## OpenVE-Bench [OpenVE-Bench](https://huggingface.co/datasets/Lewandofski/OpenVE-Bench) is a new Instruction-Guided Video Editing benchmark contained 431 video-edit pairs that cover a diverse range of editing tasks with three key metrics highly aligned with human judgment. A folder containing original videos: ```folder ├── OpenVE-Bench │ ├── videos | |── 0000_global_style_Apply_the_Impression.mp4 | |── 0001_global_style_Apply_the_Ukiyoe_ani.mp4 | |── ... │ ├── benchmark_videos.csv ``` `benchmark_videos.csv` contains following fields: ``` edited_type,prompt,original_video ``` ## Generate and Organize Your Videos Following the editing `prompt` in the `benchmark_videos.csv` file and the `original_video`, generate the video results for your model, and record the video paths in a new CSV `new_result.csv` file, adding a `edited_result_path` column at the end. `new_result.csv` should contains following fields: ``` edited_type,prompt,original_video,edited_result_path ``` ## Evaluate using Seed1.6VL/Gemini 2.5 Pro/InternVL3.5-38B/Qwen3VL-32B For Seed1.6VL and Gemini 2.5 Pro, you should set your correct API key. Seed 1.6 VL ```python python seed_benchmark.py --input_csv new_result.csv --root_path yours_OpenVE-Bench_path --output_csv new_result_gemini_score.csv ``` Gemini 2.5 Pro ```python python gemini_benchmark.py --input_csv new_result.csv --root_path yours_OpenVE-Bench_path --output_csv new_result_gemini_score.csv ``` [InternVL3.5-38B](https://huggingface.co/OpenGVLab/InternVL3_5-38B) ```python python internvl_benchmark.py --input_csv new_result.csv --root_path yours_OpenVE-Bench_path --output_csv new_result_gemini_score.csv --model_path /yours_model_path/InternVL3.5-38B ``` [Qwen3VL-32B](https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct) ```python python qwen3vl_benchmark.py --input_csv new_result.csv --root_path yours_OpenVE-Bench_path --output_csv new_result_gemini_score.csv --model_path /yours_model_path/Qwen3VL-32B ``` *The final average metric results are in a JSON file.*