yt:channel:UCfzlCWGWYyIQ0aLC5w48gBQ UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2012-12-16T20:49:11+00:00 yt:video:b5xpXecR3LY b5xpXecR3LY UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-07-11T20:10:17+00:00 2017-08-05T20:02:14+00:00 Self-driving cars with Python and TensorFlow update v0.04-v0.06 Recent changes to our self-driving AI: More waypoint following (gps following) data, fine-tuned controlling by emulating an xbox360 controller's input, and adding a speedometer. See the AI live: https://www.twitch.tv/sentdex https://psyber.io/ How this project was made: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ yt:video:mXuEoqK4bEc mXuEoqK4bEc UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-07-10T23:19:48+00:00 2017-08-05T20:03:20+00:00 Cython Tutorial - Bridging between Python and C/C++ for performance gains Welcome to a Cython tutorial. The purpose of Cython is to act as an intermediary between Python and C/C++. At its heart, Cython is a superset of the Python language, which allows you to add typing information and class attributes that can then be translated to C code and to C-Extensions for Python. Text-based tutorial and sample code: https://pythonprogramming.net/introduction-and-basics-cython-tutorial/ yt:video:CGLV22xuCYk CGLV22xuCYk UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-06-20T17:47:06+00:00 2017-08-03T23:01:25+00:00 MSR Cresson 3.1 CCW S2000 March 26 2017 Honda S2000 @ MSR Cresson 3.1 CCW March 26 2017. yt:video:kKnBrTPeLYA kKnBrTPeLYA UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-06-20T17:42:29+00:00 2017-08-05T04:47:15+00:00 Self-driving cars with Python and TensorFlow update v0.03 An update to the self driving cars with Python and Tensorflow update for model v0.03. V0.03 mainly includes a higher resolution (480x270) along with waypoint following information, which I plan to make use of with reinforcement learning. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:aYMUYkk92NY aYMUYkk92NY UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-06-01T17:52:23+00:00 2017-08-05T15:25:46+00:00 AI Agent Changes 0.01-0.03 - Python plays GTA p.16 Support via Patreon: https://www.patreon.com/sentdex Support via Stream: https://twitch.streamlabs.com/sentdex General AI information: https://psyber.io/ 24/7 (ish) live stream: https://www.twitch.tv/sentdex Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:edWI4ZnWUGg edWI4ZnWUGg UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-05-08T15:18:21+00:00 2017-08-05T15:05:46+00:00 Stream, FPV, and more data - Python plays GTA p.15 Our AI friend here, Charles, is a convolutional neural network that learns to drive through deep learning. At the moment, Charles learns and takes all actions based on single frames at a time, and bases his decisions on just pixel data. Charles only sees exactly what you see. In time, I intend to give Charles some short-term memory to hopefully improve his driving. https://www.twitch.tv/sentdex Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:KSX2psajYrg KSX2psajYrg UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-21T18:16:48+00:00 2017-08-05T18:48:17+00:00 Self driving car neural network in the city - Python plays GTA with Tensor Flow p.14 In this self-driving car with Python video, I introduce a newer, much more challenging network and task that is driving through a city. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:nWJZ4w0HKz8 nWJZ4w0HKz8 UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-18T17:11:07+00:00 2017-08-05T13:20:07+00:00 A more interesting self-driving neural network model - Python plays GTA p.13 Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Training data and trained model: https://pythonprogramming.net/more-interesting-self-driving-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:H5D-6IsFn40 H5D-6IsFn40 UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-18T17:11:03+00:00 2017-08-05T10:30:07+00:00 Testing self driving neural network model - Python plays GTA p.12 Welcome to Part 12 of the Python Plays: Grand Theft Auto V tutorial series, where we're working on creating a self-driving car in the game. In the previous tutorial, we trained a convolutional neural network on some game data, and now we're ready to see how we've done. While we trained the convolutional neural network, we saved our progress to a model file. This lets us easily load back in this model and either use it, or even train it some more. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:I1qT-VbA_MM I1qT-VbA_MM UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-18T17:10:59+00:00 2017-08-03T00:26:19+00:00 Training convolutional neural network for self-driving - Python plays GTA p.11 Welcome to Part 11 of the Python Plays: Grand Theft Auto V tutorial series, where we're working on creating a self-driving car in the game. Leading up to this point, we've built a training dataset that consists of 80x60 resized game imagery data, along with keyboard inputs for A,W, and D (left, forward, and right respectively). Next, we need to create and train a neural network for this task. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:wIxUp-37jVY wIxUp-37jVY UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-18T17:10:55+00:00 2017-08-03T00:30:25+00:00 Balancing self-driving training data - Python plays GTA p.10 Welcome to Part 10 of the Python Plays: Grand Theft Auto V tutorial series, where we're working on creating a self-driving car in the game. Before we get into the neural network model, and training it, one other thing to think about is that, chances are, the vast majority of our moves are going to be forward. If we throw data at a neural network that is, for example, 80% biased towards this, the neural network will learn to always predict that class, EXCEPT in cases where it's seen that it is not. The problem here is that the network will almost certainly overfit. So, in training and validation, you might see that you're accuracy is 99%, so surely it's not just only predicting that 80% class, but, then, you throw some out out sample data at the network, or even attempt to actually use it, and you're baffled by the results! Well, you over fit and then created a bunch of rules basically for the edge cases in a case of overfitment. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:E_lN40yhlzY E_lN40yhlzY UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-18T17:10:50+00:00 2017-08-03T00:30:09+00:00 Next steps for self-driving vehicles - Python plays GTA p.8 Welcome to part 8 of the Python Plays: GTA V tutorial series. After the initial release, I got tons of great ideas from all of you, along with some very useful code submissions either in the comments or by a pull request on the Github page. Thank you to everyone for contributing. First, before we move on, let's talk about some of the changes that we've made. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:F4y4YOpUcTQ F4y4YOpUcTQ UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-18T17:10:36+00:00 2017-08-01T01:44:00+00:00 Neural Network Training Data for self-driving - Python plays GTA p.9 Welcome to part 9 of the Python Plays: Grand Theft Auto series, where our first goal is to create a self-driving car. In this tutorial, we're going to cover how we can build a training dataset for a deep learning neural network. Text tutorials and sample code: https://pythonprogramming.net/game-frames-open-cv-python-plays-gta-v/ Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:CLFp9D9-0Eo CLFp9D9-0Eo UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-10T14:59:55+00:00 2017-08-05T17:36:35+00:00 Self-driving Car - Python plays Grand Theft Auto 5 p.7 As I was contemplating the next steps, I was curious about a couple of choices for Artificially Intelligent driving. One thought I had was that we could detect both lanes, and then attempt to orient the car in between the two lanes, so long as those two lanes had different slopes. ...then I began to think about it, and wondered if the problem coudl be even more simple than that. I noticed that the times when the lanes would "both" be on one side or the other was when we were getting to close to one of the edges. So next I wondered, hmm, what if we just work with the following logic: If one lane's slope is positive, and the other is negative, then we're fine, continue straight. If both lane's slopes are negative, then we're too far left, and we should turn right. If both lane's slopes are posotive, then we're too far right, and we should turn left. ...surely it can't be that simple right? Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex yt:video:CAr7UupSUh0 CAr7UupSUh0 UCfzlCWGWYyIQ0aLC5w48gBQ sentdex https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ 2017-04-10T14:59:39+00:00 2017-08-05T12:13:44+00:00 Lane Finding - Python plays Grand Theft Auto 5 p.6 Now, the goal is to determine from these lines, which are likely our actual lanes. I am just going to throw my function in. It's not the best, and I am hoping someone comes up with something better. That said, while we wait for a savior, my code works in the following way: First, find the main lines. Next, find the groups of lines that are similar to eachother (by comparing slope and bias), and save these as "the same line." Next, take the two most common lines, and assume these must be our lanes. After we've done ROI, the next most likely "line" just simply is almost certain to be the lanes. That's the hypothesis anyway! Project Github: https://github.com/sentdex/pygta5 https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex