From 176260d82a4d82ce4ce1f09cd6139a50e1a2aa84 Mon Sep 17 00:00:00 2001
From: Edmond Yoo <hj3yoo@uwaterloo.ca>
Date: Sun, 16 Sep 2018 06:29:06 +0000
Subject: [PATCH] Card matching algo

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 README.md |   12 +++++++++++-
 1 files changed, 11 insertions(+), 1 deletions(-)

diff --git a/README.md b/README.md
index e10253f..2cb7c54 100644
--- a/README.md
+++ b/README.md
@@ -91,4 +91,14 @@
 
 <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.
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+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.png" 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.
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