Learn Facial Recognition Using YOLOv7: Deep Learning Project using Roboflow and Google Colab
Course Title: Facial Recognition Using YOLOv7: Deep Learning Project using Roboflow and Google Colab
Course Description:
Welcome to the “Facial Recognition Using YOLOv7: Deep Learning Project using Roboflow and Google Colab.” This comprehensive course is designed to take you on a hands-on journey through the process of building a facial recognition system using the state-of-the-art YOLOv7 algorithm. Leveraging the capabilities of Roboflow for efficient dataset management and Google Colab for cloud-based model training, you will acquire the skills needed to implement facial recognition in real-world scenarios.
What You Will Learn:
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Introduction to Facial Recognition and YOLOv7:
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Gain insights into the significance of facial recognition in computer vision and understand the fundamentals of the YOLOv7 algorithm.
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Setting Up the Project Environment:
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Learn how to set up the project environment, including the installation of necessary tools and libraries for implementing YOLOv7 for facial recognition.
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Data Collection and Preprocessing:
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Explore the process of collecting and preprocessing datasets of faces, ensuring the data is optimized for training a YOLOv7 model.
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Annotation of Facial Images:
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Dive into the annotation process, marking facial features on images to train the YOLOv7 model for accurate and robust facial recognition.
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Integration with Roboflow:
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Understand how to seamlessly integrate Roboflow into the project workflow, leveraging its features for efficient dataset management, augmentation, and optimization.
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Training YOLOv7 Model:
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Explore the end-to-end training workflow of YOLOv7 using the annotated and preprocessed dataset, adjusting parameters and monitoring model performance.
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Model Evaluation and Fine-Tuning:
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Learn techniques for evaluating the trained model, fine-tuning parameters for optimal facial recognition, and ensuring robust performance.
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Deployment of the Model:
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Understand how to deploy the trained YOLOv7 model for real-world facial recognition tasks, making it ready for integration into applications or security systems.
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Ethical Considerations in Facial Recognition:
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Engage in discussions about ethical considerations in facial recognition, focusing on privacy, consent, and responsible use of biometric data.
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Course Details
- Language: #English
- Students: 1087
- Rating: 4.5 / 5.0
- Reviews: 1
- Category: #IT_and_Software
- Published: 2024-01-11 20:44:30 UTC
- Price: €49.99
- Instructor: | | ARUNNACHALAM SHANMUGARAAJAN | |
- Content: 1 total hour
- Articles: 0
- Downloadable Resources: 0
Coupon Details
- Coupon Code: 1623D08E59AAB8885AD9
- Expire Time: 2024-01-29 03:59:00 UTC