From 504ece5b00f192d5c1b343fd06ce1648f9139180 Mon Sep 17 00:00:00 2001 From: Edmond Yoo <hj3yoo@uwaterloo.ca> Date: Mon, 17 Sep 2018 03:06:19 +0000 Subject: [PATCH] Code cleaning & training new YOLO model --- README.md | 24 +++++++++++++++++++++++- 1 files changed, 23 insertions(+), 1 deletions(-) diff --git a/README.md b/README.md index e4b5500..0d00b55 100644 --- a/README.md +++ b/README.md @@ -79,4 +79,26 @@ ## Sept 14th, 2018 -------------------- -Thankfully, OpenCV had an implementation for DNN, which supports YOLO as well. They have done quite an amazing job, and the speed isn't too bad, either. I can score about 20~25fps on my tiny YOLO, without using GPU. \ No newline at end of file +Thankfully, OpenCV had an implementation for DNN, which supports YOLO as well. They have done quite an amazing job, and the speed isn't too bad, either. I can score about 20~25fps on my tiny YOLO, without using GPU. + + +## Sept 15th, 2018 +-------------------- + +I tried to do an alternate approach - instead of making model identify cards as annonymous, train the model for EVERY single card. As you may imagine, this isn't sustainable for 10000+ different cards that exists in MTG, but I thought it would be reasonable for classifying 10 different cards. + +Result? Suprisingly effective. + +<img src="https://github.com/hj3yoo/darknet/blob/master/figures/4_detection_result_1.jpg" width="360"> <img src="https://github.com/hj3yoo/darknet/blob/master/figures/4_detection_result_2.jpg" width="360"><img src="https://github.com/hj3yoo/darknet/blob/master/figures/4_detection_result_3.jpg" width="360"> <img src="https://github.com/hj3yoo/darknet/blob/master/figures/4_detection_result_4.png" width="360"> + +They're of course slightly worse than annonymous detection and impractical for any large number of cardbase, but it was an interesting approach. + +------------------ + +I've made a quick openCV algorithm to extract cards from the image, and it works decently well: + +<img src="https://github.com/hj3yoo/darknet/blob/master/figures/4_detection_result_5.jpg" width="360"> + +At the moment, it's fairly limited - the entire card must be shown without obstruction nor cropping, otherwise it won't detect at all. + +Unfortunately, there is very little use case for my trained network in this algorithm. It's just using contour detection and perceptual hashing to match the card. \ No newline at end of file -- Gitblit v1.10.0