1] - 2),
0,
line_thick / 3, [225, 255, 255],
hickness=font_thick,
lineType=cv2.LINE_AA)
def draw_text(img,
text,
font=cv2.FONT_HERSHEY_COMPLEX_SMALL,
position=(10, 10),
font_scale=0.6,
font_thickness=1,
text_color=(0, 0, 0),
text_color_bg=(255, 255, 255),
alignment="center"):
"""
draws text in a coloured rectangle
"""
x, y = [int(x) for x in position]
text_size, _ = cv2.getTextSize(text, font, font_scale, font_thickness)
# space
text_w, text_h = [int(x) for x in text_size]
cv2.rectangle(img,
position, (x + text_w, y + text_h + 5),
text_color_bg,
-1,
lineType=cv2.LINE_AA)
cv2.putText(img,
text, (x, y + text_h),
font,
font_scale,
text_color,
font_thickness,
lineType=cv2.LINE_AA)
return img
def write_solution(image, empty_boxes, solved):
# Write grid on image
side = image.shape[0] // 9
for i in range(9):
for j in range(9):
if (empty_boxes[i][j] != 1):
continue
text = str(solved[i][j])
offset = 0
font = cv2.FONT_HERSHEY_SIMPLEX
(text_height, text_width), baseLine = cv2.getTextSize(text,
font,
fontScale=1,
thickness=3)
font_scale = 0.4 * side / max(text_height, text_width)
text_height *= font_scale
text_width *= font_scale
bottom_left_corner_x = side * j + math.floor(
(side - text_width) / 2) + offset
bottom_left_corner_y = side * (i + 1) - math.floor(
(side - text_height) / 2) + offset
image = cv2.putText(image,
text,
(bottom_left_corner_x, bottom_left_corner_y),
font,
font_scale, (0, 255, 0),
thickness=3,
lineType=cv2.LINE_AA)
return image
def generate_solution_grid_img(solved_grid_exc_predicted, grid_img):
FONT = cv2.FONT_HERSHEY_DUPLEX
CELL_WIDTH = grid_img.shape[1] // 9
OFFSET = CELL_WIDTH // 15
# FONT_SCALE = get_optimal_font_scale(CELL_WIDTH)
FONT_SCALE = CELL_WIDTH / 10 / 4
transparent_img = np.zeros((grid_img.shape[1], grid_img.shape[0]),
np.uint8)
(text_height, text_width), _ = cv2.getTextSize("0",
FONT,
fontScale=FONT_SCALE,
thickness=1)
for row in range(9):
for column in range(9):
if solved_grid_exc_predicted[row][column] == 0:
continue
cell_num_str = str(solved_grid_exc_predicted[row][column])
bottom_left_x = CELL_WIDTH * column + (CELL_WIDTH -
text_width) // 2 + OFFSET
bottom_left_y = CELL_WIDTH * (row + 1) - (
CELL_WIDTH - text_height) // 2 + OFFSET
transparent_img = cv2.putText(
transparent_img,
cell_num_str, (int(bottom_left_x), int(bottom_left_y)),
FONT,
FONT_SCALE,
255,
thickness=1,
lineType=cv2.LINE_AA)
return transparent_img
def object_and_speed(self, filename, objects, frame, matrix, ratio_width):
"""
Функция осуществляет отслеживание, идентификацию,
подсчет скорости объектов и вывод инфо в заданный файл
"""
# Добавление центроидов каждую секунду (или TIME) в упорядоченный словарь для нахождения скорости
if self.frame_count % (self.skip_frames * TIME) < 1:
self.centroids.save_centroids(objects)
# цикл по отслеживанию объектов
for (idx, (object_id, centroid)) in enumerate(objects.items()):
# проверить, существует ли отслеживаемый объект для текущего идентификатора объекта
add_object = self.centroids.track.get(object_id, None)
# если не существует отслеживаемого объекта, создаем его
if add_object is None:
add_object = TrackableObject(object_id, centroid)
else:
add_object.centroids.append(centroid)
if not add_object.counted: # проверяем, был ли объект подсчитан
add_object.counted = True
self.centroids.track[object_id] = add_object
self.people_count = int(object_id + 1)
cv2.putText(frame, str(object_id + 1),
(centroid[0] - 10, centroid[1] - 10),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
cv2.circle(frame, (centroid[0], centroid[1]), 5, (0, 0, 255), -1)
# TODO: лучше настроить отслеживание объектов
if self.frame_count % (self.skip_frames * TIME) < 1 or \
object_id not in self.centroids.speed:
self.centroids.search_delta_speed(object_id, matrix,
ratio_width)
if self.frame_count % (self.skip_frames * TIME) < 1:
self.centroids.save_speed(
filename, round(self.frame_count / self.skip_frames),
object_id, self.centroids.speed[object_id])
speed_label = str(
"%d" % self.centroids.speed[object_id]) + " km/hr"
speed_label_size, base_line = cv2.getTextSize(
speed_label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
y_left_bottom = max(centroid[1], speed_label_size[1])
cv2.rectangle(
frame,
(centroid[0] + 50, centroid[1] - speed_label_size[1] - 100),
(centroid[0] - speed_label_size[1] - 35,
y_left_bottom + base_line - 100), (255, 255, 255), cv2.FILLED)
cv2.putText(frame, speed_label,
(centroid[0] - 50, y_left_bottom - 100),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0))
info = "time {}: ID {}: {}".format(
round(self.frame_count / self.skip_frames), int(object_id + 1),
speed_label)
cv2.putText(frame, info, (int(frame.shape[1] / 2), frame.shape[0] -
((idx * 50) + 50)),
cv2.FONT_HERSHEY_SIMPLEX, 1.2, (0, 0, 0), 1,
cv2.LINE_AA)
def get_optimal_font_scale(width):
for scale in reversed(range(0, 60, 1)):
textSize = cv2.getTextSize("0",
fontFace=cv2.FONT_HERSHEY_DUPLEX,
fontScale=scale / 10,
thickness=1)
new_width = textSize[0][0]
if (new_width <= width):
return scale / 10 / 2
return 1
def _tagPhoto(opencvImage, tag):
font = cv.FONT_HERSHEY_DUPLEX
textsize = cv.getTextSize(tag, font, 1, 2)[0]
cv.rectangle(opencvImage, (10 - 10, 40 + 10),
(10 + textsize[0] + 10, 40 + 10 - textsize[1] - 20),
(0, 0, 0), -1)
cv.putText(opencvImage, tag, (10, 40), font, 1, (0, 255, 255), 2,
cv.LINE_AA)
def draw_predict(bss, strss, img, num):
'''绘制预测框'''
j = 0
for bs in bss:
width = 640
height = 480
x = [0 for i in range(9)]
y = [0 for i in range(9)]
a = np.arange(18)
corners2D_gt = a.reshape(9, 2)
for i in range(9):
x[i] = int(bs[i][0] * width)
y[i] = int(bs[i][1] * height)
cv2.circle(img, (x[i], y[i]), 1, (255, 0, 255), -1)
string = str(i)
cv2.putText(
img, string, (x[i], y[i]), cv2.FONT_HERSHEY_COMPLEX, 0.5, (255, 0, 255), 1)
corners2D_gt[i, 0] = x[i]
corners2D_gt[i, 1] = y[i]
# 输出物品名称和识别率
text = strss[j][0] + ' ' + strss[j][1]
size = cv2.getTextSize(text, cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.8, 1)
if x[1] + size[0][0] <= width and y[1] - size[0][1] > 0:
tx = x[1]
ty = y[1]
else:
tx = x[8]
ty = y[8]
cv2.rectangle(img, (tx - 2, ty + 2), (tx + 2 +
size[0][0], ty - 2 - size[0][1]), (255, 255, 0), cv2.FILLED)
cv2.putText(img, text, (tx, ty),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.8, (0, 0, 0))
cv2.line(img, (x[1], y[1]), (x[2], y[2]), (255, 255, 0), 2)
cv2.line(img, (x[2], y[2]), (x[4], y[4]), (255, 255, 0), 2)
cv2.line(img, (x[3], y[3]), (x[4], y[4]), (255, 255, 0), 2)
cv2.line(img, (x[1], y[1]), (x[3], y[3]), (255, 255, 0), 2)
cv2.line(img, (x[1], y[1]), (x[5], y[5]), (255, 255, 0), 2)
cv2.line(img, (x[2], y[2]), (x[6], y[6]), (255, 255, 0), 2)
cv2.line(img, (x[3], y[3]), (x[7], y[7]), (255, 255, 0), 2)
cv2.line(img, (x[4], y[4]), (x[8], y[8]), (255, 255, 0), 2)
cv2.line(img, (x[5], y[5]), (x[6], y[6]), (255, 255, 0), 2)
cv2.line(img, (x[5], y[5]), (x[7], y[7]), (255, 255, 0), 2)
cv2.line(img, (x[6], y[6]), (x[8], y[8]), (255, 255, 0), 2)
cv2.line(img, (x[7], y[7]), (x[8], y[8]), (255, 255, 0), 2)
j += 1
# 保存照片
cv2.imwrite('JPEGImages/predict' + str(num) + '.jpg', img)
def draw_boxes(x, img, classes):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
cls = int(x[-1])
label = "{0}".format(classes[cls])
color = (0, 0, 255)
cv2.rectangle(img, c1, c2, color, 2)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1, 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2, color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4),
cv2.FONT_HERSHEY_PLAIN, 1, [225, 255, 255], 1)
return img
def find_font_params(top_text, bot_text):
FONT = cv2.FONT_HERSHEY_COMPLEX
FONT_SCALE = 1.5
FONT_THICKNESS = 2
(top_label_width, top_label_height), _ = cv2.getTextSize(top_text,
FONT,
FONT_SCALE,
FONT_THICKNESS)
(bot_label_width, bot_label_height), _ = cv2.getTextSize(bot_text,
FONT,
FONT_SCALE,
FONT_THICKNESS)
max_width = max([top_label_width, bot_label_width])
font = {
'font': FONT,
'scale': FONT_SCALE,
'thickness': FONT_THICKNESS
}
return font
def create_and_write_meme(partitioned_text):
my_path = os.path.abspath(os.path.dirname(__file__))
pic_path = os.path.join(my_path, 'spongebob.jpg')
# height, width, channels
img = cv2.imread(pic_path)
img_height, img_width, _ = img.shape
print('[!] Use num characters to determine font')
# def find_font_size()
top_text, bot_text = partitioned_text.split("|SPONGEPIC|")
# TODO: swap font type -> IMPACT, use Dank Learnings meme writer maybe?
font = find_font_params(top_text, bot_text)
label_color = (255, 255, 255) #255 #(0, 0, 0)
# TODO: add black outline to text
(top_label_width, top_label_height), _ = cv2.getTextSize(top_text,
font['font'],
font['scale'],
font['thickness'])
top_center = top_label_width / 2
top_left = int((img_width/2) - top_center)
top_top = int((img_height * .05) + top_label_height) # 5% down
(bot_label_width, bot_label_height), _ = cv2.getTextSize(bot_text,
font['font'],
font['scale'],
font['thickness'])
bot_center = bot_label_width / 2
bot_left = int((img_width/2) - bot_center)
bot_bot = int((img_height * .95) - bot_label_height) # 5% down
label_color = (255, 255, 255) #255 #(0, 0, 0)
cv2.putText(img, top_text, (top_left, top_top), font['font'], font['scale'], label_color, thickness=font['thickness']S)
cv2.putText(img, bot_text, (bot_left, bot_bot), font['font'], font['scale'], label_color, thickness=font['thickness'])
cv2.imwrite(os.path.join(os.getcwd(), 'meme.jpg'), img)
def crea_video(inizio_dt, fine_dt, percorso, fps, grayscale, gif):
if percorso[-1] != "/":
percorso = percorso + "/"
frame_width = 1280
frame_height = 720
out = cv2.VideoWriter('video_out.mp4', cv2.VideoWriter_fourcc(*'mp4v'),
fps, (frame_width, frame_height))
vettore_file_data = {}
for filename in os.listdir(percorso):
exif_dict = piexif.load(percorso + filename)
data = exif_dict["Exif"][36867].decode()
data_dt = datetime.datetime.strptime(data, "%Y:%m:%d %H:%M:%S")
if data_dt >= inizio_dt and data_dt <= fine_dt:
vettore_file_data[data_dt] = filename
for key in sorted(vettore_file_data):
if (grayscale == 1):
img = cv2.imread(percorso + vettore_file_data[key],
cv2.IMREAD_GRAYSCALE)
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
else:
img = cv2.imread(percorso + vettore_file_data[key],
cv2.IMREAD_ANYCOLOR)
# shape restituisce (altezza,larghezza,num_canali)
#calcolo nuove dimensioni
if img.shape[0] != frame_height or img.shape[1] != frame_width:
frame = ridimensiona(img, frame_height, frame_width)
else:
frame = img
dimtesto = cv2.getTextSize(str(key), cv2.FONT_HERSHEY_SIMPLEX, 1,
1)[0] # (larghezza,altezza)
altezza_rect = dimtesto[1] + 10
cv2.rectangle(frame, (0, frame_height),
(frame_width, frame_height - altezza_rect), (0, 0, 0),
-1)
cv2.putText(frame, str(key),
(int((frame_width - dimtesto[0]) / 2),
int(frame_height - (altezza_rect - dimtesto[1]) / 2)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1,
cv2.LINE_AA)
out.write(frame)
out.release()
if (gif == 1):
clip = VideoFileClip("video_out.mp4")
clip.write_gif("video_out.gif")
def drawAllResult(self, image):
"""Draw the detection result on image"""
for facebox, conf in self.detectionResult:
cv2.rectangle(image, (facebox[0], facebox[1]),
(facebox[2], facebox[3]), (0, 255, 0))
label = "face: %.4f" % conf
labelSize, baseLine = cv2.getTextSize(label,
cv2.FONT_HERSHEY_SIMPLEX,
0.5, 1)
cv2.rectangle(image, (facebox[0], facebox[1] - labelSize[1]),
(facebox[0] + labelSize[0], facebox[1] + baseLine),
(0, 255, 0), cv2.FILLED)
cv2.putText(image, label, (facebox[0], facebox[1]),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0))
def put_text_right(img, text):
if text is None:
return None
text_size = cv2.getTextSize(text,
FONT,
fontScale=FONT_SCALE,
thickness=FONT_THICKNESS)[0]
text_x = int(ICON_RIGHT_X1 + ((ICON_WIDTH - text_size[0]) / 2))
text_y = int(ICON_RIGHT_Y1 + ICON_HEIGHT + text_size[1] + 20)
cv2.putText(img,
text, (text_x, text_y),
fontFace=FONT,
fontScale=FONT_SCALE,
color=(147, 58, 31),
thickness=FONT_THICKNESS,
lineType=cv2.LINE_AA)
def show_confidence(result, img, color):
for box in result:
text = box.object_class
(text_width, text_height) = cv2.getTextSize(text,
font,
fontScale=fontScale,
thickness=1)[0]
text_offset_x = box.topleft_x
text_offset_y = box.topleft_y
# make the coords of the box with a small padding of two pixels
box_coords = ((text_offset_x, text_offset_y),
(text_offset_x + text_width - 2,
text_offset_y - text_height - 2))
cv2.rectangle(img, box_coords[0], box_coords[1], color, cv2.FILLED)
cv2.putText(img, text, (box.topleft_x, box.topleft_y), font, fontScale,
fontColor, lineType)
def draw_prediction(self, image, class_id, confidence, x1, y1, x2, y2):
image_height, image_width, _ = image.shape
fontSize = round(image_height / 1024)
label = (str(self.classes[class_id]) + " " + str(round(confidence * 100)) + "%").upper()
color = self.colors[class_id]
x1 = max(x1, 0)
y1 = max(y1, 0)
cv2.rectangle(image, (x1, y1), (x2, y2), color, fontSize)
(textWidth, textHeight), baseline = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, fontSize, fontSize)
if y1 - textHeight <= 0:
y1 = y1 + textHeight
cv2.rectangle(image, (x1, y1), (x1 + textWidth, y1 - textHeight), color, -1)
cv2.putText(image, label, (x1, y1), cv2.FONT_HERSHEY_SIMPLEX, fontSize, (0, 0, 0), fontSize)
else:
cv2.rectangle(image, (x1, y1), (x1 + textWidth, y1 - textHeight), color, -1)
cv2.putText(image, label, (x1, y1), cv2.FONT_HERSHEY_SIMPLEX, fontSize, (0, 0, 0), fontSize)
def put_end_text(img, text):
if text is None:
return None
text_size = cv2.getTextSize(text,
FONT,
fontScale=FONT_SCALE,
thickness=FONT_THICKNESS)[0]
text_x = int((WINDOW_WIDTH / 2) - (text_size[0] / 2))
text_y = ICON_CENTER_Y1 + ICON_HEIGHT + text_size[1] + 90
cv2.putText(img,
text, (text_x, text_y),
fontFace=FONT,
fontScale=FONT_SCALE,
color=(147, 58, 31),
thickness=FONT_THICKNESS,
lineType=cv2.LINE_AA)
def text_height(self, text, **kwargs):
overlay_font = \
getattr( cv2, 'FONT_{}'.format( kwargs['overlayfont'] ) ) \
if 'overlayfont' in kwargs else cv2.FONT_HERSHEY_SIMPLEX
overlay_scale = float( kwargs['overlayscale'] ) \
if 'overlayscale' in kwargs else 0.5
overlay_thickness = int( kwargs['overlaythickness'] ) \
if 'overlaythickness' in kwargs else 1
size = cv2.getTextSize(text,
fontFace=overlay_font,
fontScale=overlay_scale,
thickness=overlay_thickness * 4)
return size[0][1]
def draw_bboxes(img, bbox, identities=None, offset=(0, 0)):
for i, box in enumerate(bbox):
x1, y1, x2, y2 = [int(i) for i in box]
x1 += offset[0]
x2 += offset[0]
y1 += offset[1]
y2 += offset[1]
# box text and bar
id = int(identities[i]) if identities is not None else 0
color = COLORS_10[id % len(COLORS_10)]
label = '{}{:d}'.format("", id)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2, 2)[0]
cv2.rectangle(img, (x1, y1), (x2, y2), color, 3)
cv2.rectangle(img, (x1, y1), (x1 + t_size[0] + 3, y1 + t_size[1] + 4),
color, -1)
cv2.putText(img, label, (x1, y1 + t_size[1] + 4),
cv2.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)
def plot_one_box(x, img, color=None, label=None, line_thickness=None):
# Plots one bounding box on image img
tl = line_thickness or round(
0.002 * (img.shape[0] + img.shape[1]) / 2) + 1 # line/font thickness
color = color or [random.randint(0, 255) for _ in range(3)]
c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3]))
cv2.rectangle(img, c1, c2, color, thickness=tl, lineType=cv2.LINE_AA)
if label:
tf = max(tl - 1, 1) # font thickness
t_size = cv2.getTextSize(label, 0, fontScale=tl / 3, thickness=tf)[0]
c2 = c1[0] + t_size[0], c1[1] - t_size[1] - 3
cv2.rectangle(img, c1, c2, color, -1, cv2.LINE_AA) # filled
cv2.putText(img,
label, (c1[0], c1[1] - 2),
0,
tl / 3, [225, 255, 255],
thickness=tf,
lineType=cv2.LINE_AA)
def drawPred(class_id, confidence, left, top, right, bottom, car_num):
"""
根据预测结果在图片上画出矩形框
:param class_id:
:param confidence:
:param left:
:param top:
:param right:
:param bottom:
:return:
"""
cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 3)
#label = "{0}: {1:.4f},count={2}".format(class_names[class_id], confidence,count_car)
label = "{0}".format(car_num)
labelSize, _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 1, 2)
top = max(top, labelSize[1])
cv2.putText(frame, label, (left, top), cv2.FONT_HERSHEY_SIMPLEX, 1,
(0, 0, 0), 2)
def addCV2Text(text):
from cv2 import cv2
font = cv2.FONT_HERSHEY_SIMPLEX
# Work out how big we will need to make an array to display the text, line by line.
lineCount = 0
maxHeight = 0
maxWidth = 0
for line in enumerate(text.split('\n')):
lineCount += 1
s = line[1]
(width, height), baseline = cv2.getTextSize(s,
font,
fontScale=1,
thickness=2)
print(height, width, baseline, s)
maxHeight = max(maxHeight, height)
maxWidth = max(maxWidth, width)
textImgArray = newImageArray((maxHeight + 20) * lineCount, maxWidth + 20)
print('Lines = ', lineCount)
print('Maxh, Maxw =', maxHeight, maxWidth)
print('Shape is', textImgArray.shape)
# Line-by-line add the text to the array
for line in enumerate(
text.split('\n')): # line is compound: (line-number, text)
i = line[0]
text_offset_x = 10
text_offset_y = i * (maxHeight + 20)
cv2.putText(textImgArray,
line[1], (text_offset_x, text_offset_y),
font,
fontScale=1,
thickness=1,
color=(0, 0, 0))
showImage('CV2Text', textImgArray)
return textImgArray
def draw_box(self):
boxes = self.get_boxes(self.frame_no)
for box in boxes:
x1, y1, x2, y2 = box[0], box[1], box[2], box[3]
id = box[4]
label = f"{id}"
if id in self.window.mark_map:
color = (0, 255, 0)
t = self.window.mark_map[id]
if t[0] != -1:
label += f" {self.window.names[t[0]]}({self.window.names[t[1]]})"
elif self.window.identity == id:
color = (255, 0, 0)
else:
color = (0, 0, 255)
# print(color)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2, 2)[0]
cv2.rectangle(self.frame, (x1, y1), (x2, y2), color, 3)
cv2.rectangle(self.frame, (x1, y1), (x1 + t_size[0] + 3, y1 + t_size[1] + 4), color, -1)
cv2.putText(self.frame, label, (x1, y1 + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)
def put_countdown_text(img, eye_position, count):
countdown = str(
round((SELECTED_CYCLE_THRESHOLD * CYCLE_TIME) - (count * CYCLE_TIME),
1))
text_size = cv2.getTextSize(countdown,
FONT,
fontScale=FONT_SCALE,
thickness=FONT_THICKNESS)[0]
text_x = 20 # left
if eye_position == EYE_POSITION_RIGHT:
text_x = WINDOW_WIDTH - text_size[0] - 20
elif eye_position == EYE_POSITION_CENTER:
text_x = int((WINDOW_WIDTH / 2) - (text_size[0] / 2))
text_y = text_size[1] + 100
cv2.putText(img,
countdown, (text_x, text_y),
fontFace=FONT,
fontScale=FONT_SCALE,
color=(147, 58, 31),
thickness=FONT_THICKNESS,
lineType=cv2.LINE_AA)
def make_video(begin, end, path, fps, grayscale, frame_width, frame_height,
name_video, client, bucket):
path_list = retrieve_photos(begin, end, path, client, bucket)
out = cv2.VideoWriter('/tmp/{}.avi'.format(name_video),
cv2.VideoWriter_fourcc(*'MJPG'), fps,
(frame_width, frame_height))
for photo_file in path_list:
if grayscale == 1:
img = cv2.imread(photo_file, cv2.IMREAD_GRAYSCALE)
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
elif grayscale == 0:
img = cv2.imread(photo_file, cv2.IMREAD_ANYCOLOR)
# shape restituisce (altezza,larghezza,num_canali)
#calcolo nuove dimensioni
if img.shape[0] != frame_height or img.shape[1] != frame_width:
frame = resize_frame(img, frame_height, frame_width)
else:
frame = img
# Aggiunta della data
#la data deve essere trasformata in un formato leggibile
date = photo_file.split('/')[-1].split('.')[0]
date = '{}-{}-{} {}:{}'.format(date[0:4], date[4:6], date[6:8],
date[8:10], date[10:])
dimtesto = cv2.getTextSize(date, cv2.FONT_HERSHEY_SIMPLEX, 1,
1)[0] # (larghezza,altezza)
altezza_rect = dimtesto[1] + 10
cv2.rectangle(frame, (0, frame_height),
(frame_width, frame_height - altezza_rect), (0, 0, 0),
-1)
cv2.putText(frame, date,
(int((frame_width - dimtesto[0]) / 2),
int(frame_height - (altezza_rect - dimtesto[1]) / 2)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1,
cv2.LINE_AA)
out.write(frame)
out.release()
return path_list[-1]
def drawPredCar(car):
"""
根据预测结果在图片上画出矩形框
"""
if car.lane_num == 1:
rectcolor = (0, 255, 0) #绿
elif car.lane_num == 2:
rectcolor = (255, 0, 0) #蓝
elif car.lane_num == 3:
rectcolor = (0, 255, 255) #黄
elif car.lane_num == 4:
rectcolor = (255, 0, 255)
else: #car.lane_num==-1: #错误
rectcolor = (0, 0, 255)
cv2.rectangle(frame, (car.left, car.top),
(car.left + car.width, car.top + car.height), rectcolor, 3)
#label = "{0}: {1:.4f},count={2}".format(class_names[class_id], confidence,count_car)
label = "{0},y={1:.1f},x={2:.1f}".format(car.car_num, car.dy, car.dx)
labelSize, _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 1, 2)
#top = max(car.top, labelSize[1])
cv2.putText(frame, label, (int(car.x_center), car.top + car.height),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
def write_soln_on_image(image, grid, user_grid):
# Write grid on the image
SIZE = 9
width = image.shape[1] // 9
height = image.shape[0] // 9
for i in range(SIZE):
for j in range(SIZE):
if (user_grid[i][j] != 0): # If already filled
continue
# Convert to string
text = str(grid[i][j])
off_set_x = width // 15
off_set_y = height // 15
font = cv2.FONT_HERSHEY_SIMPLEX
(text_height, text_width), baseline = cv2.getTextSize(text,
font,
fontScale=1,
thickness=3)
font_scale = 0.6 * min(width, height) / max(
text_height, text_width)
text_height *= font_scale
text_width *= font_scale
bottom_left_corner_x = width * j + math.floor(
(width - text_width) / 2) + off_set_x
bottom_left_corner_y = height * (i + 1) - math.floor(
(height - text_height) / 2) + off_set_y
# Line_AA minimizes distortion in the text drawn
image = cv2.putText(image,
text,
(bottom_left_corner_x, bottom_left_corner_y),
font,
font_scale, (0, 255, 0),
thickness=3,
lineType=cv2.LINE_AA)
return image
def writeLicensePlateCharsOnImage(imgOriginalScene, licPlate):
ptCenterOfTextAreaX = 0
ptCenterOfTextAreaY = 0
ptLowerLeftTextOriginX = 0
ptLowerLeftTextOriginY = 0
sceneHeight, sceneWidth, sceneNumChannels = imgOriginalScene.shape
plateHeight, plateWidth, plateNumChannels = licPlate.imgPlate.shape
intFontFace = cv2.FONT_HERSHEY_SIMPLEX
fltFontScale = float(plateHeight) / 30.0
intFontThickness = int(round(fltFontScale * 1.5))
textSize, baseline = cv2.getTextSize(licPlate.strChars, intFontFace,
fltFontScale, intFontThickness)
((intPlateCenterX, intPlateCenterY), (intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg) = licPlate.rrLocationOfPlateInScene
intPlateCenterX = int(intPlateCenterX)
intPlateCenterY = int(intPlateCenterY)
ptCenterOfTextAreaX = int(intPlateCenterX)
if intPlateCenterY < (sceneHeight * 0.75):
ptCenterOfTextAreaY = int(round(intPlateCenterY)) + int(
round(plateHeight * 1.6))
else:
ptCenterOfTextAreaY = int(round(intPlateCenterY)) - int(
round(plateHeight * 1.6))
textSizeWidth, textSizeHeight = textSize
ptLowerLeftTextOriginX = int(ptCenterOfTextAreaX - (textSizeWidth / 2))
ptLowerLeftTextOriginY = int(ptCenterOfTextAreaY + (textSizeHeight / 2))
cv2.putText(imgOriginalScene, licPlate.strChars,
(ptLowerLeftTextOriginX, ptLowerLeftTextOriginY), intFontFace,
fltFontScale, SCALAR_YELLOW, intFontThickness)