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--- |
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license: apache-2.0 |
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task_categories: |
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- text-to-video |
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language: |
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- en |
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tags: |
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- data-juicer |
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- multimodal |
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- text-to-video |
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--- |
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# <span style="font-family: 'Courier New', monospace; font-weight: bold">Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development |
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## Project description |
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The emergence of large-scale multi-modal generative models has drastically advanced artificial intelligence, introducing unprecedented levels of performance and functionality. |
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However, optimizing these models remains challenging due to historically isolated paths of model-centric and data-centric developments, leading to suboptimal outcomes and inefficient resource utilization. |
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In response, we present a novel sandbox suite tailored for integrated data-model co-development. This sandbox provides a comprehensive experimental platform, enabling rapid iteration and insight-driven refinement of both data and models. |
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Our proposed "Probe-Analyze-Refine" workflow, validated through applications on [T2V-Turbo](https://github.com/Ji4chenLi/t2v-turbo) and achieve a new state-of-the-art on [VBench leaderboard](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard) with 1.09% improvement from T2V-Turbo. Our experiment code and model are released at [Data-Juicer Sandbox](https://github.com/modelscope/data-juicer/blob/main/docs/Sandbox.md). |
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## Dataset Information |
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- The whole dataset is available [here](http://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/MM_data/our_refined_data/Data-Juicer-T2V/data_juicer_t2v_optimal_data_pool.zip) (About 227.5GB). |
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- Number of samples: 147,176 (Include videos and keep ~12.09% from the original dataset) |
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- The original dataset totals 1,217k instances from [InternVid](https://github.com/OpenGVLab/InternVideo/tree/main/Data/InternVid) (606k), [Panda-70M](https://github.com/snap-research/Panda-70M) (605k), and [MSR-VTT](https://www.microsoft.com/en-us/research/publication/msr-vtt-a-large-video-description-dataset-for-bridging-video-and-language/) (6k). |
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## Refining Recipe |
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```yaml |
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# global parameters |
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# global parameters |
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project_name: 'Data-Juicer-recipes-T2V-optimal' |
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dataset_path: '/path/to/your/dataset' # path to your dataset directory or file |
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export_path: '/path/to/your/dataset.jsonl' |
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np: 4 # number of subprocess to process your dataset |
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# process schedule |
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# a list of several process operators with their arguments |
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process: |
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- video_nsfw_filter: |
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hf_nsfw_model: Falconsai/nsfw_image_detection |
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score_threshold: 0.000195383 |
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frame_sampling_method: uniform |
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frame_num: 3 |
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reduce_mode: avg |
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any_or_all: any |
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mem_required: '1GB' |
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- video_frames_text_similarity_filter: |
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hf_clip: openai/clip-vit-base-patch32 |
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min_score: 0.306337 |
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max_score: 1.0 |
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frame_sampling_method: uniform |
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frame_num: 3 |
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horizontal_flip: false |
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vertical_flip: false |
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reduce_mode: avg |
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any_or_all: any |
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mem_required: '10GB' |
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``` |
