Sections | Descriptions | Status |
---|---|---|
Documentations | Build idea, input, output, tasks and plan for project | |
Object Detection | Build model using PyTorch and deploy it onto Web-server using FastAPI | |
Web-server | Building a web-server to embedded model AI, monitor Camera and control system | |
Embedded Artificial Intelligence | Building a system has hardward and AI, in detail that system can be a robot or similar | |
Reference papers | Research for project |
🔗 Dataset: https://www.kaggle.com/datasets/sriramr/apples-bananas-oranges/data?select=original_data_set
💁 We only use apples and oranges data, so before train model, we need to pre-process dataset:
- First: We need re-oraginal data to apples directory and oranges directory.
- Second: Split data to train and test data. Actually, I want to create two folder (train and test).
💁 We have pre-processed data above, now we can train some models with the data.
- In this project, I'm going to use PyTorch to train models.
- I will experiment some models such as ResNet, Efficient, MobileNet...
- See which model is compatible with our project based on criteria such as its accuracy and size.
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📉 This chart is descript for train and test loss/accuracy of model
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🍏🍊 We can make some prediction to see what's going on
Name model | Accuracy Testing (%) | Accuracy Predict (%) | Time Predict (s) | Size (MB) |
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ResNet50 | 98.660714 | 97.001250 | 0.203992 | 89 |
ResNet18 | 97.321429 | 99.881893 | 0.178116 | 42 |
MobileNetV2 | 98.660714 | 99.923056 | 0.170975 | 8 |
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⏲️ Shortest predict time: MobileNetV2 with 0.17 seconds
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📁 Smallest size file: MobileNetV2 with 8 MB
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📉 Accuracy: The above three models have similar accuracy rates, but MobileNetV2 is trained with the fewest training iterations (5), while ResNet50 and ResNet18 are trained with 8 iterations.
- GET API from ESP32 ESP32 GET JSON from API - ESP32 GET request from API receive JSON
- POST API from ESP32 ESP32 POST JSON to api endpoint - ESP32 POST request to API endpoint
- PUT (update) API from ESP32 ESP32 PUT JSON to api endpoint - ESP32 POST request to API endpoint
Paper | Link | Quote |
---|---|---|
Object Detection using ESP 32 CAM | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4152378 | Mehendale, Ninad. "Object Detection using ESP 32 CAM." Available at SSRN 4152378 (2022). |
Real-Time Reinforcement Learning for Vision-Based Robotics Utilizing Local and Remote Computers | https://arxiv.org/pdf/2210.02317 | Wang, Yan, Gautham Vasan, and A. Rupam Mahmood. "Real-time reinforcement learning for vision-based robotics utilizing local and remote computers." 2023 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2023. |
Flow-guided Semi-supervised Video Object Segmentation | https://arxiv.org/pdf/2301.10492 | Zhang, Yushan, et al. "Flow-guided semi-supervised video object segmentation." arXiv preprint arXiv:2301.10492 (2023). |