This is a clean and reproducible Colab-based reimplementation of Stability AI's TripoSR — a powerful zero-shot model that generates 3D object meshes from a single 2D image.

Built on top of the PyImageSearch blog tutorial, this notebook integrates:

• 2D input image upload
• Background removal via rembg
• Inference using TripoSR via Hugging Face
• 360° turntable render output
• Mesh export in .obj format

• Zero-shot inference: No need for fine-tuning — just drop an image and get a 3D model
• Background cleanup: Uses rembg for cleaner foreground object extraction
• Smooth renders: Generates 30-angle renders + MP4 video
• Mesh export: Outputs ready-to-use 3D .obj files

1. Open the Colab notebook

   ▶️ Click here to run in Colab

2. Upload an image (preferably product-style or with clear foreground)

3. Run all cells
   Sit back and let the notebook:

   • Process the image
   • Run the TripoSR model
   • Render 360° views
   • Export a .obj 3D mesh

4. Preview your result!
   A video preview will auto-play inside the notebook 🎬

After running the notebook, your output/ folder will look like this:

output/
└── 0/
├── input.png # Processed input image
├── render_000.png # 30 rendered views
├── render_001.png
├── ...
├── render.mp4 # Turntable video
└── mesh.obj # Exported mesh

• TripoSR on Hugging Face
• Original PyImageSearch tutorial
• Paper: TripoSR: Ultra-Fast 3D Reconstruction from a Single Image

• Wrap this into an end-to-end web app
• Dockerize for easier deployment
• Add sample gallery + download links