I appreciate the detail and time you are putting into these lessons. I really want a thorough understanding of this and the way you are teaching is definitely fitting that bill. I hope you continue with the amount of details. This is mirroring some of the content on your artificial intelligence lessons and hearing it again is very helpful. I see in the future lessons that you have uploaded we are going to go even further into the artificial intelligence side which I am very excited about. Looking forward to where you are taking these lessons.
Yes, you will see similar themes in these lessons, with things tailored to the Pi. One difference is, with the Pi we have access to the GPIO pins, so can do more with what we learn from the AI
Very good lesson Paul. Thank you for detailed explanation. I was wondering why the green color pixel output value was changing constantly if the color itself was constant (at around 32nd min of VDO)
Thank you for the great tutorial. One thing is for me not completely clear. You mentioned in the b&w frame array 0=off (black) and 1=on (white). So far so good, but in the next section about grayscale you said 125 is gray (half black half white) and 255 is white). So that means closer to zero is more black and closer to 255 is more white. So far so good but how knows the program 1 is white or nearly black? Many thanks from Austria
Homework submitted th-cam.com/video/-R6FWh7SqKo/w-d-xo.html This was a good refresher from the AI lessons so I revisited the checker board project and added a twist to step it up a notch. Thanks Paul for another great lesson.
Yes, you will see these lessons reinforce what we did in the AI class. But here, we have access to the GPIO pins, so can do cool things like the pan/tilt hat to actually track objects of interst. I am having lots of fun with this series.
![KRK - ชนิสรา Ft.WanMai , N/A [Official MV] Prod. By Sakarin](http://i.ytimg.com/vi/C-WMwwYobcU/mqdefault.jpg)
This lesson reminds me of trying to program in basic (back in about '82-'84), creating image elements called 'imps' (4x4 pixels). Go Space Invaders!!!
Missed the beginning, will restart it later. Thanks for the great content.
so impressive topic to discuss, very needed!
Good lesson - great foundation on picture make up and arrays
Perfect lesson Paul, marvelous thanks.
Really liked the lesson, appreciate the detailed explanation.
Thanks Paul. This is one of them lessons that will click down the line as my brain cell multiplies.
I appreciate the detail and time you are putting into these lessons. I really want a thorough understanding of this and the way you are teaching is definitely fitting that bill. I hope you continue with the amount of details. This is mirroring some of the content on your artificial intelligence lessons and hearing it again is very helpful. I see in the future lessons that you have uploaded we are going to go even further into the artificial intelligence side which I am very excited about. Looking forward to where you are taking these lessons.
Yes, you will see similar themes in these lessons, with things tailored to the Pi. One difference is, with the Pi we have access to the GPIO pins, so can do more with what we learn from the AI
Great review, Paul! It was not too tedious at all. The basics are very important to do the advanced stuff well. Thank you!
This is really very interesting!
Nice review! Well done too...Thanks
Very good lesson Paul. Thank you for detailed explanation. I was wondering why the green color pixel output value was changing constantly if the color itself was constant (at around 32nd min of VDO)
Thanks Paul!
Thank you for the great tutorial. One thing is for me not completely clear. You mentioned in the b&w frame array 0=off (black) and 1=on (white). So far so good, but in the next section about grayscale you said 125 is gray (half black half white) and 255 is white). So that means closer to zero is more black and closer to 255 is more white. So far so good but how knows the program 1 is white or nearly black?
Many thanks from Austria
python allows comment(s) in the array
frame = [
[[0,1,2],[3,4,5],[7,8,9]], # row 0
[[10,11,12],[13,14,15],[17,18,19]], # row 1
]
print( frame[1][2][1] ) # 18
If "tedious" is code for no one left behind, then I'm all for tedious
Tedious but necessary. Get that muscle memory going.
Homework submitted th-cam.com/video/-R6FWh7SqKo/w-d-xo.html
This was a good refresher from the AI lessons so I revisited the checker board project and added a twist to step it up a notch.
Thanks Paul for another great lesson.
Yes, you will see these lessons reinforce what we did in the AI class. But here, we have access to the GPIO pins, so can do cool things like the pan/tilt hat to actually track objects of interst. I am having lots of fun with this series.