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I will build face recognition and facial emotion detection ai with python opencv
Building efficient, accurate, and intelligent AI models
Hi, I'm Abdul Hameed AI/ML Engineer with 4+ years in Deep Learning, NLP & Computer Vision.
I build: facial emotion & expression analysis from video, face recognition (ArcFace), speech-to-text pipelin...
Informazioni su questo servizio
Need a face recognition or facial emotion detection system that works on your real data? I build production-ready computer vision models in Python (PyTorch, TensorFlow, OpenCV) and deliver clean, documented code you can run and extend.
What I can build for you:
- Face recognition (identify/verify people from images, webcam or CCTV)
- Face detection and tracking in video
- Facial emotion / expression recognition (happy, sad, angry, neutral, etc.)
- Attendance systems, access control, customer emotion analytics
- Custom CNN / Vision Transformer models trained on your dataset
- REST API (FastAPI) and cloud deployment for real use
What you get:
- Source code + setup guide
- Trained model files
- Accuracy report
- Documentation and post-delivery support
Tech: Python, PyTorch, TensorFlow, OpenCV, MediaPipe, InsightFace, DeepFace, YOLO, FastAPI.
Why me: I run RoboLogicX, an AI and automation company. I have delivered facial and emotion analysis models for university research and business clients, and I explain results in plain language.
Message me with your use case, data and target platform before ordering so I can confirm the right package.
Linguaggio di programmazione:
Python
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MATLAB
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SQL
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NoSQL
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MLflow
Framework:
Scikit-learn
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DeepPy
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keras
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PyTorch
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Panda
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tensorflow
Il mio portfolio
Altri servizi della categoria Data science e ML offerti da me
FAQ
What types of facial emotion detection models can you develop?
I can develop custom AI models for facial emotion recognition, sentiment analysis, facial expression detection, mood classification, and real-time emotion detection from images or video streams.
Can you train the model on my custom dataset?
Yes. I can train, fine-tune, and optimize the model using your custom dataset to improve accuracy and performance for your specific use case.
Which technologies and frameworks do you use?
I work with Python, TensorFlow, PyTorch, OpenCV, CNNs, Deep Learning, Computer Vision, and other state-of-the-art AI frameworks depending on project requirements.
Can the model work in real-time applications?
Yes. I can develop real-time emotion detection systems for webcams, CCTV cameras, mobile applications, desktop software, and web-based solutions.
Will you provide deployment and API integration support?
Yes. I can deploy the trained model and provide integration support using FastAPI, Flask, REST APIs, or custom deployment solutions based on your project needs.
What do you need to get started?
To get started, please provide your project requirements, sample data (if available), expected output format, deployment preferences, and any specific accuracy or performance goals.
