deep-waste-app
Managing waste in fun and easy way with AI ā»ļø (by sumn2u)
trashnet
Dataset of images of trash; Torch-based CNN for garbage image classification (by garythung)
| deep-waste-app | trashnet | |
|---|---|---|
| 3 | 2 | |
| 25 | 545 | |
| - | - | |
| 6.1 | 1.8 | |
| 4 months ago | 11 months ago | |
| Dart | Lua | |
| BSD 3-clause "New" or "Revised" License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deep-waste-app
Posts with mentions or reviews of deep-waste-app.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-06.
- Open source app to manage household waste
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Deep Learning Waste Management App with Gamification
The source code can be found here (https://github.com/sumn2u/deep-waste-app).
trashnet
Posts with mentions or reviews of trashnet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-06.
-
Deep Learning Waste Management App with Gamification
Torch and Keras provide the pre-trained models DenseNet121 and MobileNet, respectively, which we utilize for our image recognition models. These models were initially trained on ImageNet. We then fine-tuned MobileNet using the TrashNet data collection to classify garbage material. Then resultant model are then converted into tflite file, making it accessible for processing in mobile devices
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NotImplementedError (YOLOv5)
Iām running it on the trashnet dataset. A labeled version of it. I have trained the model with modified code for 4 epochs and still the above mentioned metrics are 0. When I run it on the CPU tho, with the original code, the metrics starts at pretty reasonable values and goes on an increasing trend.
What are some alternatives?
When comparing deep-waste-app and trashnet you can also consider the following projects:
WeatherApp-Flutter - Flutter Weather App
yolov5 - YOLOv5 š in PyTorch > ONNX > CoreML > TFLite
flutter_programs - Experiments with Mobile
techniques - Techniques for deep learning with satellite & aerial imagery
ez_tickets_app - A cinema ticket booking app made with Flutter SDK
TACO - š® Trash Annotations in Context Dataset Toolkit
Musify - Unlock the full potential of music: Stream effortlessly with one app!
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
awesome-flutter - An awesome list that curates the best Flutter libraries, tools, tutorials, articles and more.