This pull request introduces several improvements and fixes to the PRIMA demo, focusing on better progress reporting in the Gradio interface, improved OpenGL backend selection for rendering, consistent checkpoint naming, and enhanced checkpoint validation. It also updates documentation and example scripts to reflect these changes.

User experience and progress reporting:

• Added real-time progress updates to the Gradio demo by introducing a progress_callback mechanism in _collect_animal_results, which reports the current processing stage (e.g., detection, rendering, TTA) to the user. This makes long-running inferences more transparent and user-friendly. (app.py) [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12]

Rendering and environment compatibility:

• Improved OpenGL backend selection for headless environments by preferring EGL over OSMesa when available, increasing compatibility with pyrender and reducing rendering errors in cloud or containerized deployments. (prima/utils/mesh_renderer.py, prima/utils/renderer.py) [1] [2]

Checkpoint management and validation:

• Standardized Stage 3 checkpoint naming to s3ckpt_inference.ckpt throughout the codebase, scripts, and documentation for consistency and to avoid confusion. (prima/utils/weights.py, demo.sh, demo_tta.sh, README.md) [1] [2] [3] [4] [5] [6]
• Enhanced checkpoint validation by checking for corrupt zip members and supporting the new weights_only argument in torch.load for more robust and informative error handling. (prima/utils/weights.py)

Documentation and examples:

• Updated documentation to reflect the new checkpoint naming and added a reference to the SAM3DB project. (README.md) [1] [2]
• Adjusted Gradio example parameters and default TTA iterations for a better out-of-the-box experience. (app.py) [1] [2]
• Ensured the model is moved to the correct device in evaluation scripts. (eval.py)
• Set minimum Python version to 3.10 in the project metadata. (pyproject.toml)