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move_embryo_fov_new_new_thresh.py
390 lines (384 loc) · 19.5 KB
/
move_embryo_fov_new_new_thresh.py
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# -*- coding: utf-8 -*-
"""
Created on Wed Feb 9 09:49:36 2022
@author: User
"""
from XYZ_Stage.XYZ_Position import XYZ_Location
from Delta_XY_FOV_1_lin import Delta_XY_FOV_1_lin
from Delta_XY_FOV_2_lin import Delta_XY_FOV_2_lin
from Delta_Z_FOV_1_lin import Delta_Z_FOV_1_lin
from Delta_Z_FOV_2_lin import Delta_Z_FOV_2_lin
from ML.ml_injection_point_estimation_new import ml_injection_point_estimation_new
import time
from matplotlib import pyplot as plt
from Pressure_Control.Continuous_Pressure import continuous_pressure
from stream_image import stream_image
import numpy as np
from math import pi,cos,sin
import cv2
from detect_injection import detect_injection
from ML.transform_points import transform_points
def move_embryo_fov_new_new_thresh(fov,action,X_est,Y_est,Z_est,inj_depth,inj_speed,back_pressure_value,pressure_value,pressure_time,arduino,current_x,current_y,current_z,view_1_x,view_1_y,view_2_x,view_2_y,footage_socket_1,footage_socket_2,inj_num,y1_1_crop,y2_1_crop,x1_1_crop,x2_1_crop,y1_2_crop,y2_2_crop,x1_2_crop,x2_2_crop,im_height_1,im_width_1,im_height_2,im_width_2,graph,sess,ser,time_wait,next_z,post_z,current_z_new,move_num,pic,thresh_1,thresh_2,resize):
end=0
end_1=0
end_2=0
injection_list_num=0
injected=2
sum_image=0
x_coord_emb_1=0
y_coord_emb_1=0
x_coord_tip_1=view_1_x
y_coord_tip_1=view_1_y
x_coord_emb_2=0
y_coord_emb_2=0
x_coord_tip_2=view_2_x
y_coord_tip_2=view_2_y
x_post_1=0
y_post_1=0
x_post_2=0
y_post_2=0
q='x'
q_o='x'
q_e='1'
l='x'
l_o='x'
l_e='1'
k=0
press_count=1
o=0
back_pressure_value_new=pressure_value
im_width_1_old=im_width_1
im_height_1_old=im_height_1
im_width_2_old=im_width_2
im_height_2_old=im_height_2
if fov==1 and action=='centroid':
current_z_new=current_z
# FOV 1 Center
img1,img2=stream_image(footage_socket_1,footage_socket_2,pic,1)
img1_crop=img1[y1_1_crop:y2_1_crop,x1_1_crop:x2_1_crop]
if resize==1:
img1_crop=cv2.resize(img1_crop,(400,400))
im_height_1=400
im_width_1=400
output_dict_detection_boxes_stored,output_dict_detection_classes_stored,output_dict_detection_scores_stored,y1a_rc,y2a_rc,x1a_rc,x2a_rc,xc_rc,yc_rc=ml_injection_point_estimation_new([img1_crop],thresh_1,im_height_1,im_width_1,graph,sess,1)
list_classes=output_dict_detection_classes_stored[0].tolist()
if 1 not in list_classes:
print('No centroid detected FOV1')
cv2.imwrite('C:/Users/me-alegr011-admin/Downloads/Robot_code/ML/Centroid_FOV_1_No_Work/{}.jpg'.format(inj_num),img1_crop)
current_x=X_est
current_y=Y_est
current_z=Z_est
end=2
else:
list_classes_index=list_classes.index(1)
if resize==1:
xc_rc[0][list_classes_index],yc_rc[0][list_classes_index]=transform_points(im_width_1,im_height_1,im_width_1_old,im_height_1_old,xc_rc[0][list_classes_index],yc_rc[0][list_classes_index])
plt.figure(1)
plt.title('Detected Centroid FOV1')
plt.xlabel('x coordinate (px)')
plt.ylabel('y coordinate (px)')
plt.plot(xc_rc[0][list_classes_index]+x1_1_crop,yc_rc[0][list_classes_index]+y1_1_crop,'ro',markersize=3)
plt.plot(view_1_x,view_1_y,'bo',markersize=3)
plt.imshow(img1,cmap='gray')
plt.show()
dx,dy=Delta_XY_FOV_1_lin(view_1_x,xc_rc[0][list_classes_index]+x1_1_crop)
dx=dx
dy=dy
print('Move up half z for FOV_1')
dz=int(float(Delta_Z_FOV_1_lin(view_1_y,yc_rc[0][list_classes_index]+y1_1_crop-105)))
current_z=current_z+dz
print('Current Z = ',current_z)
print('Moving embryo center under needle FOV1')
XYZ_Location(5000,5000,2000,current_x,current_y,current_z,ser)
time.sleep(.25)
current_x=current_x+dx
current_y=current_y+dy
x_coord_emb_1=xc_rc[0][list_classes_index]+x1_1_crop
y_coord_emb_1=yc_rc[0][list_classes_index]+y1_1_crop
x_coord_tip_1=view_1_x
y_coord_tip_1=view_1_y
print('Current X = ',current_x)
print('Current Y = ',current_y)
XYZ_Location(5000,5000,2000,current_x,current_y,current_z,ser)
time.sleep(.25)
next_z=current_z
elif fov==2 and action=='centroid':
current_z_new=current_z
# time.sleep(.15)
img1,img2=stream_image(footage_socket_1,footage_socket_2,pic,0)
img2_crop=img2[y1_2_crop:y2_2_crop,x1_2_crop:x2_2_crop]
if resize==2:
img2_crop=cv2.resize(img2_crop,(400,400))
im_height_2=400
im_width_2=400
output_dict_detection_boxes_stored,output_dict_detection_classes_stored,output_dict_detection_scores_stored,y1a_rc,y2a_rc,x1a_rc,x2a_rc,xc_rc,yc_rc=ml_injection_point_estimation_new([img2_crop],thresh_2,im_height_2,im_width_2,graph,sess,2)
list_classes=output_dict_detection_classes_stored[0].tolist()
if 1 not in list_classes:
print('No centroid detected FOV2')
cv2.imwrite('C:/Users/me-alegr011-admin/Downloads/Robot_code/ML/Centroid_FOV_2_No_Work/{}.jpg'.format(inj_num),img2_crop)
current_x=current_x
current_y=current_y
current_z=current_z
end=1
print('Done centroid FOV2')
else:
list_classes_index=list_classes.index(1)
if resize==2:
xc_rc[0][list_classes_index],yc_rc[0][list_classes_index]=transform_points(im_width_2,im_height_2,im_width_2_old,im_height_2_old,xc_rc[0][list_classes_index],yc_rc[0][list_classes_index])
plt.figure(2)
plt.title('Detected Centroid FOV2')
plt.xlabel('x coordinate (px)')
plt.ylabel('y coordinate (px)')
plt.plot(xc_rc[0][list_classes_index]+x1_2_crop,yc_rc[0][list_classes_index]+y1_2_crop,'ro',markersize=3)
plt.plot(view_2_x,view_2_y,'bo',markersize=3)
plt.imshow(img2,cmap='gray')
plt.show()
dx,dy=Delta_XY_FOV_2_lin(view_2_x,xc_rc[0][list_classes_index]+x1_2_crop)
print('Move up half z for FOV_2')
dz=int(float(Delta_Z_FOV_2_lin(view_2_y,yc_rc[0][list_classes_index]+y1_2_crop-90)))
current_z=current_z+dz
print('Current Z = ',current_z)
print('Moving embryo center under needle FOV2')
XYZ_Location(5000,5000,2000,current_x,current_y,current_z,ser)
time.sleep(.25)
current_x=current_x+dx
current_y=current_y+dy
x_coord_emb_2=xc_rc[0][list_classes_index]+x1_2_crop
y_coord_emb_2=yc_rc[0][list_classes_index]+y1_2_crop
x_coord_tip_2=view_2_x
y_coord_tip_2=view_2_y
print('Current X = ',current_x)
print('Current Y = ',current_y)
XYZ_Location(5000,5000,2000,current_x,current_y,current_z,ser)
time.sleep(.25)
next_z=current_z
elif action=='no move':
next_z=next_z
# time.sleep(.15)
img1,img2=stream_image(footage_socket_1,footage_socket_2,pic,0)
img1_crop=img1[y1_1_crop:y2_1_crop,x1_1_crop:x2_1_crop]
if resize==1:
img1_crop=cv2.resize(img1_crop,(400,400))
im_height_1=400
im_width_1=400
output_dict_detection_boxes_stored,output_dict_detection_classes_stored,output_dict_detection_scores_stored,y1a_rc,y2a_rc,x1a_rc,x2a_rc,xc_rc,yc_rc=ml_injection_point_estimation_new([img1_crop],thresh_1,im_height_1,im_width_1,graph,sess,3)
list_classes=output_dict_detection_classes_stored[0].tolist()
current_z_new=current_z
if 3 in list_classes:
print('Posterior detected FOV1')
list_classes_index=list_classes.index(3)
if resize==1:
xc_rc[0][list_classes_index],yc_rc[0][list_classes_index]=transform_points(im_width_1,im_height_1,im_width_1_old,im_height_1_old,xc_rc[0][list_classes_index],yc_rc[0][list_classes_index])
plt.figure(3)
plt.title('Detected Injection Point FOV1')
plt.xlabel('x coordinate (px)')
plt.ylabel('y coordinate (px)')
plt.plot(xc_rc[0][list_classes_index]+x1_1_crop,yc_rc[0][list_classes_index]+y1_1_crop,'ro',markersize=3)
plt.plot(view_1_x,view_1_y,'bo',markersize=3)
plt.imshow(img1,cmap='gray')
plt.show()
dx,dy=Delta_XY_FOV_1_lin(view_1_x,xc_rc[0][list_classes_index]+x1_1_crop)
current_x_new=current_x+dx
current_y_new=current_y+dy
dz_1=int(float(Delta_Z_FOV_1_lin(view_1_y,yc_rc[0][list_classes_index]+y1_1_crop-70)))
x_coord_emb_1=xc_rc[0][list_classes_index]+x1_1_crop
y_coord_emb_1=yc_rc[0][list_classes_index]+y1_1_crop
x_coord_tip_1=view_1_x
y_coord_tip_1=view_1_y
img2_crop=img2[y1_2_crop:y2_2_crop,x1_2_crop:x2_2_crop]
if resize==2:
img2_crop=cv2.resize(img2_crop,(400,400))
im_height_2=400
im_width_2=400
output_dict_detection_boxes_stored,output_dict_detection_classes_stored,output_dict_detection_scores_stored,y1a_rc,y2a_rc,x1a_rc,x2a_rc,xc_rc,yc_rc=ml_injection_point_estimation_new([img2_crop],thresh_2,im_height_2,im_width_2,graph,sess,6)
list_classes=output_dict_detection_classes_stored[0].tolist()
if 3 in list_classes:
print('Posterior detected FOV2')
list_classes_index_2=list_classes.index(3)
if resize==2:
xc_rc[0][list_classes_index_2],yc_rc[0][list_classes_index_2]=transform_points(im_width_2,im_height_2,im_width_2_old,im_height_2_old,xc_rc[0][list_classes_index_2],yc_rc[0][list_classes_index_2])
plt.figure(6)
plt.title('Detected Injection Point FOV2')
plt.xlabel('x coordinate (px)')
plt.ylabel('y coordinate (px)')
plt.plot(xc_rc[0][list_classes_index_2]+x1_2_crop,yc_rc[0][list_classes_index_2]+y1_2_crop,'ro',markersize=3)
plt.plot(view_2_x,view_2_y,'bo',markersize=3)
plt.imshow(img2,cmap='gray')
plt.show()
dx,dy=Delta_XY_FOV_2_lin(view_2_x,xc_rc[0][list_classes_index_2]+x1_2_crop)
current_x_new=current_x_new+dx
current_y_new=current_y_new+dy
dz_2=int(float(Delta_Z_FOV_2_lin(view_2_y,yc_rc[0][list_classes_index_2]+y1_2_crop-70)))
current_z_new=current_z+int(np.mean([dz_1,dz_2]))
x_coord_emb_2=xc_rc[0][list_classes_index_2]+x1_2_crop
y_coord_emb_2=yc_rc[0][list_classes_index_2]+y1_2_crop
x_coord_tip_2=view_2_x
y_coord_tip_2=view_2_y
if abs(x_coord_emb_1-x_coord_tip_1)<=5*move_num and abs(x_coord_emb_2-x_coord_tip_2)<=5*move_num:
current_x=current_x
current_y=current_y
else:
current_x=current_x_new
current_y=current_y_new
else:
print('Done posterior FOV2')
end_2=1
else:
end_1=1
print('Done posterior FOV1')
elif action=='just move':
next_z=next_z
print('Current X = ',current_x)
print('Current Y = ',current_y)
print('Current Z = ',current_z)
print('Moving embryo injecion point under needle')
XYZ_Location(5000,5000,2000,current_x,current_y,current_z,ser)
# time.sleep(.25)
time.sleep(.5)
elif action=='inject new':
XYZ_Location(5000,5000,2000,current_x,current_y,current_z,ser)
time.sleep(.5)
next_z=next_z
current_z_new=current_z
# time.sleep(.15)
img1,img2=stream_image(footage_socket_1,footage_socket_2,pic,0)
img1_crop=img1[y1_1_crop:y2_1_crop,x1_1_crop:x2_1_crop]
if resize==1:
img1_crop=cv2.resize(img1_crop,(400,400))
im_height_1=400
im_width_1=400
output_dict_detection_boxes_stored,output_dict_detection_classes_stored,output_dict_detection_scores_stored,y1a_rc_1,y2a_rc_1,x1a_rc_1,x2a_rc_1,xc_rc_1,yc_rc_1=ml_injection_point_estimation_new([img1_crop],thresh_1,im_height_1,im_width_1,graph,sess,3)
list_classes_1=output_dict_detection_classes_stored[0].tolist()
img2_crop=img2[y1_2_crop:y2_2_crop,x1_2_crop:x2_2_crop]
if resize==2:
img2_crop=cv2.resize(img2_crop,(400,400))
im_height_2=400
im_width_2=400
output_dict_detection_boxes_stored,output_dict_detection_classes_stored,output_dict_detection_scores_stored,y1a_rc_2,y2a_rc_2,x1a_rc_2,x2a_rc_2,xc_rc_2,yc_rc_2=ml_injection_point_estimation_new([img2_crop],thresh_2,im_height_2,im_width_2,graph,sess,2)
list_classes_2=output_dict_detection_classes_stored[0].tolist()
if 3 in list_classes_1 and 3 in list_classes_2:
print('Posterior detected FOV1')
list_classes_index_1=list_classes_1.index(3)
if resize==1:
xc_rc_1[0][list_classes_index_1],yc_rc_1[0][list_classes_index_1]=transform_points(im_width_1,im_height_1,im_width_1_old,im_height_1_old,xc_rc_1[0][list_classes_index_1],yc_rc_1[0][list_classes_index_1])
x_post_1=xc_rc_1[0][list_classes_index_1]
y_post_1=yc_rc_1[0][list_classes_index_1]
print('Posterior detected FOV2')
list_classes_index_2=list_classes_2.index(3)
if resize==2:
xc_rc_2[0][list_classes_index_2],yc_rc_2[0][list_classes_index_2]=transform_points(im_width_2,im_height_2,im_width_2_old,im_height_2_old,xc_rc_2[0][list_classes_index_2],yc_rc_2[0][list_classes_index_2])
x_post_2=xc_rc_2[0][list_classes_index_2]
y_post_2=yc_rc_2[0][list_classes_index_2]
cv2.imwrite('C:/Users/me-alegr011-admin/Downloads/Robot_code/ML/Surface_injection/images/post_fov_1_{}.jpg'.format(inj_num),img1_crop)
cv2.imwrite('C:/Users/me-alegr011-admin/Downloads/Robot_code/ML/Surface_injection/images/post_fov_2_{}.jpg'.format(inj_num),img2_crop)
injection_list_num=1
dz=int(np.mean([float(Delta_Z_FOV_1_lin(view_1_y,y_post_1+y1_1_crop)),float(Delta_Z_FOV_2_lin(view_2_y,y_post_2+y1_2_crop))]))+inj_depth
print('Injection Depth = ',dz)
plt.figure(7)
plt.title('Detected Injection Point FOV1')
plt.xlabel('x coordinate (px)')
plt.ylabel('y coordinate (px)')
plt.plot(x_post_1+x1_1_crop,y_post_1+y1_1_crop,'ro',markersize=3)
plt.plot(view_1_x,view_1_y,'bo',markersize=3)
plt.imshow(img1,cmap='gray')
plt.figure(8)
plt.title('Detected Injection Point FOV2')
plt.xlabel('x coordinate (px)')
plt.ylabel('y coordinate (px)')
plt.plot(x_post_2+x1_2_crop,y_post_2+y1_2_crop,'ro',markersize=3)
plt.plot(view_2_x,view_2_y,'bo',markersize=3)
plt.imshow(img2,cmap='gray')
plt.show()
current_z=current_z+dz
print('Current Z = ',current_z)
print('Piercing through embryo')
# change from 2000 to 5000
XYZ_Location(5000,5000,inj_speed,current_x,current_y,current_z,ser)
# Pressure
print('Injecting embryo')
#comment
while q=='x' or q_o=='x' or q_e!='p':
print('Try ',o+1)
signal=continuous_pressure(back_pressure_value_new,pressure_value,'inj')
arduino.write(signal.encode())
arduino.flush()
q_=arduino.readline()
q_=q_.decode()
print(q_)
q_o=q_[7]
q=q_[8]
q_e=q_[len(q_)-3]
o+=1
#comment
time.sleep(pressure_time)
# #comment
#new
current_z=current_z-inj_depth-300
# Come out
#comment
XYZ_Location(20000,20000,inj_speed,current_x,current_y,current_z,ser)
time.sleep(1.5)
img1,img2=stream_image(footage_socket_1,footage_socket_2,pic,0)
img1_crop=img1[y1_1_crop:y2_1_crop,x1_1_crop:x2_1_crop]
img2_crop=img2[y1_2_crop:y2_2_crop,x1_2_crop:x2_2_crop]
# #comment
# #new
# print('Pressure done')
# if pressure_time==1 or pressure_time==2:
# time.sleep(1)
# while back_pressure_value_new>back_pressure_value:
# back_pressure_value_new=pressure_value-(press_count)
# print(back_pressure_value_new)
# l='x'
# l_o='x'
# l_e='1'
# k=0
# while l=='x' or l_o=='x' or l_e!='p':
# print('Try ',k+1)
# signal=continuous_pressure(back_pressure_value_new,pressure_value,'bp')
# arduino.write(signal.encode())
# l_=arduino.readline()
# l_=l_.decode()
# print(l_)
# l_o=l_[7]
# l=l_[8]
# l_e=l_[len(l_)-3]
# k+=1
# press_count+=1
# # press_count+=2
#comment
#new
print('Pressure done')
if pressure_time==1 or pressure_time==2:
time.sleep(1)
while l=='x' or l_o=='x' or l_e!='p':
print('Try ',k+1)
arduino.write("P0p".encode())
arduino.flush()
l_=arduino.readline()
l_=l_.decode()
print(l_)
l_o=l_[7]
l=l_[8]
l_e=l_[len(l_)-3]
k+=1
cv2.imwrite('C:/Users/me-alegr011-admin/Downloads/Robot_code/ML/Detect_injection/post_fov_1_{}.jpg'.format(inj_num),img1_crop)
cv2.imwrite('C:/Users/me-alegr011-admin/Downloads/Robot_code/ML/Detect_injection/post_fov_2_{}.jpg'.format(inj_num),img2_crop)
sum_image_1=detect_injection(img1,view_1_x,view_1_y,y2_1_crop)
print('FOV 1 number of blue px = ',sum_image_1)
sum_image_2=detect_injection(img2,view_2_x,view_2_y,y2_2_crop)
print('FOV 2 number of blue px = ',sum_image_2)
sum_image=np.mean([sum_image_1,sum_image_2])
print('Mean of blue px = ',sum_image)
injected=1
#comment
end=3
elif 3 not in list_classes_1:
print('no injection because FOV 1')
end_1=1
else:
print('no injection because FOV 1')
end_2=1
else:
print('Doing nothing')
return end,current_x,current_y,current_z,next_z,injection_list_num,x_coord_emb_1,y_coord_emb_1,x_coord_tip_1,y_coord_tip_1,x_coord_emb_2,y_coord_emb_2,x_coord_tip_2,y_coord_tip_2,arduino,y1_1_crop,y2_1_crop,x1_1_crop,x2_1_crop,y1_2_crop,y2_2_crop,x1_2_crop,x2_2_crop,im_width_1_old,im_height_1_old,im_width_2_old,im_height_2_old,current_z_new,move_num,injected,end_1,end_2,injected,sum_image