From a055821b732f748524680d08ffbcef5cbef25713 Mon Sep 17 00:00:00 2001 From: Edmond Yoo <hj3yoo@uwaterloo.ca> Date: Mon, 17 Sep 2018 06:43:16 +0000 Subject: [PATCH] Fine-tuning opencv --- README.md | 32 +++++++++++++++++++++++++++++++- 1 files changed, 31 insertions(+), 1 deletions(-) diff --git a/README.md b/README.md index e4b5500..82829c7 100644 --- a/README.md +++ b/README.md @@ -79,4 +79,34 @@ ## 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. + + +## Sept 16th, 2018 +-------------------- + +I've tweaked the openCV algorithm from yesterday and ran for a demo: + +https://www.youtube.com/watch?v=BZkRZDyhMRE&feature=youtu.be \ No newline at end of file -- Gitblit v1.10.0