🌟Image Vision🌟: A Deep Learning Model for Object Detection and Classification 🚀

By : @anuj_dwivedi

Project Overview 📝

🔍 Image Vision is a deep learning model for object detection and classification using computer vision techniques. The model uses state-of-the-art deep learning algorithms, such as Faster R-CNN and YOLO, to detect and classify objects in images with high accuracy. The model can be trained on custom datasets to improve its performance for specific use cases.

🛠️ The project is implemented using Python programming language and popular deep learning libraries such as TensorFlow and PyTorch. The model is trained on GPU for faster training times and improved accuracy.

💻 The project also includes a user-friendly GUI application built with PyQT5, allowing users to easily upload images and view the model's predictions.

Features and Benefits ✨

• Accurate object detection and classification for a wide range of use cases.
• Customizable and scalable for specific needs.
• User-friendly GUI for easy use and integration into existing workflows.
• Fast training times with GPU acceleration.

Getting Started 🚀

To get started with using Image Vision, follow these steps:

1. Clone the Image Vision repository to your local machine.
2. Install the required dependencies using pip install -r requirements.txt.
3. Train the model on your custom dataset or use the pre-trained model.
4. Use the GUI application to upload images and view the model's predictions.

Technical Details 🔬

• The model is implemented using deep learning algorithms such as Faster R-CNN and YOLO.
• The model is trained on GPU using popular deep learning libraries such as TensorFlow and PyTorch.
• The user interface is built with PyQT5.

Future Work 🔮

Future work for the Image Vision project includes:

• Improving the model's performance and accuracy.
• Adding support for video input and real-time object detection.
• Integrating the model into existing workflows and applications.

Contact 📧

LinkTree LinkedIn Instagram