Skip to main content

Check if image was rotated by 90, 180, 270 degrees.

Project description

Check orientation

Models to check if image was rotated by 0, 90, 180, 270 degrees.

Installation

pip install -U check_orientation

Example inference

Colab notebook with the example: Open In Colab

Training

Define the config.

Example at check_orientation/configs

Define the environmental variable TRAIN_IMAGE_PATH that points to the folder with train dataset.

Example:

export TRAIN_IMAGE_PATH=<path to the tranining folder>

Define the environmental variable VAL_IMAGE_PATH that points to the folder with validation dataset.

Example:

export VAL_IMAGE_PATH=<path to the validation folder>

Training

python -m check_orientation.train -c <path to config>

Inference

python -m torch.distributed.launch --nproc_per_node=<num_gpu> check_orientation/inference.py \
                                   -i <path to images> \
                                   -c <path to config> \
                                   -w <path to weights> \
                                   -o <output-path> \
                                   --fp16

Pre-trained models

Models were pre-trained on the OpenImages dataset.

Models Validation accuracy Config file Weights
swsl_resnext50_32x4d 0.9128 Link Link

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

check_orientation-0.0.5.tar.gz (6.6 kB view hashes)

Uploaded Source

Built Distribution

check_orientation-0.0.5-py2.py3-none-any.whl (11.4 kB view hashes)

Uploaded Python 2 Python 3

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