Mask-RCNN-Implementation
food-recognition-benchmark-starter-kit
Mask-RCNN-Implementation | food-recognition-benchmark-starter-kit | |
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1 | 3 | |
3 | 66 | |
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3.2 | 0.0 | |
about 3 years ago | 7 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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Mask-RCNN-Implementation
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Mask RCNN Implementation for Image Segmentation | Tutorial
1.Git clone the Mask-RCNN-Implementation 2.Install the Mask_Rcnn module.
food-recognition-benchmark-starter-kit
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54392 real-world Food Images with 100,256 annotations
âšī¸ What's unique? These are real images of real food - not a biased data set downloaded from food websites. The images were collected by participants in the foodandyou_ch study (and released with their consent đ). đŧī¸ Dataset preview: https://i.imgur.com/BjH4ypx.png đ Download and know more about the dataset: https://www.aicrowd.com/challenges/food-recognition-benchmark-2022#datasets đ¤ Pre-trained MMdetection & Detectron2 models on this dataset: https://github.com/AIcrowd/food-recognition-benchmark-starter-kit đ Open Benchmark (if you are interested in the ML part): https://www.aicrowd.com/challenges/food-recognition-benchmark-2022/leaderboards
đ¤ Pre-trained MMdetection & Detectron2 models on this dataset: https://github.com/AIcrowd/food-recognition-benchmark-starter-kit
- Dataset containing 54392 real-world Food Images [and computer vision benchmark]
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