labelme2yolo, yolo2labelme format converter

 

original page is here:

https://marearts.notion.site/Labelme2Yolo-Yolo2Labelme-3564dd886ac64b5499d6f2784a8a4be8

yolo2labelme main code

if __name__ == "__main__":

#parameters

paser = argparse.ArgumentParser()

args = paser.parse_args("")

##### set params #####

#input : yolo image, label path

args.yolo_images_path = './yolo_data/images/'

args.yolo_labels = './yolo_data/labels/'

#class count

args.yolo_nc = 80

#class names

args.yolo_names = ['aeroplane', 'apple', 'backpack', 'banana', 'baseball bat', 'baseball glove', 'bear', 'bed', 'bench', 'bicycle', 'bird', 'boat', 'book', 'bottle', 'bowl', 'broccoli', 'bus', 'cake', 'car', 'carrot', 'cat', 'cell phone', 'chair', 'clock', 'cow', 'cup', 'diningtable', 'dog', 'donut', 'elephant', 'fire hydrant', 'fork', 'frisbee', 'giraffe', 'hair drier', 'handbag', 'horse', 'hot dog', 'keyboard', 'kite', 'knife', 'laptop', 'microwave', 'motorbike', 'mouse', 'orange', 'oven', 'parking meter', 'person', 'pizza', 'pottedplant', 'refrigerator', 'remote', 'sandwich', 'scissors', 'sheep', 'sink', 'skateboard', 'skis', 'snowboard', 'sofa', 'spoon', 'sports ball', 'stop sign', 'suitcase', 'surfboard', 'teddy bear', 'tennis racket', 'tie', 'toaster', 'toilet', 'toothbrush', 'traffic light', 'train', 'truck', 'tvmonitor', 'umbrella', 'vase', 'wine glass', 'zebra']

#output : labelme output path

args.labelme_path = './output_yolo2labelme/'

args.labelme_save_image = True #False #create jpg images in output path

#######################

#######################

#start processing

yolo2labelme_main(args)

#######################

labelme2yolo main code

#parameters

paser = argparse.ArgumentParser()

args = paser.parse_args("")

##### set params #####

#input : labelme output path

args.labelme_path = './output_yolo2labelme/'

args.labelme_save_image = True #False #create jpg images in output path

#output : yolo image, label path

args.yolo_images_path = './output_yolo_data/images/'

args.yolo_labels = './output_yolo_data/labels/'

#class count

args.yolo_nc = 80

#class names

args.yolo_names = ['aeroplane', 'apple', 'backpack', 'banana', 'baseball bat', 'baseball glove', 'bear', 'bed', 'bench', 'bicycle', 'bird', 'boat', 'book', 'bottle', 'bowl', 'broccoli', 'bus', 'cake', 'car', 'carrot', 'cat', 'cell phone', 'chair', 'clock', 'cow', 'cup', 'diningtable', 'dog', 'donut', 'elephant', 'fire hydrant', 'fork', 'frisbee', 'giraffe', 'hair drier', 'handbag', 'horse', 'hot dog', 'keyboard', 'kite', 'knife', 'laptop', 'microwave', 'motorbike', 'mouse', 'orange', 'oven', 'parking meter', 'person', 'pizza', 'pottedplant', 'refrigerator', 'remote', 'sandwich', 'scissors', 'sheep', 'sink', 'skateboard', 'skis', 'snowboard', 'sofa', 'spoon', 'sports ball', 'stop sign', 'suitcase', 'surfboard', 'teddy bear', 'tennis racket', 'tie', 'toaster', 'toilet', 'toothbrush', 'traffic light', 'train', 'truck', 'tvmonitor', 'umbrella', 'vase', 'wine glass', 'zebra']

#######################

#######################

#start processing

labelme2yolo_main(args)

#######################

Thank you.

www.marearts.com

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