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vo_gui.py
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"""---------- Batchaya Noumeme Yacynte Divan ----------"""
"""---------- Bachelor's in Mechatronics Thesis ----------"""
"""---------- Development of Monocular Visual Odometry Algorithm, WS 23/24 ----------"""
"""---------- Technische Hochshule Wuerzburg-Schweinfurt ---------"""
"""---------- Centre for Robotics ---------"""
from cProfile import label
import tkinter as tk
import cv2, csv
from scipy.spatial.transform import Rotation
import time
from tkinter import ttk
from tkinter import filedialog
from functools import partial
import numpy as np
import os
import queue
from tkinter.ttk import Progressbar
import threading
import matplotlib.pyplot as plt
import visual_odometry
from plot_param import regression
class VOApp:
def __init__(self, root):
self.root = root
self.root.title("Visual Odometry")
# Selected data folder path
self.data_folder_path = tk.StringVar()
# Create frame for the option selection on the left
self.option_frame_left = ttk.Frame(root)
self.option_frame_left.pack(side="left", padx=20, pady=20)
# Label for the data folder selection
#ttk.Label(self.option_frame_left, text="Select Data Folder:").grid(row=0, column=0, padx=5, pady=5)
# Progress bar
self.progress_label = ttk.Label(self.option_frame_left, text="Progress Bar:")
self.progress_label.grid(pady=5)
self.progress_var = tk.DoubleVar()
self.progress_bar = Progressbar(self.option_frame_left, length=200, mode='determinate', variable=self.progress_var)
self.progress_bar.grid(pady=5, columnspan=3)
# Create a label to display the percentage
self.percentage_label = tk.Label(self.option_frame_left, text="")
self.percentage_label.grid(row=2, column=0, padx=5, pady=5)
# Create a label to display the speed
self.speed_label = tk.Label(self.option_frame_left, text="")
self.speed_label.grid(row=2, column=1, padx=5, pady=5)
# Entry for the selected data folder path
# self.data_folder_entry = ttk.Entry(self.option_frame_left, textvariable=self.data_folder_path, state="readonly")
# self.data_folder_entry.grid(row=0, column=1, padx=5, pady=5)
# Button to browse and select data folder
# ttk.Button(self.option_frame_left, text="Browse", command=self.select_data_folder).grid(row=0, column=2, padx=5, pady=5)
# Button to clear selected data folder
# ttk.Button(self.option_frame_left, text="Clear Data Folder", command=self.clear_data_folder).grid(row=0, column=3, padx=5, pady=5)
# Label for the option selection
ttk.Label(self.option_frame_left, text="Tello Dji data:").grid(row=3, column=0, padx=5, pady=5)
# Combobox for Option 1
self.option1_var = tk.StringVar()
self.option1_combo = ttk.Combobox(self.option_frame_left, textvariable=self.option1_var, state="readonly")
self.option1_combo.grid(row=3, column=1, padx=5, pady=5)
self.option1_combo['values'] = ('c-curve','line')#, 'line2', 'square', 'c_curve_3')
# Label for the sub-option selection
ttk.Label(self.option_frame_left, text="Kitti data:").grid(row=4, column=0, padx=5, pady=5)
# Combobox for Option 2
self.option2_var = tk.StringVar()
self.option2_combo = ttk.Combobox(self.option_frame_left, textvariable=self.option2_var, state="readonly")
self.option2_combo.grid(row=4, column=1, padx=5, pady=5)
self.option2_combo['values'] = ('c-curve', 'line')
# Label for the sub-option selection
ttk.Label(self.option_frame_left, text="Unreal Engine data:").grid(row=5, column=0, padx=5, pady=5)
# Combobox for Option 3
self.option3_var = tk.StringVar()
self.option3_combo = ttk.Combobox(self.option_frame_left, textvariable=self.option3_var, state="readonly")
self.option3_combo.grid(row=5, column=1, padx=5, pady=5)
self.option3_combo['values'] = ('line', 'square')#, 'c-curve', 'circle', 'square_rotate')
# Button to select the folder based on the options
#ttk.Button(self.option_frame_left, text="Select dataset", command=self.select_folder).grid(pady=10)
# Button to unselect the option
ttk.Button(self.option_frame_left, text="Unselect data", command=self.clear_option_selection).grid(pady=10)
self.switch_state = True
self.toggle_button = tk.Button(self.option_frame_left, text="STATIC", command=self.toggle_switch)
self.toggle_button.grid(row=6, column=1, pady=10)
self.switch_label = tk.Label(self.option_frame_left, text="STATIC", bg="red", width=10)
self.switch_label.grid(row=6, column=2, pady=10)
self.update_switch_label()
# Create frame for the option selection on the right
self.option_frame_right = ttk.Frame(root)
self.option_frame_right.pack(side="right", padx=20, pady=20)
"""# Button to unselect the option
ttk.Button(self.option_frame_right, text="Unselect Option", command=self.clear_option_selection).grid(row=0, column=0, padx=5, pady=5)
# Label for the option selection
ttk.Label(self.option_frame_right, text="Select Option 1:").grid(row=1, column=0, padx=5, pady=5)
# Combobox for Option 1
self.option1_var = tk.StringVar()
self.option1_combo = ttk.Combobox(self.option_frame_right, textvariable=self.option1_var, state="readonly")
self.option1_combo.grid(row=1, column=1, padx=5, pady=5)
self.option1_combo['values'] = ('Option 1.1', 'Option 1.2', 'Option 1.3')
# Button to select the folder based on the options
ttk.Button(root, text="Select Folder", command=self.select_folder).pack(pady=10)
"""
self.start_button = ttk.Button(self.option_frame_right, text="Start VO", command=self.start_vo)
self.start_button.pack(pady=5)
self.pause_button = tk.Button(self.option_frame_right, text="Pause VO", command=self.pause_vo, state=tk.DISABLED)
self.pause_button.pack(pady=5)
self.stop_button = tk.Button(self.option_frame_right, text="Stop VO", command=self.stop_vo, state=tk.DISABLED)
self.stop_button.pack(pady=5)
# Label for the option selection
# ttk.Label(self.option_frame, text="Select Option 1:").grid(row=0, column=0, padx=5, pady=5)
self.status_label = tk.Label(root, text="")
self.status_label.pack(pady=5)
# Input parameters
self.param_label = tk.Label(root, text="Input Parameters:")
self.param_label.pack(pady=5)
# Initial values for parameters
initial_param1 = 500 # number of features
initial_param2 = 5 # window size
initial_param3 = 5 # level
initial_param4 = 70 # iteration
initial_param5 = 3 # inlier threshold
self.param1_label = tk.Label(root, text="Number of Features:")
self.param1_label.pack()
self.param1_entry = tk.Entry(root)
self.param1_entry.insert(0, initial_param1) # Set initial value
self.param1_entry.pack()
self.param2_label = tk.Label(root, text="Optical Flow window size:")
self.param2_label.pack()
self.param2_entry = tk.Entry(root)
self.param2_entry.insert(0, initial_param2) # Set initial value
self.param2_entry.pack()
self.param3_label = tk.Label(root, text="level of Pyramid:")
self.param3_label.pack()
self.param3_entry = tk.Entry(root)
self.param3_entry.insert(0, initial_param3) # Set initial value
self.param3_entry.pack()
self.param4_label = tk.Label(root, text="Number of Iteration:")
self.param4_label.pack()
self.param4_entry = tk.Entry(root)
self.param4_entry.insert(0, initial_param4) # Set initial value
self.param4_entry.pack()
self.param5_label = tk.Label(root, text="Inlier Threshold:")
self.param5_label.pack()
self.param5_entry = tk.Entry(root)
self.param5_entry.insert(0, initial_param5) # Set initial value
self.param5_entry.pack()
# Initialize thread variables
self.vo_thread = None
self.running = False
self.pause = False
self.stop = False
self.time = time.time()
self.folder_path = " "
#self.q = queue.Queue()
# Add more entry fields for additional parameters as needed
def clear_option_selection(self):
self.option1_var.set("")
self.option2_var.set("")
self.option3_var.set("")
def update_progress_bar(self, progress_percent, shared_data):
self.progress_bar['value'] = progress_percent
self.root.update_idletasks()
speed = shared_data[2]
self.progress_var = progress_percent
progress_percent = "{:.0f}".format(progress_percent)
speed = "{:.2f}".format(speed)
self.percentage_label.config(text=f"Progress: {progress_percent}%")
self.speed_label.config(text=f"Speed: {speed} Frames/sec")
def toggle_switch(self):
# global switch_state
self.switch_state = not self.switch_state
self.update_switch_label()
def update_switch_label(self):
if self.switch_state:
self.switch_label.config(text="ON", bg="green")
else:
self.switch_label.config(text="OFF", bg="red")
def start_vo(self):
if self.vo_thread is None or not self.vo_thread.is_alive():
self.running = True
self.stop = False
self.pause = False
self.time = time.time()
# Create a queue
q = queue.Queue()
# print("Queue created")
ground_truth = []
monocular_vo = []
param1 = self.param1_entry.get()
param2 = self.param2_entry.get()
param3 = self.param3_entry.get()
param4 = self.param4_entry.get()
param5 = self.param5_entry.get()
# Get input parameters from entry fields
self.start_button.config(state=tk.DISABLED)
self.pause_button.config(state=tk.NORMAL)
self.stop_button.config(state=tk.NORMAL)
self.status_label.config(text="VO Running...")
# Get selected options
option1 = self.option1_var.get()
option2 = self.option2_var.get()
option3 = self.option3_var.get()
if option1:
self.folder_path = "data/Tello_dataset/" + option1
elif option2:
self.folder_path = "data/Kitti_dataset/" + option2
elif option3 :
self.folder_path = "data/UE_dataset/" + option3
#ue_data = "Monocular-Visual-Odometry/data/UE_virtual_data/" + option3
#print(folder_path)
#print(option1,option2,option3)
# Construct the folder path based on selected options
#folder_path = os.path.join("vo_package", option1, option2, option3)
# Check if the folder exists
if not os.path.exists(self.folder_path):
tk.messagebox.showerror("Error", "Selected folder does not exist.")
self.stop_vo()
# Run VO in a separate thread with input parameters
if self.running:
self.vo_thread = threading.Thread(target=self.run_vo, args=(q, ground_truth, monocular_vo, param1, param2, param3, param4, param5,self.folder_path))
self.vo_thread.daemon = True
self.vo_thread.start()
#print(self.running)
#time.sleep(10)
while self.running:
if self.pause_button.cget("state") != "normal":
self.pause_vo()
elif self.stop_button.cget("state") != "normal":
self.stop_vo()
else :
try:
# Update progress bar
shared_data = q.get(timeout=0.1)
progress_percent = (shared_data[0]+ 1) * 100 / shared_data[1]
# print(progress_percent, shared_data)
self.update_progress_bar(progress_percent, shared_data)
#print(self.pause_button.cget("state"))
state = [self.pause_button.cget("state"), self.stop_button.cget("state")]
except queue.Empty:
# Queue is empty
# print("No data available")
if not self.running or not self.vo_thread.is_alive() or self.stop_button.cget("state") != "normal" :
self.vo_finished()
break # Exit loop if thread has finished
def pause_vo(self):
# Implement pause functionality here
self.pause = True
pass
def stop_vo(self):
#print("In stop")
self.running = False
self.stop = True
self.pause_button.config(state=tk.DISABLED)
self.stop_button.config(state=tk.DISABLED)
self.start_button.config(state=tk.NORMAL)
self.update_progress_bar(0)
self.status_label.config(text="VO Stopped")
root.mainloop()
def run_vo(self, q, ground_truth, monocular_vo, param1, param2, param3, param4, param5, folder_path):
# Your Visual Odometry logic goes here
# Example: your_vo_module.run_vo(param1, param2)
# print("Queue is here")
visual_odometry.main(q, folder_path, ground_truth, monocular_vo, int(param1), int(param2), int(param3), int(param4), float(param5), self.switch_state,)
# Close all openCV windows
cv2.destroyAllWindows()
# plt.close('all')
"""---------------- Hand Eye Callibration -------------"""
gt_3d = np.array(ground_truth)
gt_path_3d = gt_3d[:,3:]
gt_rot_vec = gt_3d[:,:3]
estimated_3d = np.array(monocular_vo)
estimated_path_3d = estimated_3d [:,3:]
estimated_rot_vec = estimated_3d[:,:3]
vo_to_rotate = np.copy(estimated_path_3d - gt_path_3d[0])
# est_rot_matrix, _ = cv2.Rodrigues(estimated_rot_vec)
# gt_rot_matrix, _ = cv2.Rodrigues(gt_rot_vec)
rotate_matrix = []
for i in range(len(estimated_rot_vec)):
R, _ = cv2.Rodrigues(estimated_rot_vec[i]-gt_rot_vec[0])
rotate_matrix.append(R) # for i in range(len(estimated_rot_vec))]
# print(estimated_rot_vec[i])
rotate_matrix = np.array(rotate_matrix)
hec_angles = np.array([np.radians(-3.7582), np.radians(12.5854), np.radians(4.9001)])
hec_translation = np.array([-0.9762, 7.7199, -3.6327])/100
if "UE" in self.folder_path:
noise = np.random.normal(0,0.01,3*len(vo_to_rotate[21:]))
noise = noise.reshape((len(vo_to_rotate)-21,3))
vo_to_rotate[21:] += noise
hec_rotation_matrix = Rotation.from_euler('xyz', [-90, 0, 90], degrees=True) #[-4, 12.5, 5], degrees=True)
# hec_rotation_matrix = Rotation.from_euler('xyz', [90, 0, -90], degrees=True)
elif "Tello" in self.folder_path:
hec_rotation_matrix = Rotation.from_euler('xyz', [0, 190, 170], degrees=True) #cv2.Rodrigues(hec_angles)[0]
# hec_rotation_matrix = Rotation.from_euler('xyz', [0, 180, -45], degrees=True)
else:
hec_rotation_matrix = Rotation.from_euler('xyz', [0, 0, 0], degrees=True)
hec_rotation_matrix = hec_rotation_matrix.as_matrix()
vo_to_rotate = vo_to_rotate[:,:,np.newaxis]
vo_rotated = hec_rotation_matrix@vo_to_rotate
rotate_matrix_ = rotate_matrix
estimated_path_3d = np.squeeze(vo_rotated, axis=2)
estimated_path_3d = np.copy(estimated_path_3d + gt_path_3d[0])
estimated_rot_vec = []
for i in range(len(rotate_matrix_)):
R, _ = cv2.Rodrigues(rotate_matrix_[i])
estimated_rot_vec.append((R[0][0],R[1][0],R[2][0]))
estimated_rot_vec = estimated_rot_vec + gt_rot_vec[0]
# estimated_path_3d[1:] = estimated_path_3d[1:] # + np.array([0,0,0.18])
dist_gt = np.zeros(len(gt_path_3d))
dist_gt[1:] = np.linalg.norm(gt_path_3d[1:] - gt_path_3d[:-1], axis=1)
for i in range(1,len(dist_gt)):
dist_gt[i] += dist_gt[i-1]
dist_vo = np.linalg.norm(estimated_path_3d, axis=1)
errors = np.linalg.norm(gt_path_3d - estimated_path_3d, axis=1)
error_per = 100* errors[1:] / dist_gt[1:]
rmse = np.sqrt(np.mean(np.square(errors)))
rmse_p = np.sqrt(np.mean(np.square(error_per)))
std = np.std(errors)
err_max = np.max(dist_gt)
err_min = np.min(dist_gt)
# per_rms = 100*rmse/(err_max-err_min)
print("RMS Error:", "{: .4f}".format(rmse)+"m"," Mean Error:", "{: .4f}".format(np.mean(errors))+"m", "Standard devistion of errors:", "{: .4f}".format(std)+"m","% RMSE:", "{: .2f}".format(rmse_p)+"%")
# Specify the file name
# file_name = self.folder_path+"/error/Q/"+"angledynamics_error_1.npy"
# file_name1 = self.folder_path+"/error/"+"750dynamics_%error_.npy"
# gt = self.folder_path+"/error/"+"gt.npy"
# Save the array to a file
# np.save(file_name, errors)
# np.save(file_name1, error_per)
# np.save(gt, dist_gt)
"""-----------Plot the Results to view the estimated path alongside the ground truth----------"""
# Create a figure and two subplots
#fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 5))
ax = plt.figure().add_subplot(projection='3d')
ax.plot(estimated_path_3d[:,2],estimated_path_3d[:,0],estimated_path_3d[:,1],label='Visual Odometry')
ax.plot(gt_path_3d[:,2],gt_path_3d[:,0],gt_path_3d[:,1],label='Ground Truth')
#plt.grid()
ax.legend()
ax.set_xlabel("z")
ax.set_ylabel("x")
ax.set_zlabel("y")
#plt.show()
#plt.close('all')
# Create a figure and two subplots
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
# Plot the first graph on the first subplot
ax1.plot(dist_gt, errors)
ax1.set_title('Error measurment')
ax1.set_ylabel("Error in m")
ax1.set_xlabel("Ground truth in m")
ax1.grid()
# Plot the second graph on the second subplot
ax2.plot(dist_gt[3:], error_per[2:])
ax2.set_title('Error %')
ax2.set_ylabel("Error in %")
ax2.set_xlabel("Ground truth in m")
ax2.grid()
gig, (bx1, bx2, bx3) = plt.subplots(1, 3, figsize=(12, 5))
estimated_rot_vec = np.degrees(estimated_rot_vec)
gt_rot_vec = np.degrees(gt_rot_vec)
# errors = gt_rot - estimated_rot
# Plot the first graph on the first subplot
bx1.plot(dist_gt, gt_rot_vec[:,0], label='GT roll')#-estimated_rot[:,2])
bx1.plot(dist_gt, estimated_rot_vec[:,0], label='VO roll')
# bx1.set_title('Error measurment')
bx1.set_ylabel("Rotation in degrees")
bx1.set_xlabel("distance covered in m")
bx1.grid()
# Plot the second graph on the second subplot
bx2.plot(dist_gt, gt_rot_vec[:,1], label='GT Pitch')
bx2.plot(dist_gt, estimated_rot_vec[:,1], label='VO Pitch')
# bx1.set_ylabel("Rotation in degree")
# bx1.set_xlabel("distance covered in m")
bx2.grid()
bx2.legend()
# Plot the second graph on the second subplot
bx3.plot(dist_gt, gt_rot_vec[:,2], label='GT Yaw')
bx3.plot(dist_gt, estimated_rot_vec[:,2], label='VO Yaw')
# bx3.set_title('Error %')
# bx3.set_ylabel("Error in %")
# bx3.set_xlabel("Ground truth in m")
bx3.grid()
bx3.legend()
'''
# Plot the third graph on the second subplot
ax3.plot(range(1,len(distance_error_z)+1), distance_error_z)
ax3.set_title('Error in Z axis')
ax4.plot(range(len(error_per)), error_per)
ax4.set_title('Error percentage')'''
hig, (cx1, cx2, cx3) = plt.subplots(1, 3, figsize=(12, 5))
err = gt_rot_vec[:,0]-estimated_rot_vec[:,0]
gx,cx,pre_err = regression(dist_gt, err)
cx1.plot(dist_gt,err,label='Error')
cx1.plot(dist_gt,pre_err, label='Predicted Model')
# cx1.set_title('Error measurment')
cx1.set_ylabel("Rotation Error X in degrees")
cx1.set_xlabel("distance covered in m")
cx1.legend()
cx1.grid()
# Plot the second graph on the second subplot
err = gt_rot_vec[:,1]-estimated_rot_vec[:,1]
gy,cy,pre_err = regression(dist_gt, err)
cx2.plot(dist_gt,err,label='Error')
cx2.plot(dist_gt,pre_err, label='Predicted Model')
# cx2.set_title('Error measurment')
cx2.set_ylabel("Rotation Error Y in degrees")
# cx1.set_xlabel("distance covered in m")
cx2.legend()
cx2.grid()
# Plot the second graph on the second subplot
err = gt_rot_vec[:,2]-estimated_rot_vec[:,2]
gz,cz,pre_err = regression(dist_gt, err)
cx3.plot(dist_gt,err,label='Error')
cx3.plot(dist_gt,pre_err, label='Predicted Model')
# cx3.plot(dist_gt, gt_rot_vec[:,2]-estimated_rot_vec[:,2])
# cx1.set_title('Error measurment')
cx3.set_ylabel("Rotation Error Z in degrees")
# cx3.set_xlabel("distance covered in m")
cx3.legend()
cx3.grid()
print(gx,cx,gy,cy,gz,cz)
# Add labels and title to the entire figure
fig.suptitle('Translation Error Measurements')
hig.suptitle('Rotational Error Measurements ')
gig.suptitle('Rotational Motion ')
plt.show()
# Update GUI after VO finishes
# self.vo_finished()
# self.root.after(0, self.vo_finished())
def vo_finished(self):
self.start_button.config(state=tk.NORMAL)
self.pause_button.config(state=tk.DISABLED)
self.stop_button.config(state=tk.DISABLED)
self.status_label.config(text="VO Finished")
root.mainloop()
if __name__ == "__main__":
root = tk.Tk()
app = VOApp(root)
root.mainloop()