├── README.md
├── code
    ├── Object detection.py
    ├── Selection of ROI.py
    ├── las to pcd with UI.py
    └── las2pcd.py
└── output
    └── Final output.jpg


/README.md:
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 1 | # Object-Detection-using-LiDAR
 2 | 
 3 | This repo refers to object detection using LiDAR data specifically LAS and LAZ formats.
 4 | 
 5 | Main libraries used in this project: 
 6 | 
 7 |     1. laspy
 8 |     
 9 |     2. Keras
10 |     
11 |     3. pytorch
12 |     
13 |     4. numpy
14 |     
15 |     5. scipy
16 |     
17 |     6. pcl
18 |     
19 | Output is shown below as a jpeg format (screenshot of the output LiDAR .las file)
20 | 
21 | 
22 | 
23 | 
24 | ![Object detection](https://github.com/niranjanreddy891/Object-Detection-using-LiDAR/blob/master/output/Final%20output.jpg)
25 | 
26 | 
27 | Note:
28 | 
29 | 
30 | # In the next release, I want to display the name of the object like person, vehicle, trees and roads by Name if possible to show accuracy in percentage.
31 | 


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/code/Object detection.py:
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 1 | # author: niranjanreddy891@gmail.com
 2 | 
 3 | 
 4 | import numpy as np
 5 | import random
 6 | import scipy as sc
 7 | from laspy import file
 8 | import pcl
 9 | from pcl import pcl_visualization
10 | import tkinter
11 | import tkinter as tk
12 | from tkinter.filedialog import askopenfilename
13 | import tensorflow as tf
14 | import keras
15 | 
16 | def browseFile1():
17 |   global inFile1
18 |   inFile1=askopenfilename()
19 |   txt1.insert(0.0, inFile1)
20 | root = tk.Tk()
21 | root.title("Visualization tool")
22 | Label = tk.Label(root, text="Select a LAS file")
23 | Label.grid(row = 1, column = 0, columnspan = 30)
24 | 
25 | 
26 | browseButton1 = tk.Button(root,text="Browse", command=browseFile1)
27 | browseButton1.grid(row = 2, column = 2)
28 | 
29 | txt1 = tk.Text(root, width = 60, height = 1)
30 | txt1.grid(row = 2, column = 0, columnspan = 2)
31 | 
32 | def on_click():
33 |     f = file.File(inFile1,mode='r')
34 |     ptcloud = np.vstack((f.x, f.y, f.z)).transpose()
35 |     f.close()
36 | 
37 |     # Centred the data
38 |     ptcloud_centred = ptcloud - np.mean(ptcloud, 0)
39 | 
40 |     # Simulate an intensity information between 0 and 1
41 |     ptcloud_centred = sc.append(ptcloud_centred, np.zeros((ptcloud.shape[0], 1)), axis=1)  # Ajout d'une ligne (axis=0)
42 |     for i in range(ptcloud_centred.shape[0] - 1):
43 |         ptcloud_centred[i, 3] = random.random()
44 | 
45 |     p = pcl.PointCloud_PointXYZI()
46 |     p.from_array(np.array(ptcloud_centred, dtype=np.float32))
47 | 
48 |     visual = pcl_visualization.CloudViewing()
49 |     visual.ShowGrayCloud(p)
50 |     def check_was_stopped():
51 |         visual.WasStopped()
52 | 
53 |         root.after(100, check_was_stopped)
54 |     check_was_stopped()
55 | #laspy librairy, read las file
56 | 
57 | label = tk.Label(root)
58 | label.grid()
59 | 
60 | tk.Button(text="Visualize", command=on_click).grid()
61 | 
62 | 
63 | root.geometry('600x130')
64 | root.mainloop()
65 | 


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/code/Selection of ROI.py:
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 1 | # author: niranjanreddy891@gmail.com
 2 | 
 3 | 
 4 | import numpy as np
 5 | import random
 6 | import scipy as sc
 7 | from laspy import file
 8 | import tkinter
 9 | import tkinter as tk
10 | from tkinter.filedialog import askopenfilename
11 | import pclpy
12 | from pclpy import pcl
13 | from tkinter import *
14 | import tensorflow as tf
15 | import keras
16 | 
17 | 
18 | def browseFile1():
19 |   global inFile1
20 |   inFile1=askopenfilename()
21 |   txt1.insert(0.0, inFile1)
22 | root = tk.Tk()
23 | root.title("Selection of ROI")
24 | Label = tk.Label(root, text="Select a LAS/LAZ file")    # both las and laz file support
25 | Label.grid(row = 1, column = 0, columnspan = 30)
26 | 
27 | 
28 | browseButton1 = tk.Button(root,text="Browse", command=browseFile1)
29 | browseButton1.grid(row = 2, column = 2)
30 | 
31 | txt1 = tk.Text(root, width = 80, height = 1)
32 | txt1.grid(row = 2, column = 0, columnspan = 2)
33 | 
34 | def on_click():
35 |     def ROI_window():
36 |         offset = pclpy.io.las.get_offset(inFile1)
37 |         pc = pclpy.io.las.read(inFile1, "PointXYZRGBA", xyz_offset=offset)
38 |         viewer = pcl.visualization.PCLVisualizer("viewer", True)
39 |         viewer.addPointCloud(pc)
40 |         viewer.resetCamera()
41 | 
42 |         viewers = [viewer]
43 | 
44 |         def handle_event_area(event):
45 |             # use x to toggle rectangle selection
46 |             assert isinstance(event, pcl.visualization.AreaPickingEvent)
47 |             indices = pcl.vectors.Int()
48 |             event.getPointsIndices(indices)
49 | 
50 |             other_viewer = pcl.visualization.PCLVisualizer("viewer", True)
51 |             rgb = np.array([pc.r[indices], pc.g[indices], pc.b[indices]]).T
52 |             other_pc = pcl.PointCloud.PointXYZRGBA.from_array(pc.xyz[indices], rgb)
53 |             other_viewer.addPointCloud(other_pc)
54 |             other_viewer.resetCamera()
55 |             viewers.append(other_viewer)
56 | 
57 |         viewer.registerAreaPickingCallback(handle_event_area)
58 | 
59 |         while not all(v.wasStopped() for v in viewers):
60 |             for v in viewers:
61 |                 if not v.wasStopped():
62 |                     v.spinOnce(50)
63 | 
64 |     ROI_window()
65 | 
66 | 
67 | label = tk.Label(root)
68 | label.grid()
69 | 
70 | tk.Button(text="Visualize", command=on_click).grid()
71 | 
72 | 
73 | root.geometry('730x140')
74 | root.mainloop()
75 | 
76 | #############################################################################
77 | 
78 | 


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/code/las to pcd with UI.py:
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 1 | # author: niranjanreddy891@gmail.com
 2 | 
 3 | 
 4 | import numpy as np
 5 | import random
 6 | import scipy as sc
 7 | from laspy import file
 8 | import pcl
 9 | from pcl import pcl_visualization
10 | import tkinter
11 | import tkinter as tk
12 | from tkinter.filedialog import askopenfilename
13 | 
14 | 
15 | def browseFile1():
16 |   global inFile1
17 |   inFile1=askopenfilename()
18 |   txt1.insert(0.0, inFile1)
19 | root = tk.Tk()
20 | root.title("Visualization tool")
21 | Label = tk.Label(root, text="Select a LAS file")
22 | Label.grid(row = 1, column = 0, columnspan = 30)
23 | 
24 | 
25 | browseButton1 = tk.Button(root,text="Browse", command=browseFile1)
26 | browseButton1.grid(row = 2, column = 2)
27 | 
28 | txt1 = tk.Text(root, width = 60, height = 1)
29 | txt1.grid(row = 2, column = 0, columnspan = 2)
30 | 
31 | def on_click():
32 |     f = file.File(inFile1,mode='r')
33 |     ptcloud = np.vstack((f.x, f.y, f.z)).transpose()
34 |     f.close()
35 | 
36 |     # Centred the data
37 |     ptcloud_centred = ptcloud - np.mean(ptcloud, 0)
38 | 
39 |     # Simulate an intensity information between 0 and 1
40 |     ptcloud_centred = sc.append(ptcloud_centred, np.zeros((ptcloud.shape[0], 1)), axis=1)  # Adjusting axis (axis=0)
41 |     for i in range(ptcloud_centred.shape[0] - 1):
42 |         ptcloud_centred[i, 3] = random.random()
43 | 
44 |     p = pcl.PointCloud_PointXYZI()
45 |     p.from_array(np.array(ptcloud_centred, dtype=np.float32))
46 | 
47 |     visual = pcl_visualization.CloudViewing()
48 |     visual.ShowGrayCloud(p)
49 |     def check_was_stopped():
50 |         visual.WasStopped()
51 | 
52 |         root.after(100, check_was_stopped)
53 |     check_was_stopped()
54 | #laspy librairy, read las file
55 | 
56 | label = tk.Label(root)
57 | label.grid()
58 | 
59 | tk.Button(text="Visualize", command=on_click).grid()
60 | 
61 | 
62 | root.geometry('1000x600')
63 | root.mainloop()
64 | 


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/code/las2pcd.py:
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 1 | # author: niranjanreddy891@gmail.com
 2 | 
 3 | 
 4 | from laspy.file import File
 5 | import numpy as np
 6 | 
 7 | inFile = File('E:/Lidar-practice/new-files/las14_type7_ALS_RIEGL_Q680i.las', mode='r')
 8 | 
 9 | I = inFile.Classification == 2
10 | 
11 | outFile = File('E:/Lidar-practice/new-files/tttttttttttt.pcd', mode='w', header=inFile.header)
12 | outFile.points = inFile.points[I]
13 | outFile.close()
14 | 


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/output/Final output.jpg:
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https://raw.githubusercontent.com/niranjanreddy891/Object-Detection-using-LiDAR/8b5e335c0aad80458cd315d5ed1b781dd18ebb12/output/Final output.jpg


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