💡Build a sign language detector using Tensorflow and Python
📸Collect and label images for training
🎓Perform transfer learning for better accuracy
👀Detect sign language poses in real time
🔬Use the Tensorflow object detection API for faster training
💡Build a sign language detector using Tensorflow and Python
📸Collect and label images for training
🎓Perform transfer learning for better accuracy
👀Detect sign language poses in real time
🔬Use the Tensorflow object detection API for faster training
What is transfer learning?
—Transfer learning is a machine learning technique where a pre-trained model is used as a starting point for a new task, allowing for faster and more accurate training.
Can I use a different webcam?
—Yes, you can modify the code to work with different webcam devices. Simply change the device number in the code.
How many images do I need to collect?
—In this tutorial, we collect 15 images for each sign language pose. You can adjust the number based on your specific needs.
Can I use a different pre-trained model?
—Yes, you can choose a different pre-trained model from the Tensorflow Model Zoo. Just make sure it is compatible with the Tensorflow object detection API.
Is this project suitable for beginners?
—Yes, this tutorial is beginner-friendly and provides step-by-step instructions for building a sign language detector. Basic knowledge of Python is recommended.
00:01[Music]
00:07Introduction to building a sign language detector using Tensorflow and Python
00:24Overview of the steps involved in building the detector
02:22Code setup and cloning the real-time object detection repository
04:32Collecting images using a webcam and OpenCV
09:55Looping through each label and capturing images
10:16Conclusion and final thoughts on building a sign language detector
