ML Sign Detection (Digits 0 to 9)

How to use it

• Download or clone the project using git clone https://github.com/lavsharmaa/ml-asl-sign-detection or fork the repo.

Creating your own dataset

• 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 from 0 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 are 100 images for digit 0 we placed 80 images for training and 20 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.

Training the dataset

• 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.

Predicting the sign

• Finally run python predict.py, perform your sign into the webcam and see the output.

Tools and Technologies

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)

Team

• Mansi Anantpurkar
• Lav Sharma
• Rutuja Bhate