CODEWITHSUNDEEP
object-detectionyolo
Y W
Y W

Reputation: 25

How to generate the labels of custom data for YOLO

The labels for YOLO is like [class, x , y, width, height] . Since the dataset is very large, is there any shortcut to generate the labels for YOLO, or we have to hardcode them through measurement?

Upvotes: 0

Views: 4562

Answers (1)

Addie Ira B. Parico
Addie Ira B. Parico

Reputation: 617

Method 1: Using Pre-trained YOLOv4 models. YOLOv4 models were pre-trained on COCO dataset. So, if your object(s) can be found in this list, then, you can use the pre-trained weights to pseudo-label your object(s).

To process a list of images data/new_train.txt and save results of detection in Yolo training format for each image as label <image_name>.txt, use: darknet.exe detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights -thresh 0.25 -dont_show -save_labels < data/new_train.txt

Method 2: Using Other Pre-trained Models. It's the same concept. Use other pre-trained models to detect your object (as long as they have trained their models on your object), then export/convert the labels to YOLO format.

Method 3: Use hand-crafted feature descriptors. Examples are shape detection, color-based detection, etc.

Method 4: Manual labelling. If everything else fails, do the labelling yourself or hire some data labelling services. Here's a list of tools that you can use if you want to label them yourself.

Upvotes: 1

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