Я нашел только образцы для отслеживания лица.
Как я могу отслеживать прямоугольники с определенным цветом?
И мне нужны его пиксели.
Вот скрипт, который сделает это:
from PIL import Image
from math import sqrt
RED = 0
GREEN = 1
BLUE = 2
COLORS = [RED, GREEN, BLUE]
RED_HEALTH = (234, 105, 112)
BLUE_HEALTH = (84, 165, 226)
HEALTH_BORDER = (0, 0, 0)
image = Image.open("image.jpg")
def close_enough_to(src, target, delta):
diff = 0
for color in COLORS:
diff += (src[color] - target[color]) ** 2
diff = sqrt(diff)
return diff <= delta
class HealthBar:
def __init__(self, team, health_percentage, length, pos):
self.team = team
self.health_percentage = health_percentage
self.length = length
self.pos = pos
def __str__(self):
return "team {}, percentage {}, length {}, pos {}".format(self.team,
self.health_percentage,
self.length,
self.pos
)
def __repr__(self):
return str(self)
def flood_fill_health_bar(image, pos, color, traversed):
(x, y) = pos
health_pixels = 0
while close_enough_to(image.getpixel((x, y)), color) \
and (x, y) not in traversed:
health_pixels += 1
traversed.add((x, y))
x += 1
black_pixels = 0
while close_enough_to(image.getpixel((x, y)), HEALTH_BORDER, 50) \
and (x, y) not in traversed:
black_pixels += 1
traversed.add((x, y))
x += 1
if black_pixels > 0:
if color is RED_HEALTH:
team = "red"else:
team = "blue"percent_health = health_pixels / (health_pixels + black_pixels)
return HealthBar(team, percent_health, health_pixels + black_pixels, pos)
def in_bounds(image, pos):
return pos[0] >= 0 and pos[1] >= 0 \
and pos[0] < image.width and pos[1] < image.height
def flood_fill_image(image, start, delta):
flood_fill_queue = [start]
traversed = []
color = image.getpixel(start)
pos = start
pix = image.load()
while len(flood_fill_queue):
(x, y) = flood_fill_queue.pop()
positions = [(x+1, y), (x-1, y), (x, y+1), (x, y-1)]
for position in positions:
if in_bounds(image, position) \
and close_enough_to(image.getpixel(position), color, delta):
if position not in traversed:
flood_fill_queue.append(position)
traversed.append(position)
(x, y) = position
pix[x, y] = (0, 0, 255)
return traversed
def get_width(positions):
return get_max_x(positions) - get_min_x(positions)
def get_height(positions):
return get_max_y(positions) - get_min_y(positions)
def get_max_x(positions):
return sorted(list(positions), key=lambda x: x[0])[-1][0]
def get_max_y(positions):
return sorted(list(positions), key=lambda x: x[1])[-1][1]
def get_min_x(positions):
return sorted(list(positions), key=lambda x: x[0])[0][0]
def get_min_y(positions):
return sorted(list(positions), key=lambda x: x[1])[0][1]
def find_health_bars(image):
traversed = set()
health_bars = []
pix = image.load()
(width, height) = image.size
for col in range(0, width):
for row in range(0, height):
# pix = image.getpixel((col, row))
if (col, row) in traversed:
continue
for health_color in [RED_HEALTH, BLUE_HEALTH]:
border_pixels = []
if close_enough_to(image.getpixel((col, row)), health_color, 10):
health_pixels = flood_fill_image(image, (col, row), 100)
for pos in health_pixels:
(x, y) = pos
traversed.add(pos)
pix[x, y] = (255, 255, 0)
border_pixels = flood_fill_image(image, (col - 1, row - 1), 30)
if len(border_pixels) is 0:
continue
health_bar_width = get_width(border_pixels)
health_bar_height = get_height(border_pixels)
health_width = get_width(health_pixels)
if abs(health_bar_width / health_bar_height) - 10 <= 0.5:
team = "blue" if health_color == BLUE_HEALTH else "red"percent_health = health_width / health_bar_width
health_bar = HealthBar(team, percent_health, health_bar_width, (col, row))
health_bars.append(health_bar)
for pos in border_pixels:
(x, y) = pos
traversed.add(pos)
pix[x, y] = (0, 255, 255)
health_bars = [health_bar for health_bar in health_bars if health_bar is not None]
health_bars.sort(key=lambda x: x.length)
return health_bars
health_bars = find_health_bars(image)
print(health_bars)
В основном это алгоритм:
Вот как это выглядит визуально после вычисления заливки (функция не подходит для ваших кругов, хотя я думаю, что это не будет проблемой …):
Желтые области — это область здоровья, а голубой — граница. Как видите, он не идеален, но, надеюсь, он достаточно близок. Кроме того, я предполагаю, что изображения, с которыми вы будете использовать это, будут png вместо jpg, так что это устранит некоторую неточность.
РЕДАКТИРОВАТЬ: Вот вывод печати health_bars
:
[team blue, percentage 1.0, length 20, pos (66, 433), team blue, percentage 1.0, length 34, pos (130, 436), team red, percentage 0.38095238095238093, length 63, pos (149, 357), team blue, percentage 0.953125, length 64, pos (27, 404), team red, percentage 0.6703296703296703, length 91, pos (480, 119), team red, percentage 0.5700934579439252, length 107, pos (500, 52)]
Составьте список, в который вы поместите каждого миньона, затем переберите этот список и посмотрите, красный он или синий. Если это возможно …