Cara Membuat Ruang Awan Titik 3D Sintetis dengan Label (Tutorial Python)

In this tutorial, I show how to generate unlimited synthetic 3D point cloud rooms with perfect semantic labels using simple Python code. I cover generating basic 3D shapes (plane, sphere, cube), building a complete room environment, adding realistic noise patterns, assigning perfect semantic labels, visualizing results with color coding, exporting to industry‑standard PLY format, and using the synthetic data for machine learning training. The approach is useful for training segmentation algorithms, testing robotics systems, computer vision development, generating unlimited variations, and creating perfect ground truth data. TIMESTAMPS: [00:00] Masalah dengan data 3D dunia nyata [02:05] Kotak Alat [02:57] Alur Kerja [04:46] Membuat bentuk geometris dasar [11:10] Merakit lingkungan ruangan yang lengkap [12:05] Menambahkan label semantik secara otomatis [12:54] Mengekspor ke format PLY standar industri [14:12] Memvisualisasikan hasil dengan Open3D [15:45] Menggunakan data sintetis untuk pelatihan ML [18:05] Visualisasi 3D dengan Perangkat Lunak [19:45] Unduh kode lengkap