- Download or clone the project using
git clone https://github.com/lavsharmaa/ml-asl-sign-detection
or fork the repo.
collect-data.py
is used for creating your own dataset.- Run it using
python collect-data.py
it will show you a list of numbers from0 to 9
. - Using the number you can create dataset. For example, if you want to create dataset of number
0
press 0 on your keyboard and perform the sign it will start capturing it. - Similarly, you can do this for other numbers also and even for alphabets
A to Z
. - We followed
80:20
ratio. That means if there are100 images
for digit0
we placed80 images
for training and20 images
for testing. Higher the number of images in training and testing more accurate your model will be in detecting the sign. - You can also download the dataset that we have created.
- After you have successfully generated your dataset.
- Run
python train.py
to generate your model. It will take few mins and you will get your training accuracy.
- Finally run
python predict.py
, perform your sign into the webcam and see the output.
Food Corner is the web based project. Developed using
- Python (3.7.4)
- IDE (Jupyter)
- Numpy (version 1.16.5)
- cv2 (openCV) (version 3.4.2)
- Keras (version 2.3.1)
- Tensorflow (as keras uses tensorflow in backend and for image preprocessing) (version 2.0.0)