Contact person: Business Client

Phone:Show

Email:Show

Location: Faridabad, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I’m building a macOS application that can watch a live webcam feed, isolate one or two hands, recognise each American Sign Language alphabet letter with high accuracy, and automatically concatenate those letters into clean, properly spaced words and sentences—so H-E-L-L-O W-O-R-L-D instantly appears as “HELLO WORLD”, and longer phrases such as I-A-M-G-O-O-D emerge as “I AM GOOD HOW ARE YOU”.

The workflow I have in mind is:

• The moment a hand enters the frame the model detects it, classifies the current static sign, and posts the corresponding letter to an on-screen text buffer.
• When no new sign is detected for a short debounce interval, the buffer inserts a space so we move naturally from letters to words to full sentences.
• A clean desktop UI on my MacBook should show the camera preview with bounding boxes or landmarks, plus a side console where the live text stream can be copied or saved. Dark- and light-mode compatibility would be a plus.

Key expectations
• High accuracy on the full ASL alphabet in real-time (30 fps on a standard MacBook webcam).
• Smooth UX: minimal latency, clear feedback when a sign is recognised, and an easy reset/clear function.
• Well-structured, documented source code. I’m flexible on the stack—Python with PyTorch/TensorFlow, Swift/SwiftUI, or a hybrid Electron front-end are all acceptable as long as you reach the performance target on macOS.

Deliverables
1. Trained model and all training scripts.
2. macOS executable (or simple one-command setup) with UI and live console.
3. README covering installation, usage, and a quick guide to retraining or fine-tuning the model on additional data.

I’ll test by signing full sentences on my laptop webcam; if the output text matches what I spell, we’re good to go. Looking forward to your approach and any past work you can share on similar computer-vision projects." (client-provided description)