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https://github.com/dominhhai/captcha-breaker
High Accuracy Captcha Breaker with Tensorflow and Node.js
https://github.com/dominhhai/captcha-breaker
captcha nodejs tensorflow
Last synced: 18 days ago
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High Accuracy Captcha Breaker with Tensorflow and Node.js
- Host: GitHub
- URL: https://github.com/dominhhai/captcha-breaker
- Owner: dominhhai
- License: mit
- Created: 2018-06-19T05:44:00.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-11-22T04:29:09.000Z (almost 2 years ago)
- Last Synced: 2023-11-07T16:30:09.316Z (about 1 year ago)
- Topics: captcha, nodejs, tensorflow
- Language: Python
- Homepage:
- Size: 27.3 KB
- Stars: 130
- Watchers: 8
- Forks: 37
- Open Issues: 14
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE
Awesome Lists containing this project
README
# Captcha Breaker
Build with Tensorflow (ConvNets) and Node.js :muscle::muscle::muscle:
E.x: *Amazon Captcha* (click image below to watch demo video)
[](https://youtu.be/pruaoG-MSo4)
# Installation
#### Python packages
```
$ pip install -r requirements.txt
```
#### Node.js packages (Node.js user only)
```
$ npm i
```
# Usage
## 1. Create train data
#### Prepare your training dataset
* Copy captcha images to `data/captcha` folder
```
|_data
|_captcha
|_ xss7.jpg
|_ tvu4.jpg
```
**IMPORTANT:** Note each image file is named with it's own solution.
That means that if an image is named `A1bD3.jpg`, it corresponds to a captcha's whose solution is `A1bD3`
#### Build train data for model
Run `src/create_train_data.py` will save your train data as `data/captcha.npz` compressed file.
```
$ python src/create_train_data.py
```
The compressed `data/captcha.npz` includes:
* Train Data ( `x_train`, `y_train` ): `80%`
* Test Data ( `x_test`, `y_test` ): `20%`
## 2. Train
Run `src/train.py` to train the model with your own dataset.
```
$ python src/train.py
```
Take :coffee: or :tea: while waiting!
## 3. Attack
Now, enjoy your war :fire::fire::fire: :stuck_out_tongue_winking_eye::stuck_out_tongue_winking_eye::stuck_out_tongue_winking_eye:
#### Python
```
$ python src/predict --fname YOUR_IMAGE_PATH_or_URL
```
Sample output:
```
loading image: data/captcha/captcha_2.jpg
load captcha classifier
predict for 1 char: `X` with probability: 99.956%
predict for 2 char: `I` with probability: 99.909%
predict for 3 char: `N` with probability: 99.556%
predict for 4 char: `C` with probability: 99.853%
predict for 5 char: `H` with probability: 99.949%
predict for 6 char: `A` with probability: 98.889%
Captcha: `XINCHA` with confident: `99.686%`
XINCHA
```
#### Node.js
```js
const captchaPredict = require('src/predict')
captchaPredict(YOUR_IMAGE_PATH_or_URL)
.then(console.log)
.catch(console.error)
```
Sample output:
```
[
"loading image: data/captcha/captcha_2.jpg",
"load captcha classifier",
"predict for 1 char: `X` with probability: 99.956%",
"predict for 2 char: `I` with probability: 99.909%",
"predict for 3 char: `N` with probability: 99.556%",
"predict for 4 char: `C` with probability: 99.853%",
"predict for 5 char: `H` with probability: 99.949%",
"predict for 6 char: `A` with probability: 98.889%",
"Captcha: `XINCHA` with confident: `99.686%`",
"XINCHA"
]
```