Edmond Yoo
2018-10-13 17c776a0eab276e9d1057cb1abf8fd7d77d54ada
README.md
@@ -114,6 +114,6 @@
I've been trying to fiddle with the mask R-CNN using [this repo](https://github.com/matterport/Mask_RCNN)'s implementation, and got to train them with 60 manually labelled image set. The result is not too bad considering such a small dataset was used. However, there was a high FP rate overall (again, probably because of small dataset and the simplistic features of cards).
<img src="https://github.com/hj3yoo/darknet/blob/master/figures/5_rcnn_result_1.jpg" width="360"><img src="https://github.com/hj3yoo/darknet/blob/master/figures/5_rcnn_result_2.jpg" width="360"><img src="https://github.com/hj3yoo/darknet/blob/master/figures/5_rcnn_result_3.jpg" width="360"><img src="https://github.com/hj3yoo/darknet/blob/master/figures/5_rcnn_result_4.jpg" width="360"><img src="https://github.com/hj3yoo/darknet/blob/master/figures/5_rcnn_result_5.jpg" width="360">
<img src="https://github.com/hj3yoo/mtg_card_detector/blob/master/figures/5_rcnn_result_1.png" width="360"><img src="https://github.com/hj3yoo/mtg_card_detector/blob/master/figures/5_rcnn_result_2.png" width="360"><img src="https://github.com/hj3yoo/mtg_card_detector/blob/master/figures/5_rcnn_result_3.png" width="360"><img src="https://github.com/hj3yoo/mtg_card_detector/blob/master/figures/5_rcnn_result_4.png" width="360"><img src="https://github.com/hj3yoo/mtg_card_detector/blob/master/figures/5_rcnn_result_5.png" width="360">
Although it may be worth to generate large training dataset and train the model more thoroughly, I'm being short on time, as there are other priorities to do. I may revisit this later.
Although it may be worth to generate large training dataset and train the model more thoroughly, I'm being short on time, as there are other priorities to do. I may revisit this later. I will be cleaning this repo in the next few days, wrapping it up for now.