https://github.com/monocongo/vod_convert
Python modules and scripts for conversion between popular visual object detection annotation formats.
https://github.com/monocongo/vod_convert
Last synced: 6 months ago
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Python modules and scripts for conversion between popular visual object detection annotation formats.
- Host: GitHub
- URL: https://github.com/monocongo/vod_convert
- Owner: monocongo
- License: mit
- Created: 2019-10-21T16:34:43.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-07-06T15:18:15.000Z (about 2 years ago)
- Last Synced: 2024-07-06T16:35:15.009Z (about 2 years ago)
- Language: Python
- Size: 14.6 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# vod_convert
Python modules and scripts for conversion between popular visual object detection annotation formats.
## Install the TensorFlow Object Detection API
Since we'll utilize the TensorFlow models API in order to perform TFRecord
conversions we'll need to have access to the
[TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection).
(**NOTE**: the below is a simplification of the
[official installation instructions](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md))
1. Clone the TensorFlow Object Detection API from GitHub and set the API's base
directory as an environment variable for later use:
```bash
$ cd
$ git clone git@github.com:tensorflow/models.git
$ cd models
$ export TFOD=`pwd`
```
2. Create a new Python environment (or activate an existing Python environment).
In this example we'll use an Anaconda environment:
```bash
$ conda create -n tltod python=3 --yes
$ conda activate tltod
```
3. Install TensorFlow and other necessary packages:
```bash
$ pip install tensorflow
$ pip install Cython
$ pip install contextlib2
$ pip install pillow
$ pip install lxml
$ pip install jupyter
$ pip install matplotlib
```
4. Compile the Protobuf libraries:
```bash
$ cd ${TFOD}/research
$ protoc object_detection/protos/*.proto --python_out=.
```
5. Add the API's `research` and `research/slim` directories to the `PYTHONPATH` variable:
```bash
$ cd ${TFOD}/research
$ export PYTHONPATH=`pwd`:`pwd`/slim
```
6. Test the installation:
```bash
$ python object_detection/builders/model_builder_test.py
```