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AutoTag-YOLOv8 is an object detection project that uses the YOLOv8 model and leverages the power of SAM and DINGO models for automatic labeling. This repository provides the code and resources needed to train the YOLOv8 model using custom datasets, and perform automatic labeling on images using the SAM and DINGO models.

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BilalAltundag/AutoTag-YOLOv8-Instance-Segmentation-with-SAM-and-DINO-Model

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AutoTag-YOLOv8-Instance-Segmentation-with-SAM-and-DINGO-Model

No more labeling for hours!

AutoTag-YOLOv8 is an object detection project that uses the YOLOv8 model and leverages the power of SAM and DINO models for automatic labeling. This repository provides the code and resources needed to train the YOLOv8 model using custom datasets, and perform automatic labeling on images using the SAM and DINO models.

Auto Detect DINO and SAM : Open In Colab

Instance segmentation with YOLOv8 : Open In Colab

DINO and SAM model otomatic labeled example:

indir (30)

First DINO apply object detection in this image. We give the word and picture that we need to detect as input. After this, in the detected region, the SAM model applies the segmentation process.

Example image output:

indir

Example video output:

Example youtube video

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AutoTag-YOLOv8 is an object detection project that uses the YOLOv8 model and leverages the power of SAM and DINGO models for automatic labeling. This repository provides the code and resources needed to train the YOLOv8 model using custom datasets, and perform automatic labeling on images using the SAM and DINGO models.

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