Mask-RCNN 실습모음(2021-07-29~02)
이론 내용은 아래 링크에서 확인할수 있습니다.
2021.07.30 - [기록 note] - 2021-07-29(Mask-RCNN_Segmentation)
2021-07-29(Mask-RCNN_Segmentation)
Semantic Segmentation이란 masking 정보를 씌어서 전체 이미지에서 문맥적으로 의미 있는 형태를 찾아내는 개념이다. Instance Segmentation과 차이점이 있다면 동일한 객체에 대한 표현방식에 있다. Semantic은
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1.coco_annotations_mask_visuals(COCO_Dataset를 활용한 mask Segmentation)
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2. opencv_mask_rcnn_inference(임의의 image inference)
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3.mm_mask_rcnn_inference(MMDetection)
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4.mm_mask_rcnn_train_pascal_voc(Pascal VOC Datasets -> COCO Datasets 변경후 trained)
https://colab.research.google.com/drive/1UrgKD_lY6eAD5jVEGelEg78MmhX_ZMNR?hl=ko
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5.mm_mask_rcnn_train_balloon(balloon Datasets -> COCO Datasets 변경후 trained)
https://colab.research.google.com/drive/1AZ8vWDp_H1ik3q7am-d_rYhaxR-uILOu?hl=ko
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6. nucleus dataset로 실습(마찬가지로 COCO format으로 변경후 trained)
https://colab.research.google.com/drive/1xPmaW9u34OlGT6ZXF0OSvgUnchyUgQQs?hl=ko
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