ffmpeg/README.md

# Operator: video-decoder

Author: JunJie Jiang

## Overview



## Interface

```python
__init__(self, start_time=None, end_time=None, sample_type=None, args=None)


Args:

- start_time: float

- end_time: float

  decode video from start_time to end_time

-  sample_type: str
  
        uniform_temporal_subsample
        time_step_sample

-  args: dict
   sample_type is `uniform_temporal_subsample`
      num_samples: int

   sample_type is `time_step_sample`
      time_step: int
    
```      


```python
__call__(self, video_path: str)
```

Args:

- video_path:
  support local path and http/https url.

Returns:

- towhee.types.VideoFrame

## Requirements
av


## How it works
```python
from towhee import pipe, ops, DataCollection

p = (
    pipe.input('video_file')
    .flat_map('video_file', 'frame', ops.video_decode.ffmpeg(start_time=10.0, end_time=15.0, sample_type='time_step_sample', args={'time_step': 1}))
    .output('frame')
)

DataCollection(p('./video.mp4')).show(limit=1)
```

```python
from towhee import ops

d = ops.video_decode.ffmpeg(start_time=10.0, end_time=20.0, sample_type='uniform_temporal_subsample', args={'num_samples': 10})
for frame in d(video_path):
    print(frame)

print('#' * 50)

d = ops.video_decode.ffmpeg(start_time=10.0, end_time=20.0, sample_type='time_step_sample', args={'time_step': 1})
for frame in d(video_path):
    print(frame)


result:
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 10010, key_frame: 1
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 11078, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 12145, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 13280, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 14348, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 15482, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 16550, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 17684, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 18752, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 19887, key_frame: 0
##################################################
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 10010, key_frame: 1
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 11011, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 12012, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 13013, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 14014, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 15015, key_frame: 1
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 16015, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 17017, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 18018, key_frame: 0
VideoFrame shape: (360, 480, 3), mode: RGB, timestamp: 19019, key_frame: 0



## Reference



# More Resources

- [Scalar Quantization and Product Quantization - Zilliz blog](https://zilliz.com/learn/scalar-quantization-and-product-quantization): A hands-on dive into scalar quantization (integer quantization) and product quantization with Python.
- [Multimodal RAG with Milvus and GPT-4o](https://zilliz.com/event/multimodal-rag-with-milvus-and-gpt-4o/success): Join us for a webinar for a demo of multimodal RAG with Milvus and GPT-4o
- [Building a Video Analysis System with Milvus Vector Database - Zilliz blog](https://zilliz.com/blog/milvus-helps-analyze-videos-intelligently): Learn how Milvus powers the AI analysis of video content.
- [Multimodal RAG with Milvus and GPT-4o](https://zilliz.com/event/multimodal-rag-with-milvus-and-gpt-4o): Join us for a webinar for a demo of multimodal RAG with Milvus and GPT-4o
- [4 Steps to Building a Video Search System - Zilliz blog](https://zilliz.com/blog/building-video-search-system-with-milvus): Searching for videos by image with Milvus