def main():
i=1
#folder_path = "/media/pi/DAPHNIA/goniometer/" + time.strftime("%Y%m%d-%H%M%S/")
folder_path = "sample_imgs/" + time.strftime("%Y%m%d-%H%M%S/")
q = Queue(maxsize=MAX_QSIZE)
bc = BaslerController(folder_path, q)
#bc.close_camera()
bc.open_camera()
bc.update_nodemap()
bc.cont_acq()
#display(q)
print("cont")
consumer = Consumer(q)
stop_threads = False
consumer_thread = threading.Thread(target=consumer.run, args =(lambda : stop_threads, ))
consumer_thread.start()
time.sleep(4)
bc.save_images("test_1")
time.sleep(13)
bc.stop_cont_acq()
stop_threads = True
print("stop thre")
consumer_thread.join()
print("con joined")
q.join()
print("q join")
bc.close_camera()
print("done")
def main():
#folder_path = "/media/pi/DAPHNIA/goniometer/" + time.strftime("%Y%m%d-%H%M%S/")
folder_path = "/media/pi/DAPHNIA/goniometer/" + time.strftime(
"%Y%m%d-%H_%M_%S/")
bc = BaslerController(folder_path)
bc.open_camera()
bc.update_nodemap()
bc.cont_acq()
protocol_filename = "protocol_test.csv"
protocol = GoniometerObject.read_csv(protocol_filename)
go = GoniometerObject()
go.copy_csv(protocol_filename, folder_path)
time.sleep(10)
bc.stop_cont_acq()
d = [0, 0, 0]
bc.nbr_im = 1
#for d in protocol:
for i in range(0, 3):
print("led:", d[0])
go.led_angle = int(d[0])
print("stage:", d[1])
go.stage_angle = int(d[1])
print("sample:", d[2])
go.sample_angle = int(d[2])
go.done_moving(go.LED)
go.done_moving(go.STAGE)
go.done_moving(go.SAMPLE)
#bc.stop_cont_acq()
bc.save_images()
print("--------------counter at {} mod {}".format(
bc.counter, bc.counter % 9))
#bc.cont_acq() # before move im to make continuous
#
#tmp = d
#tmp[0] = i
bc.move_images([i, i, i])
time.sleep(2)
#bc.cont_acq()
#go.led_angle = 15
#go.done_moving(go.LED)
print("done main")
go.BP.reset_all()
def main():
i=1
folder_path = "/media/pi/DAPHNIA/goniometer/" + time.strftime("%Y%m%d-%H%M%S/")
bc = BaslerController(folder_path)
#bc.close_camera()
bc.open_camera()
bc.update_nodemap()
bc.cont_acq()
print("cont")
time.sleep(2)
bc.stop_cont_acq()
bc.save_images()
bc.move_images([i, i, i])
bc.cont_acq() #maybe this one should be started in save images, alt move the files in a separate method
print("cont")
time.sleep(5)
bc.stop_cont_acq()
bc.close_camera()
print("done")
def main():
nbr_im = 9
#folder_path = "/home/pi/Desktop/BrickPi3-master/Software/Python/Testing Scripts/pypylon/images/" + time.strftime("%Y%m%d-%H%M%S/")
gui_folder_name = "gui_test_1"
folder_path = "sample_imgs/" + time.strftime("%Y%m%d-%H%M%S/")
q = Queue(maxsize=MAX_QSIZE)
bc = BaslerController(folder_path, q)
#bc.close_camera()
bc.open_camera()
bc.update_nodemap()
bc.cont_acq()
print("cont")
time.sleep(2)
bc.save_images("gui_test_1")
# make this wait a method
while (not bc.thread_move):
time.sleep(1)
print("move not started")
while (bc.thread_move.isAlive()):
time.sleep(1) # todo make this sleep small or remove
print("move ongoing")
print("move done")
lowest_mean = sys.maxsize
index_off = -1
for i in range(0, nbr_im):
a = plt.imread(folder_path + gui_folder_name + "/{}.tiff".format(i))
plt.hist(a.flatten(), 32, label='LED {}'.format(i), alpha=0.5)
print("LED {} has a mean off: {}".format(i, a.mean()))
if a.mean() < lowest_mean:
lowest_mean = a.mean()
index_off = i
plt.legend(loc='upper right')
plt.show()
# print("input new exposure time in µs")
# new_exp_time = input()
# bc.update_value_nodemap("ExposureTimeRaw", new_exp_time)
# bc.stop_cont_acq()
# bc.update_nodemap()
#
# bc.cont_acq()
# print("cont")
# time.sleep(1)
# bc.save_images("gui_test_2")
# # make this wait a method
#
# while(bc.thread_move.isAlive()):
# time.sleep(1) # todo make this sleep small or remove
# print("move ongoing")
# print("move done")
# lowest_mean = sys.maxsize
# index_off = -1
# for i in range(0, nbr_im):
#
# a = plt.imread(folder_path + gui_folder_name + "/{}.tiff".format(i))
# plt.hist(a.flatten(), 32, label='LED {}'.format(i), alpha=0.5)
# print("LED {} has a mean off: {}".format(i, a.mean()))
# if a.mean() < lowest_mean:
# lowest_mean = a.mean()
# index_off = i
#
#
# plt.legend(loc='upper right')
# plt.show()
# create color_image
#dark is 0
# 1 365
# 2 405
# 3 430 (blue)
# 4 490
# 5 525 (green)
# 6 630 (red)
# 7 810
# 8 940
#
#import pdb;pdb.set_trace()
img_off = plt.imread(folder_path + gui_folder_name +
"/{}.tiff".format(index_off))
img_r = plt.imread(folder_path + gui_folder_name +
"/{}.tiff".format((index_off + 6) % 9))
img_g = plt.imread(folder_path + gui_folder_name +
"/{}.tiff".format((index_off + 5) % 9))
img_b = plt.imread(folder_path + gui_folder_name +
"/{}.tiff".format((index_off + 3) % 9))
dynamic_range = 65520
# current_fig = plt.figure(1)
# plt.imshow(img_off)
# current_fig = plt.figure(2)
# red = (img_r).astype(float)
# red = red/dynamic_range
# plt.imshow(red)
# current_fig = plt.figure(3)
# plt.imshow(img_g)
# current_fig = plt.figure(4)
# plt.imshow(img_b)
color_img = np.ndarray(shape=(img_r.shape + (3, )), dtype=float)
# red = (img_r - img_off).astype(float)
# red = red/dynamic_range
# green = (img_g - img_off).astype(float)
# green = green/dynamic_range
# blue = (img_b - img_off).astype(float)
# blue = blue/dynamic_range
# color_img[:,:,0] = red
# color_img[:,:,1] = green
# color_img[:,:,2] = blue
#
# current_fig = plt.figure(5)
# plt.imshow(red)
# current_fig = plt.figure(6)
# plt.imshow(green)
# current_fig = plt.figure(7)
# plt.imshow(blue)
#
# current_fig = plt.figure(8)
#
# plt.imshow(color_img)
current_fig = plt.figure(9)
red = (img_r).astype(float)
red = red / dynamic_range
green = (img_g).astype(float)
green = green / dynamic_range
blue = (img_b).astype(float)
blue = blue / dynamic_range
color_img[:, :, 0] = red
color_img[:, :, 1] = green
color_img[:, :, 2] = blue
plt.imshow(color_img)
plt.show(block=False)
# print("input calibration values for red [0 - 1]:")
# calib_red = input()
#
# print("input calibration values for green [0 - 1]:")
# calib_green = input()
#
# print("input calibration values for blue [0 - 1]:")
# calib_blue = input()
#
print(
"click in the top left corner and the bottom right corner of a white reference area"
)
reference_coords = plt.ginput(2)
print(reference_coords)
#import pdb; pdb.set_trace()
white_ref = color_img[
int(round(reference_coords[0][0])):int(round(reference_coords[1][0])),
int(round(reference_coords[0][1])):int(round(reference_coords[1][1])
), :]
calib_val_red = white_ref[:, :, 0].mean()
calib_val_green = white_ref[:, :, 1].mean()
calib_val_blue = white_ref[:, :, 2].mean()
print(calib_val_red)
print(calib_val_green)
print(calib_val_blue)
color_img[:, :, 0] = color_img[:, :, 0] / calib_val_red
color_img[:, :, 1] = color_img[:, :, 1] / calib_val_green
color_img[:, :, 2] = color_img[:, :, 2] / calib_val_blue
color_img = color_img / np.max(color_img)
plt.imshow(color_img)
plt.show()
bc.stop_cont_acq()
bc.close_camera()
print("done")