matlab-deep-learning/Automate-Labeling-in-Image-Labeler-using-a-Pretrained-TensorFlow-Object-Detector
This example shows how to automate object labeling in the Image Labeler app using a TensorFlow object detector model trained in Python.
This tool helps computer vision practitioners and researchers quickly and accurately label objects in images for training deep learning models. It takes your unlabelled images and a pre-trained TensorFlow object detection model, automatically identifying objects like vehicles, people, or animals, and outputs labeled images with bounding boxes. This drastically speeds up the data preparation phase for building your own custom object detectors.
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Use this if you need to create accurate labeled datasets for object detection tasks but want to avoid the time-consuming process of manual labeling for every image.
Not ideal if you do not work with images, or if your labeling needs extend beyond bounding box object detection (e.g., semantic segmentation, keypoint detection) and you require a different type of automation.
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Sep 28, 2022
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