https://github.com/waikato-datamining/fast-opex

Simpler and faster implementation of the OPEX JSON file format for object detection predictions.
https://github.com/waikato-datamining/fast-opex

exchange-format json object-detection

Last synced: 5 days ago
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Simpler and faster implementation of the OPEX JSON file format for object detection predictions.

• Host: GitHub
• URL: https://github.com/waikato-datamining/fast-opex
• Owner: waikato-datamining
• License: mit
• Created: 2024-06-13T22:09:33.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-22T04:35:32.000Z (3 months ago)
• Last Synced: 2024-11-04T05:05:59.493Z (10 days ago)
• Topics: exchange-format, json, object-detection
• Language: Python
• Homepage:
• Size: 17.6 KB
• Stars: 0
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGES.rst
  • License: LICENSE

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README

        
# fast-opex

Simpler and faster implementation of the OPEX JSON file format for object detection predictions.

Uses [orjson](https://github.com/ijl/orjson) if present (no pretty-printing available) for further speed-ups, 

otherwise the standard json library.

This library is written in Python. For a Java port, please see 

[opex4j](https://github.com/waikato-datamining/opex4j).

## Installation

You can install the library via `pip` (or `pip3`):

```commandline

pip install fast-opex

```

## JSON

```json

{

  "timestamp": "%Y%m%d_%H%M%S.%f",

  "id": "str",

  "objects": [

    {

      "score": 1.0,

      "label": "person",

      "bbox": {

        "top": 100,

        "left": 100,

        "bottom": 150,

        "right": 120

      },

      "polygon": {

        "points": [

          [100, 100],

          [150, 100],

          [150, 120],

          [100, 120]

        ]

      }

    },

    {

      "score": 0.95,

      "label": "house",

      "bbox": {

        "top": 100,

        "left": 100,

        "bottom": 200,

        "right": 200

      },

      "polygon": {

        "points": [

          [100, 100],

          [200, 100],

          [200, 200],

          [100, 200]

        ]

      },

      "meta": {

        "price": "500k"

      }

    }

  ],

  "meta": {

    "key1": "value1",

    "key2": "value2"

  }

}

```

**Notes:**

The following keys are optional: 

* timestamp

* meta

* score 

## Reading/Writing

To read a prediction:

```python

from opex import ObjectPredictions

# From a string

predictions = ObjectPredictions.from_json_string("{...}")

# From a named file

predictions = ObjectPredictions.load_json_from_file("predictions.json")

# From an open stream

with open("predictions.json", "r") as stream:

    predictions = ObjectPredictions.read_json_from_stream(stream)

```

To write a prediction:

```python

from opex import ObjectPredictions

predictions: ObjectPredictions = ...

# Serialise the object to a JSON-formatted string

print(predictions.to_json_string())

print(predictions.to_json_string(indent=2))

# Write the object to a file

predictions.save_json_to_file("predictions.json", indent=2)

# Write to an open stream

with open("predictions.json", "w") as stream:

    predictions.write_json_to_stream(stream, indent=2)

```