def save_heatmap(args):
img = args[0]
for idx, att in enumerate(args[1]):
heatmap.add(img, att, alpha=0.4, save=f'{global_att_dir}/{global_epoch}_{args[2]}_{idx}.png', axis='off')
# all_boxes[j][i] = all_boxes[j][i][keep, :]
misc_toc = time.time()
nms_time = misc_toc - misc_tic
sys.stdout.write('im_detect: {:d}/{:d} {:.3f}s {:.3f}s \r' \
.format(i + 1, num_images, detect_time, nms_time))
sys.stdout.flush()
output_dir = '/data/Salient_Image_data/output/' + input_img_path.split(
'/')[-2]
if not os.path.exists(output_dir): os.makedirs(output_dir)
output_path = os.path.join(output_dir, input_img_path.split('/')[-1])
heat_map_f = ndimage.filters.gaussian_filter(heat_map, sigma=40)
heatmap.add(im2show, heat_map_f, alpha=0.7, save=output_path)
# IPython.embed()
#
# if vis:
# # print('save image to r')
# cv2.imwrite('result.png', im2show)
#
# # pdb.set_trace()
# #cv2.imshow('test', im2show)
# #cv2.waitKey(0)
# with open(det_file, 'wb') as f:
# pickle.dump(all_boxes, f, pickle.HIGHEST_PROTOCOL)
#
# print('Evaluating detections')
import heatmap
from scipy import ndimage
from skimage import io
import numpy as np
# read image
image_filename = '../data/face.png'
image = io.imread(image_filename)
# create heat map
x = np.zeros((101, 101))
x[50, 50] = 1
heat_map = ndimage.filters.gaussian_filter(x, sigma=16)
heatmap.add(image, heat_map, alpha=0.7, save='../data/face_heat_map.png')
for alpha in np.arange(0, 1.1, 0.1):
print('alpha ' + str(alpha))
heatmap.add(image, heat_map, alpha=alpha, save='../data/face_heat_map_' + str(alpha) + '.png', axis='off')
def detect_referee(hg_matrix):
global referee_position
global input_ball
global flag
#İlk açılan pencereler
win_Settings(0)
#Hakem rengi belirlemek için
low_color = np.array([35, 0, 150])
high_color = np.array([85, 170, 255])
#Daha önce oluşturulan saha içi maske
area_mask = cv2.imread(field_mask_path)
cap = cv2.VideoCapture(vid_filepath)
#Hakemin ilk konumunu belirlemek ve konum bulmak için pencere boyutları
resize_x = 40
resize_y = 30
frame = set_object_pos(cap)
frame = init_frames(frame, resize_x, resize_y)
x = 0
y = 0
w = 0
h = 0
#Top_view'e konum atmak için arraylar
input_pts = []
input_referee = [[0, 0], 'r']
input_ball = [[0, 0], 'null']
feet_coord = [0, 0]
#Top_View boyutlarında ısı haritası oluşturma
heatmap.create_heatmap()
heat_key = True
mask_key = False
#-Hakemin her iki saniyedeki hızı
print('Starting..\n\n')
print(
'Click anywhere on Main_Frame to determine the distance.\n L-Mouse: Choose point\n R-Mouse: Remove point'
)
second = 2
rt = speed.RepeatedTimer(second, speed.flag)
#----- Hakemin tespit edilip işaretlendiği kısım ---------
while True:
ret, frame = cap.read()
if ret:
area_masked = cv2.bitwise_and(frame, area_mask)
cropped_frame_referee = area_masked[resized_r[0]:resized_r[1],
resized_r[2]:resized_r[3]]
#Maskeleme işlemleri
masked = image_masks(cropped_frame_referee, low_color, high_color)
image, contours, hierarchy = cv2.findContours(
masked, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if (len(contours) <= 0):
cv2.rectangle(cropped_frame_referee, (x, y), (x + w, y + h),
(0, 0, 255), 2)
cv2.rectangle(frame, (x + resized_r[2], y + resized_r[0]),
(x + w + resized_r[2], y + h + resized_r[0]),
(0, 255, 0), 2)
else:
for contour in contours:
(x, y, w, h) = cv2.boundingRect(contour)
if ((w < 22 or h < 20) or (w > 40 or h > 45)): continue
feet_coord = [
float((x + resized_r[2]) + int(25 / 2.0)),
float((y + resized_r[0]) + 25)
]
# feet_coord = [x + w/2, y + h)]
input_referee = [feet_coord, 'r']
cv2.rectangle(cropped_frame_referee, (x, y),
(x + w, y + h), (0, 0, 255), 2)
cv2.rectangle(frame, (x + resized_r[2], y + resized_r[0]),
(x + w + resized_r[2], y + h + resized_r[0]),
(0, 255, 0), 2)
if (x != 0 and y <= 5): set_resized_r(0, frame_lenx)
if (y >= resize_x * 2 - h - 5):
set_resized_r(1, frame_lenx)
if (x <= 5 and y != 0): set_resized_r(2, frame_lenx)
if (x >= resize_y * 2 - w - 5):
set_resized_r(3, frame_lenx)
cv2.setMouseCallback('Main_Frame', on_mouse_click,
[x + resized_r[2], y + resized_r[0]])
input_pts = [input_referee, input_ball]
top_img, player_top_points = top_view.create_topview(
hg_matrix, input_pts)
heatmap_mask = heatmap.add(player_top_points[0][0])
ref_speed = speed.cal_speed(time.localtime().tm_sec,
player_top_points[0][0])
top_img = drawoffside.drawspeed(top_img, player_top_points,
ref_speed)
if (player_top_points[1][1][0] == 'b'):
rb_distance = distance.cal_distance(player_top_points)
top_img = drawoffside.drawLine(top_img, player_top_points,
rb_distance)
cv2.imshow('Main_Frame', frame)
cv2.imshow('Top_View', top_img)
#Gereksiz kalabalık m tuşuna basınca gözükmesi ve kapanması için
if mask_key:
win_Settings(1)
cv2.imshow('Mask_Frame', masked)
cv2.imshow('Cropped_Frame', cropped_frame_referee)
else:
cv2.destroyWindow('Mask_Frame')
cv2.destroyWindow('Cropped_Frame')
else:
print("ret, false, video bitti")
win_Settings(2)
colored_heatmap = heatmap.colorize(heatmap_mask)
cv2.imshow('Heat_Map_Mask', heatmap_mask)
cv2.imshow('Heat_Map_Color', colored_heatmap)
#Tuş takımı
key = cv2.waitKey(15) & 0xFF
if key == ord('h'):
if heat_key:
win_Settings(2)
colored_heatmap = heatmap.colorize(heatmap_mask)
cv2.imshow('Heat_Map_Mask', heatmap_mask)
cv2.imshow('Heat_Map_Color', colored_heatmap)
heat_key = False
else:
heat_key = True
cv2.destroyWindow('Heat_Map_Mask')
cv2.destroyWindow('Heat_Map_Color')
if key == ord('m'):
if mask_key:
mask_key = False
else:
mask_key = True
if key == ord('q'):
break
rt.stop()
cap.release()
cv2.destroyAllWindows()