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Fine-tuning a model trained on a different problem for instance segmentation.

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alessandro1802/instance-segmentation

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Instance segmentation via transfer learning

There are 3 notebooks:

  1. sampleDataset is how the dataset was sampled
  2. train where it is shown how the model was fine-tuned and trained
  3. evaluate provides code for evaluating the model

All of them are self-explanatory.

Inference is available via REST API, made using a simple Flask app. Run with:

python app.py

Environment set-up

python3.8 -m venv venv
source venv/bin/activate
pip install git+https://github.com/tensorflow/examples.git
pip install -r requirements.txt

Data-set

Mappilary Vistas v1.2, which contains 25 000 fully-annotated high-resolution images with 66 object categories.

Base model

pix2pix : Image-to-image translation with a conditional GAN.

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