From 36a035cf659f3235116d58b7466024bd1b436b36 Mon Sep 17 00:00:00 2001 From: Olanrewaju Muili Date: Mon, 29 Apr 2024 18:19:27 -0500 Subject: [PATCH 1/6] Add 3D point cloud visualizer and sample image files --- script/3d_point_cloud_visualizer.py | 100 ++++++++++++++++++++++++++++ 1 file changed, 100 insertions(+) create mode 100644 script/3d_point_cloud_visualizer.py diff --git a/script/3d_point_cloud_visualizer.py b/script/3d_point_cloud_visualizer.py new file mode 100644 index 0000000..d860d7d --- /dev/null +++ b/script/3d_point_cloud_visualizer.py @@ -0,0 +1,100 @@ +import open3d as o3d +import numpy as np +import tkinter as tk +from tkinter import filedialog, messagebox +import matplotlib.pyplot as plt + +def apply_color_by_attribute(cloud, attribute): + colors = plt.get_cmap('viridis')(attribute)[:, :3] + cloud.colors = o3d.utility.Vector3dVector(colors) + +def voxel_downsample(cloud, voxel_size=0.05): + return cloud.voxel_down_sample(voxel_size) + +def compute_statistics(cloud, options): + results = {} + points = np.asarray(cloud.points) + + if options['mean']: + results['mean'] = np.mean(points, axis=0) + if options['standard_deviation']: + results['standard_deviation'] = np.std(points, axis=0) + + if options['density']: + bounding_box = cloud.get_axis_aligned_bounding_box() + volume = bounding_box.volume() + results['density'] = len(points) / volume if volume > 0 else 0 + + return results + +def compute_geometric_properties(cloud, options): + results = {} + + if options['centroid']: + results['centroid'] = cloud.get_center() + if options['bounding_box']: + bounding_box = cloud.get_axis_aligned_bounding_box() + results['bounding_box'] = str(bounding_box) + results['volume'] = bounding_box.volume() + + return results + +def visualize_ply(file_path, downsample=False, color_map=None, stats_options=None, geom_options=None): + cloud = o3d.io.read_point_cloud(file_path) + if downsample: + cloud = voxel_downsample(cloud) + + if color_map == 'depth' and cloud.has_points(): + zs = np.asarray(cloud.points)[:, 2] + zs_normalized = (zs - zs.min()) / (zs.max() - zs.min()) + apply_color_by_attribute(cloud, zs_normalized) + + stats_results = compute_statistics(cloud, stats_options) + geom_results = compute_geometric_properties(cloud, geom_options) + + o3d.visualization.draw_geometries([cloud]) + + output_info = '\n'.join([f"{key}: {value}" for key, value in {**stats_results, **geom_results}.items()]) + messagebox.showinfo("Point Cloud Analysis Results", output_info) + +def gui(): + root = tk.Tk() + root.title("3D Point Cloud Visualizer") + root.geometry("400x400") + + downsample_var = tk.BooleanVar() + color_map_var = tk.StringVar(value='none') + + open_button = tk.Button(root, text="Open PLY File", command=lambda: open_file_dialog()) + open_button.pack(pady=10) + + downsample_check = tk.Checkbutton(root, text="Apply Downsampling", variable=downsample_var) + downsample_check.pack(anchor='w') + + color_map_label = tk.Label(root, text="Color Map:") + color_map_label.pack(anchor='w') + + color_map_menu = tk.OptionMenu(root, color_map_var, 'none', 'depth') + color_map_menu.pack(anchor='w') + + # Options for statistics and geometric properties + stats_options = {'mean': tk.BooleanVar(), 'standard_deviation': tk.BooleanVar(), 'density': tk.BooleanVar()} + geom_options = {'centroid': tk.BooleanVar(), 'bounding_box': tk.BooleanVar(), 'volume': tk.BooleanVar()} + + # Creating checkboxes for each option + for key in stats_options: + tk.Checkbutton(root, text=f"{key.replace('_', ' ').title()}", variable=stats_options[key]).pack(anchor='w') + for key in geom_options: + tk.Checkbutton(root, text=f" {key.replace('_', ' ').title()}", variable=geom_options[key]).pack(anchor='w') + + def open_file_dialog(): + file_path = filedialog.askopenfilename(title='Select a PLY File', filetypes=[('PLY Files', '*.ply')]) + if file_path: + visualize_ply(file_path, downsample_var.get(), color_map_var.get(), + {k: v.get() for k, v in stats_options.items()}, + {k: v.get() for k, v in geom_options.items()}) + + root.mainloop() + +if __name__ == "__main__": + gui() From a3557ea4d19fd7eb65e208a9ff72745f44dc21ee Mon Sep 17 00:00:00 2001 From: Olanrewaju Muili Date: Mon, 29 Apr 2024 18:20:32 -0500 Subject: [PATCH 2/6] Add 3D point cloud visualizer and sample image files --- script/image1.png | Bin 0 -> 19084 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 script/image1.png diff --git a/script/image1.png b/script/image1.png new file mode 100644 index 0000000000000000000000000000000000000000..f17ee5364f64b54f8b24fe7b684bb90ad6475132 GIT binary patch literal 19084 zcmbTdWl&sQumu_-uE7U)3xm7c1M=Nl zx9ZjV^QZ#m%$zyeVZBSs6){SFd1qo?fpYAw2z6H<8$W z`Um5vA}#)^e39s5R{OXn58(B#) zH8=hJ#Y;_fom@7zUg*Jc!=oRC-I?clv(Ng4r`}~tx#wX?v5qryrW$>+BSB(5&TIJo zPyJNwk>SP&c(e?#uqX^N36VIGw017hNBh605HP3;chvaQi7re@_r6n6lzjRT#Uq_YA`|pRNB>w>RBn+Cp2-#SZdFPr8@E~PB$^5f z4Gnz=zHpcB99}O%+FLz~^`tMNiVpU$~v`1;y0muP>)N 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Click `Open PLY File` to load your point cloud data. +2. Select options for downsampling and color mapping as needed. +3. Choose the statistical and geometric properties you wish to calculate. +4. View the results and visualizations immediately. + +## Contributing + +We welcome contributions to this project! Please consider the following steps: + + +## License + +Distributed under the MIT License. See `LICENSE` for more information.