Dev/pxy (#73)

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scoring/matching

* update scene_cut

* update scene_cut

* update scene_cut[A

* update scene_cut

* update scene_cut

* update scene_cut

* update scene_cut

* update scene_cut

* update scene_cut

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* update readme

* update readme

* extract frames using opencv everywhere

* extract frames using opencv everywhere

* extract frames using opencv everywhere

* filter panda10m

* filter panda10m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* m

* ocr

* add ocr

* add main.sh

* add ocr

* add ocr

* add ocr

* add ocr

* add ocr

* add ocr

* update scene_cut

* update remove main.sh

* update scoring

* update scoring

* update scoring

* update README

* update readme

* update scene_cut

* update readme

* update scoring

* update readme

* update readme

* update filter_panda10m

* update readme

* update readme

* update launch.ipynb

* update scene_cut

* update scene_cut

* update readme

* update launch.ipynb

* update readme

README.md

@@ -250,7 +250,7 @@ To lower the memory usage, set a smaller `vae.micro_batch_size` in the config (s
 High-quality data is crucial for training good generation models.
 To this end, we establish a complete pipeline for data processing, which could seamlessly convert raw videos to high-quality video-text pairs.
 The pipeline is shown below. For detailed information, please refer to [data processing](docs/data_processing.md).
-Also check out the [datasets](docs/data_processing.md) we use.
+Also check out the [datasets](docs/datasets.md) we use.
 
 
 ![Data Processing Pipeline](assets/readme/report_data_pipeline.png)