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https://github.com/egemenzeytinci/identity-detector
National ID cards detector
https://github.com/egemenzeytinci/identity-detector
image-classification image-processing python tensorflow
Last synced: about 1 month ago
JSON representation
National ID cards detector
- Host: GitHub
- URL: https://github.com/egemenzeytinci/identity-detector
- Owner: egemenzeytinci
- Created: 2022-01-18T22:24:09.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2022-02-11T00:54:39.000Z (almost 3 years ago)
- Last Synced: 2024-10-21T22:51:15.911Z (3 months ago)
- Topics: image-classification, image-processing, python, tensorflow
- Language: Python
- Homepage:
- Size: 30.3 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Identity Card Detector
You can check the application from the website below,
https://identity-detector.herokuapp.com
## Install
Install dependencies by using `pip`,
```bash
$ pip3.9 install -r requirements.txt
```
## Training
You need to download dataset with using download script,
```bash
$ python3 download.py ./default.ini # or custom ini file
```
Then train your model as follows.
**Please keep in mind**, if you've a saved model in the checkpoint path, the command below continues the training.
```bash
$ python3 train.py ./default.ini # or custom ini file
```
**Please notice that**, you need to change the path variables in the default config file named as `default.ini`.
You can follow your model on the tensorboard,
```bash
$ tensorboard --logdir /tmp/tensorboard-logs
```
**Please notice that**, If you change `logdir` variable under the model section in the default config, you need to change the path to `/tmp/tensorboard-logs`.
## Prediction
You can download model [here](https://drive.google.com/file/d/1dUAbGskgIqBWs86ut3m9Azx93_QOyV0u).
Then, predict with using folder or only one file as follows,
```bash
$ python3 predict.py --model /path/to/model --path /path/to/folder # or /path/to/file
```
Here is the example response for a folder,
```json
[
{
"name": "identity_card.jpg",
"prediction": "document",
"probability": 99.99996423721313
},
{
"name": "non_document.jpg",
"prediction": "non_document",
"probability": 100.0
},
{
"name": "selfie.jpg",
"prediction": "selfie",
"probability": 99.23766255378723
}
]
```
Or you can use your camera,
```bash
$ python3 stream.py --model /path/to/model
```
## Examples
