Skip to main content

Python package for easily interfacing with MediaCatch APIs and data formats.

Project description

Unit Tests codecov Quality Check Publish Documentation

MediaCatch

Python package for easily interfacing with MediaCatch APIs and data formats. Documentation can be found at api.mediacatch.io/mediacatch/docs/.

Requirements

Installation

Install with pip

pip install mediacatch

Getting Started

Firstly, add your MediaCatch API key to your environment variables

export MEDIACATCH_API_KEY=<your-api-key-here>

Then you can start using the command line interface

mediacatch --help
usage: mediacatch <command> [<args>]

MediaCatch CLI tool

positional arguments:
  {speech,vision,viz}  mediacatch command helpers
    speech             CLI tool to run inference with MediaCatch Speech API
    vision             CLI tool to run inference with MediaCatch Vision API
    viz                CLI tool to visualize the results of MediaCatch

options:
  -h, --help           show this help message and exit

Upload a file to MediaCatch Speech API and get the results

mediacatch speech path/to/file --save-result path/to/save/result.json
# or to see options
mediacatch speech --help

Upload a file to MediaCatch vision API and get the results

mediacatch vision path/to/file ocr --save-result path/to/save/result.json
# or to see options
mediacatch vision --help

Or import as a module

from mediacatch.vision import upload, wait_for_result

file_id = upload(
  fpath='path/to/file',
  type='ocr',
  # Optional parameters with their default values
  fps=1, # Frames per second for video processing. Defaults to 1.
  tolerance=10, # Tolerance for text detection. Defaults to 10.
  min_bbox_iou=0.5 # Minimum bounding box intersection over union for text detection. Defaults to 0.5.
  min_levenshtein_ratio=0.75 # Minimum Levenshtein ratio for merging text detection (more info here: https://rapidfuzz.github.io/Levenshtein/levenshtein.html#ratio). Defaults to 0.75.
  moving_threshold=50, # If merged text detections center moves more pixels than this threshold, it will be considered moving text. Defaults to 50.
  max_text_length=3, # If text length is less than this value, use max_text_confidence as confidence threshold. Defaults to 3.
  min_text_confidence=0.5, # Confidence threshold for text detection (if text length is greater than max_text_length). Defaults to 0.5.
  max_text_confidence=0.8, # Confidence threshold for text detection (if text length is less than max_text_length). Defaults to 0.8.
  max_height_width_ratio=2.0, # Discard detection if height/width ratio is greater than this value. Defaults to 2.0.
  get_detection_histogram=False, # If true, get histogram of detection. Defaults to False.
  detection_histogram_bins=8, # Number of bins for histogram calculation. Defaults to 8.
)

result = wait_for_result(file_id)

Visualize the results from MediaCatch

mediacatch viz ocr path/to/file path/to/result.json path/to/save.mp4
# or to see options
mediacatch viz --help

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mediacatch-0.2.0.tar.gz (220.8 kB view details)

Uploaded Source

Built Distribution

mediacatch-0.2.0-py3-none-any.whl (180.2 kB view details)

Uploaded Python 3

File details

Details for the file mediacatch-0.2.0.tar.gz.

File metadata

  • Download URL: mediacatch-0.2.0.tar.gz
  • Upload date:
  • Size: 220.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for mediacatch-0.2.0.tar.gz
Algorithm Hash digest
SHA256 2fcfc590275e6182a65c4d235b7fb3add75b34837deb8f3d1768a6f6b8284e91
MD5 8a6c0ef7371735764d3092b6e6fdd908
BLAKE2b-256 795f50085b77a610a1a09b5329d59b63baf9c96039760d37dc777f8449b1b29c

See more details on using hashes here.

File details

Details for the file mediacatch-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: mediacatch-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 180.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for mediacatch-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9234d0aec21432c3701541f7ef4e90c5554f1d234acbfd2977d0407e8b673620
MD5 93c190405f6ecf4a20b60a24bbb3f1f5
BLAKE2b-256 d930eec666db9534f8d2fd3748b2bac739a53d15500c66e394017b00c7e65ea3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page