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Waste detection
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Waste detection
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<p>An YOLO model specifically trained to detect waste in images. We collected a custom dataset of waste,
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classified and annotated it, and trained the model using YOLOv8 on Keras. The model is able to detect
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the position and class of waste in images. It can separate the following classes of waste:
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</p><ul><li><p>Plastic
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</p></li><li><p>Metal
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</p></li><li><p>Paper
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</p></li><li><p>Glass
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</p></li><li><p>Organic
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</p></li><li><p>Wood
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</p></li><li><p>Textile
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</p></li><li><p>Medical
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</p></li><li><p>Electronic
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</p></li><li><p>Other
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</p></li></ul><p>There are actually over 90 classes, but they are grouped into these ones because there is only
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a small amount (in the 1-2 digits) of samples for each class. The model is able to detect multiple
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classes in the same image, or acknowledge that there is no waste in the image.
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</p><p>YOLO is used pretrained on the COCO dataset, and then fine-tuned on our dataset. This is until
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there are enough samples for each class to train the model from scratch.
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</p><p>Contributions are welcome. If you have a dataset of waste, please share it with us. We will
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annotate it (if it's not already) and train the model on it.
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</p><p>You don't need technical knowledge to contribute. If you can take photos with a phone and make
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a ZIP of them, you can contribute. If you can draw rectangles around objects with the mouse,
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you can contribute. If you can drop photos into folders corresponding to their class, you can
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contribute.
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</p><p>Of course, if you do have technical knowledge, you can help with the model training, testing, and
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optimisation. You can also improve the training code and better process the dataset.
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</p><h2>Licence</h2><p>Unless otherwise stated, the software (source code) in this repository is licenced under the GNU Affero General Public License,
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with an additional permission in section 7 - basically an LAGPL.
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A copy of the licence is located in the file <code>LICENCE-GNU-AGPL.md</code> in this directory.
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</p><blockquote><p>This program is free software, you can redistribute it and/or modify
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it under the terms of GNU Affero General Public License
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as published by the Free Software Foundation, either version 3
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of the License, or (at your option) any later version.
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</p><p>This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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or FITNESS FOR A PARTICULAR PURPOSE. See the
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General Public License for more details.
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</p><p>You should have received a copy of the the GNU Affero
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General Public License, along with this program. If not, see
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<a href="https://www.gnu.org/licenses/">https://www.gnu.org/licenses/</a>.
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</p><h5>Additional permission under the GNU Affero GPL version 3 section 7:</h5><p>If you modify this program, or any covered work, by linking or
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combining it with other code, such other code is not for that reason
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alone subject to any of the requirements of the GNU Affero GPL
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version 3.
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</p></blockquote><p>Unless otherwise stated, the annotations in this repository are dual-licensed under either of these licences:
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</p><ul><li><p><a href="https://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution Share-Alike 4.0</a>.
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To view a copy of this license, read the <code>LICENCE-CC-BY-SA.md</code> file, visit http://creativecommons.org/licenses/by-sa/4.0/
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or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
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</p></li><li><p><a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution Non-Commercial 4.0</a>.
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To view a copy of this license, read the <code>LICENCE-CC-BY-NC.md</code> file, visit http://creativecommons.org/licenses/by-nc/4.0/
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or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
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</p></li></ul><p>You do not have to comply with the terms of both licences. Choose one and comply only with it.
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</p><p>The images in the repository are licensed depending on their source:
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</p><ul><li><p>If the file name has the <code>original</code> prefix (or no prefix at all), the images are licenced under the same terms as the annotations (see above).
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</p></li><li><p>If the file name has the <code>trash-detection</code> prefix, it comes from https://universe.roboflow.com/nora-slimani/trash-detection-otdmj and is licensed under <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0</a>.
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</p></li><li><p>If the file name has the <code>ffml</code> prefix, it comes from https://www.kaggle.com/datasets/cristeaioan/ffml-dataset and is licensed under <a href="https://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution Share-Alike 4.0</a>.
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</p></li><li><p>If the file name has the <code>dwc</code> prefix, it comes from https://www.kaggle.com/datasets/arkadiyhacks/drinking-waste-classification and is public domain.
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</p></li><li><p>If the file name has the <code>hitl</code> prefix, it comes from https://www.kaggle.com/datasets/humansintheloop/recycling-dataset and is public domain.
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</p></li></ul><p>I hope I didn't infringe on any licences or miss any sources. If you think there is a problem,
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please send me an email at <a href="mailto:root&#64;roundabout-host.com">root&#64;roundabout-host.com</a> and I'll remove the infringing files.
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</p><p>The VIA application shipped in this repository (located at the <code>/via</code> path) is licensed under the BSD licence.
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</p><blockquote><p>Copyright (c) 2016-2021, Abhishek Dutta, Visual Geometry Group, Oxford University and VIA Contributors.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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</p><p>Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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this list of conditions and the following disclaimer in the documentation
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