kamipakistan/YOLOv4-Custom-Object-Detection
The "YOLOv4 Custom Object Detection" Github repository provides a comprehensive guide and code for training a custom object detection model using the YOLOv4 algorithm.
This project helps computer vision practitioners and researchers train a custom object detection model to find specific items in images or video. You input a collection of labeled images of the objects you want to detect, and it outputs a trained model that can identify those objects in new, unseen images or live video streams. It's designed for anyone needing to automatically locate and classify custom objects in visual data.
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Use this if you need to build a specialized object detection system for objects not typically found in standard datasets, such as specific types of plant diseases, manufacturing defects, or unique inventory items.
Not ideal if you're looking for a pre-trained, ready-to-use model for common objects or if you don't have a dataset of custom-labeled images.
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Jupyter Notebook
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MIT
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Last pushed
Apr 18, 2023
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