v0.1.4 release

pypi version: 0.1.4

Bug fixes

• Fix OOM error in aesthetic_quality dimension (1a213e4)

Features

• Support inference with multi-gpu using torchrun, see usage in README.md (fc4620b)
• vbench evaluate command to support launching multi-gpu inference (e3e6664)

VBench v0.1.2

Bug fixes

• Fix preprocessing for high-resolution images/videos in imaging_quality (46275d9, b484867)
• Fix VBench_full_info.json not found in PyPI package (90f0973)

Features

• Add filter_scope argument for selecting the videos to be considered for filtering out static videos (fb75b02)
• Add mode argument to select between three different evaluation modes (02e2ee1):

custom_input: Receive input prompt from --prompt/--prompt_file flags or read directly from the filename
vbench_standard: Evaluate using the standard prompt suite of VBench (default)
vbench_category: Evaluate using a specific category of VBench

• Allow evaluating with prompts specified by a file containing a dictionary using --prompt_file. (efaa6d3)

Others Changes

• Receive list of dimension instead of single dimension in --dimension flag (91bece8)

v0.1.1 release

This release contains:

• Pretrained model weights for all 16 T2V evaluation dimensions
• VBench prompt suite for T2V
• Source code for evaluating all 16 T2V dimensions
• vbench evaluate command to evaluate T2V on vbench prompt suite (cc68b18)
• static_filter command for filtering out static videos (for temporal flickering dimension) (fd3613a)