You will get Face Detection using Open CV
Project details
This project focuses on building an efficient and accurate face detection system by integrating traditional computer vision techniques with deep learning approaches. OpenCV, a powerful computer vision library, is utilized for preprocessing tasks such as image capture, resizing, and initial face localization. To achieve higher detection accuracy and robustness, a Convolutional Neural Network (CNN) model is developed and trained to identify faces in images or real-time video feeds. The system is designed to handle various challenges such as different lighting conditions, angles, and occlusions, making it suitable for real-world applications like security surveillance, access control, and human-computer interaction.
This project aims to detect human faces using a combination of OpenCV for image processing and a Convolutional Neural Network (CNN) for accurate classification and detection. OpenCV handles image acquisition and basic operations, while the CNN model is trained to recognize and locate faces effectively. The final system ensures high accuracy and real-time performance across diverse environments.
This project aims to detect human faces using a combination of OpenCV for image processing and a Convolutional Neural Network (CNN) for accurate classification and detection. OpenCV handles image acquisition and basic operations, while the CNN model is trained to recognize and locate faces effectively. The final system ensures high accuracy and real-time performance across diverse environments.
Machine Learning Tools
Keras, NumPy, OpenCV, PythonWhat's included $300
These options are included with the project scope.
$300
- Delivery Time 5 days
- Number of Revisions Unlimited
- Number of Model Variations 3
- Number of Scenarios 2
- Number of Graphs/Charts 3
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
Optional add-ons
You can add these on the next page.
Fast 3 Days Delivery
+$100
Additional Model Variation
(+ 2 Days)
+$100
Additional Scenario
(+ 2 Days)
+$100
Additional Graph/Chart
(+ 2 Days)
+$50Frequently asked questions
About Muhammad
Research based project on Computer Vision and Data Science using ML/DL
Taxila, Pakistan - 3:10 pm local time
OpenCV, TensorFlow, Keras
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Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Client purchases the project and sends requirements.
Once the client purchases the project, they send their specific requirements, such as detection speed, dataset preferences, expected accuracy, real-time video integration, or any additional features (like face mask detection or age estimation).