The source code of machine learning model's API of Travens smart guide in order to complete Bangkit Capstone Project
Endpoint | Method | Body Sent (JSON) | Description |
---|---|---|---|
/ | GET | None | HTTP GET REQUEST Testing Endpoint |
/post | POST | Anything | HTTP POST REQUEST Testing Endpoint |
/404 | GET & POST | Anything | 404 NOT FOUND Endpoint |
/predict | POST | file: Image file | HTTP POST REQUEST Prediction Endpoint |
- Clone this repo
- Open terminal and go to this project's root directory
- Type
python -m venv .venv
and hit enter - In Linux, type
source .venv/bin/activate
- In Windows, type
.venv\Scripts\activate
- Type
pip install -r requirements.txt
- Serve the Flask app by typing
flask run
- It will run on
http://127.0.0.1:5000
- Open Postman
- Enter URL request bar with
http://127.0.0.1:5000/predict
- Select method POST
- Go to Body tab and select form-data
- Change key from form-data with file (it must be named
file
) - Input the image that you want predict as a value of the key
- Send the request
- Cao B, Araujo A, Sim J. Unifying Deep Local and Global Features for Image Search. 2020. Arxiv
- Weyand T, Araujo A, Cao B, Sim J. Google Landmarks Dataset v2-A Large-Scale Benchmark for Instance-Level Recognition and Retrieval. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020. Arxiv
- A Howard, A Zhmoginov, LC Chen, M Sandler, M Zhu. MobileNetV2: Inverted Residuals and Linear Bottlenecks. The IEEE Conference on Computer Vision and Pattern Recognition. 2018. Arxiv
- Collection of models for landmark recognition TensorFlow Hub