https://github.com/zakideep/object-detection_model_with_transfer_learning-
This project uses transfer learning with ResNet50 for object detection. It identifies and localizes objects in images by drawing bounding boxes, leveraging the KITTI dataset for training.
https://github.com/zakideep/object-detection_model_with_transfer_learning-
jupyter-notebook kitti-dataset object-detection tensorflow tensorflow-datasets tensorflow-lite tensorflow-models transfer-learning
Last synced: 6 months ago
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This project uses transfer learning with ResNet50 for object detection. It identifies and localizes objects in images by drawing bounding boxes, leveraging the KITTI dataset for training.
- Host: GitHub
- URL: https://github.com/zakideep/object-detection_model_with_transfer_learning-
- Owner: zakideep
- License: agpl-3.0
- Created: 2024-11-01T16:30:00.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-02-24T18:09:14.000Z (8 months ago)
- Last Synced: 2025-02-24T19:23:50.757Z (8 months ago)
- Topics: jupyter-notebook, kitti-dataset, object-detection, tensorflow, tensorflow-datasets, tensorflow-lite, tensorflow-models, transfer-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 78.1 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Object-detection_model
🚀 Project Overview:
This project applies transfer learning to object detection using a pre-trained deep learning model. It identifies and localizes objects in images by drawing bounding boxes around detected objects.
📂 Dataset Used:
• The model is trained on the KITTI dataset, which is widely used in autonomous driving research.
• Dataset Breakdown:
o Training Set: 6,347 images
o Validation Set: 423 images
o Test Set: 711 images
🎯 Model Details:
• Pre-trained Model Used: ResNet50
• Framework: TensorFlow
• Transfer Learning: Fine-tuned ResNet50 on the KITTI dataset for object detection.
• Training Time: ~26 minutes (1586 seconds)