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import readGridEyeData
import sys
import numpy as np
import cv2
SIZE = 8
visible_size = 128
distanceBetweenSensors_w = 2.6 #cm
distanceBetweenSensors_h = 2.6 #cm
distance2Object = 60.0 #cm
OFFSET = ((0, 0), ())
TEMP_SCALE = 20
RED = (0, 0, 255)
GREEN = (0, 255, 0)
BLUE = (255, 0, 0)
background = readGridEyeData.GridEyeData(sys.argv[1])
background_frames = [np.zeros((SIZE,SIZE)), np.zeros((SIZE,SIZE)),
np.zeros((SIZE,SIZE)), np.zeros((SIZE,SIZE))]
cnt = 1
Horizon_array = np.array([[x for x in range(8)] for _ in range(8)])
Vertical_array = np.array([[x for _ in range(8)] for x in range(8)])
# Gets background of each pixel.
while background.readFrame():
frames = background.frames
for i in range(4):
background_frames[i] += np.array(frames[i].data)
cnt += 1
for i in range(4):
background_frames[i]/=cnt
# Reads data from object frames.
objects = readGridEyeData.GridEyeData(sys.argv[2])
while objects.readFrame():
frames = objects.frames
imgs = []
heat_points = []
# Subtracts background and scale the value.
for i in range(4):
frame = np.array(frames[i].data) - background_frames[i]
frame[frame < 0] = 0.0
frame *= TEMP_SCALE
frame[frame > 255] = 255
imgs.append(frame.astype(np.uint8))
x = int(sum(sum(frame * Horizon_array)) / sum(sum(frame)) / (SIZE - 1) *
(visible_size - 1))
y = int(sum(sum(frame * Vertical_array)) / sum(sum(frame)) / (SIZE - 1) *
(visible_size - 1))
heat_points.append((x,y))
print (x, y)
all_img = np.concatenate((np.concatenate((imgs[0], imgs[1]), axis = 1),
np.concatenate((imgs[2], imgs[3]), axis = 1)),
axis = 0)
all_img = cv2.cvtColor(all_img, cv2.COLOR_GRAY2RGB)
all_img = cv2.resize(all_img, (visible_size*2, visible_size*2),
interpolation = cv2.INTER_NEAREST)
cv2.circle(all_img, heat_points[0], 5, RED, -1)
cv2.circle(all_img, (heat_points[1][0]+visible_size, heat_points[1][1]), 5, RED, -1)
cv2.imshow('sample', all_img)
while cv2.getWindowProperty('sample', 0) >= 0:
key = cv2.waitKey(50)
if key >= 0:
break