This is my blog about my newest discovery of the world around me!
Meeting
Get link
Facebook
X
Pinterest
Email
Other Apps
MRL-SPL
This is our formal Sprint Review Meeting. We review what has done and we discus about what we accept as done. Then we discus about what we are going to do in our next sprint.
I just have read an article about replanting a pineapple, and guess what; here I am! After reading couple of search queries, I decided to start this process. Let's see what happens! I have removed the rest of the fruit. Also, removed the lower leafs. According to the article [and search queries], I should wait couple of days till the lower part is completely dries. Then I can soak it into water for few weeks and hopefully the roots start to grow! Afterward, I am able to plant it in the clay. The only problem is I need somewhere with really high amount of sunlight! [Which there is none in my room...]. A Pineapple If everything goes well, this cute plant will be my friend for a while. I really enjoy having such a thing on my desk. Please let me know if you have ever tried to replant a pineapple. I am really looking for some experience in this field!
As the SPL rule change in 2016, the official ball has changed. Now, robots should play soccer with a black and white, foam ball. The ball, is mostly white, with black pentagons on it. Since it is the same color with goal posts, field lines and other robots, it is harder for robots to distinguish the new ball from these objects. Formerly, as well as the ball was orange, it was uniquely colored in the field. So, it could be detected simply by searching the image for specific colors, and then just by applying few filters such as width and shape. At the beginning, our strategy for detecting ball after this change, was to simply calculating image edges, and applying a Hough transform on it. Then we were expecting an acceptable outcome just by applying few filters on the result. But it didn't work! There were more problem than we expected. Calculating edge for whole image was super heavy, so we had to reduce the image resolution 4 times. Then, since the resolution was too low, the...
After a hard period of preparation for TOEFL and GRE test, I am finally back to routine: programming! Right now I am kinda into freelancing along with my research hobbies. And now, as I am righting this post, my laptop is busy training a neural network for human face emotion detection. First I get a little taste of Google Tensor Flow library and it was amazingly easy to build and use! However, the possibilities today goes even further. I found a python wrapper for it, named TFLearn! Which makes Tensor Flow easy as few lines! And right now I am training my network with a dataset of faces that I got from Kaggler website to see whether the TFLearn is working or not. (I hope it does!) If everything goes well, I'll be able to recognize the emotion of the faces that has been detected by OpenCV.
Comments
Post a Comment