Read, load and convert to standard file types with a common interface. Especially useful for code that works with multiple file types like images, audio, video, etc.
Load and convert from and to common data types:
- numpy arrays
- file paths
- bytes,
- base64
- json
- urls
- etc.
Transmit files between services with a common interface
- Native FastSDK and FastTaskAPI integration
- Supports httpx, requests
Work with native python libs like BytesIO.
Only use the file types you need, no unnecessary dependencies.
You can install the package with PIP, or clone the repository.
# install from pypi
pip install media-toolkit
# install without dependencies: this is useful if you only need the basic functionality (working with files)
pip install media-toolkit --no-deps
# if you want to use certain file types, and convenience functions
pip install media-toolkit[VideoFile] # or [AudioFile, VideoFile, ...]
# install from github for newest release
pip install git+git://github.com/SocAIty/media-toolkit
The package checks if you have missing dependencies for certain file types while using.
Use the --no-deps
flag for a minimal tiny pure python installation.
The package with dependencies is quite small < 39kb itself.
Note: for VideoFile you will also need to install ffmpeg
The library automatically detects the data type and loads it correctly.
from media_toolkit import MediaFile, ImageFile, AudioFile, VideoFile
# could be a path, url, base64, bytesio, file_handle, numpy array ...
arbitrary_data = "...."
# Instantiate an image file
new_file = ImageFile().from_any(arbitrary_data)
All files (ImageFile, AudioFile, VideoFile)
types support the same interface / methods.
This method is more secure than from_any, because it definitely uses the correct method to load the file.
new_file = MediaFile()
new_file.from_file("path/to/file")
new_file.from_file(open("path/to/file", "rb"))
new_file.from_numpy_array(my_array)
new_file.from_bytes(b'bytes')
new_file.from_base64('base64string')
new_file.from_starlette_upload_file(starlette_upload_file)
Supports common serialization methods like bytes(), np.array(), dict()
my_file = ImageFile().from_file("path/to/my_image.png")
my_file.save("path/to/new_file.png")
as_numpy_array = my_file.to_numpy_array()
as_numpy_array = np.array(my_file)
as_bytes = my_file.to_bytes()
as_bytes = bytes(my_file)
as_base64 = my_file.to_base64()
as_json = my_file.to_json()
The VideoFiles wrap the famous vidgear package as well as pydub. VideoFiles support extra methods like audio extraction, combining video and audio. Vidgear is a powerful video processing library that supports many video formats and codecs and is known for fast video processing.
# load the video file
vf = VideoFile().from_file("test_files/test_vid_1.mp4")
# extract audio_file
vf.extract_audio("extracted_audio.mp3")
# stream the video
for img, audio in vf.to_video_stream(include_audio=True):
cv2.imwrite("outtest.png", img)
# add audio to an videofile (supports files and numpy.array)
vf.add_audio("path/to/audio.mp3")
# create a video from a folder
VideoFile().from_dir("path/to/image_folder", audio=f"extracted_audio.mp3", frame_rate=30)
# create a video from a video stream
fromstream = VideoFile().from_video_stream(vf.to_video_stream(include_audio=True))
We intent to make transmitting files between services as easy as possible. Here are some examples for services and clients.
The library supports the FastTaskAPI and FastSDK for easy file transmission between services. Simply use the files in the task_endpoint function definition and transmitted data will be converted. Check out the FastTaskAPI documentation for more information.
from fast_task_api import ImageFile, AudioFile, VideoFile
@app.task_endpoint("/my_file_upload")
def my_upload_image(image: ImageFile, audio: AudioFile, video: VideoFile):
image_as_np_array = np.array(image)
You can use the files in fastapi and transform the starlette upload file to a MediaFile.
@app.post("/upload")
async def upload_file(file: UploadFile = File(...)):
mf = ImageFile().from_starlette_upload_file(file)
return {"filename": file.filename}
To send a MediaFile to an openapi endpoint you can use the following method:
import httpx
my_media_file = ImageFile().from_file("path/to/my_image.png")
my_files = {
"param_name": my_media_file.to_httpx_send_able_tuple()
...
}
response = httpx.Client().post(url, files=my_files)
If media-file is instantiated with from_*
it converts it to an intermediate representation.
The to_*
methods then convert it to the desired format.
Currently the intermediate representation is supported in memory with (BytesIO).
- additionally support tempfile backend instead of working bytesio memory mode only.
- decreasing redundancies for _file_info() method