Driving Video MaxFrame Job

Overview

Generate customer-neutral MaxFrame job scaffolds for driving-video workflows. Frame extraction uses an ffmpeg-based mf.apply_chunk UDF (with with_fs_mount + with_running_options); image labeling and embedding use AI FUNC multi-modal models loaded via read_odps_model. Keep all stages in one lazy DAG by default and externalize all runtime settings.

When to Use

• Building a video manifest table by scanning OSS, when the customer has videos sitting in OSS but no inventory table yet (Stage 0)
• Frame extraction from in-car / cabin / dashcam / road-test video tables
• Clip-to-keyframe labeling pipelines (clip_dir_table → keyframe rows → labels)
• Image labeling jobs, including direct-image requests that ask for labeling plus embedding outputs
• Image / multi-modal embedding jobs derived from image workflows