Fishial.ai

This project includes training and validation scripts for the fish segmentation and classification model.

Demo web aplication

Project website: www.fishial.ai

Installation

Install the dependencies.

$ pip3 install -r requirements.txt

Getting Started

• https://colab.research.google.com/drive/1nKJ0V1sBLgfNJaCTQmuqUV1ybrx1m7qI?usp=sharing This jupyter notebook allows you to run segmentation and classification neural networks on Google Cloud or your computer, after downloading the files from the links below.

• auto_train_cross.py is the script performs training automatically with different parameters the selected model using the cross entropy loss function. The checkpoint with the best performance on the validation dataset is saved to the output folder.

• auto_train_triplet.py is the script performs training automatically with different the selected model using the (Triplet Quadruplet) loss function. The checkpoint with the best performance on the validation dataset according k-metric is saved to the output folder.

• auto_train_cross.py is the script cut your dataset to specific maximum and minimum count images per class to the arbitrary way.

• train.py is the basic set up script to train segmentation model using Detectrin2 API

• train_copy_paste.py is the basic set up script to train segmentation model using Detectrin2 API with Copy Paste Augumentation.

• ExportModelToTorchscript.ipynb This jupyter notebook allows convert Classification pytorch model to TorchScript format, and Detectron2 to Torchscript model.

• (model.py, utils.py): These files contain the main classification pipline implementation.

• CreateDataBaseTensor.py: This script is designed to get the attachment tensor for a trained neural network, the resulting tensor has dimensions {number of classes maximum number of images for one class embedding dimension} for classes in which the number of attachments is less than in the maximum class, a tensor with a value of 100 is added in order not to affect for inference

• CreateDatasetAndTrain.py: This script allows you to create a training and test data set from the exported fishial coco file and train the neural network

Models

Train results

Segmentation model has validated by mAP metric.

MaskRCNN

Classification model

Json file with the names of fish classes that the latest model recognizes can be found here: (labels)

License

MIT