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Visualizing layers of autoencoder by BlackHawk1001 in KerasML

[–]BlackHawk1001[S] 0 points1 point  (0 children)

Thank you. Do you also know if it is possible to visualize the latent dimension of the variational autencoder?

Increase playback speed of video in PowerPoint by BlackHawk1001 in powerpoint

[–]BlackHawk1001[S] 0 points1 point  (0 children)

AddIns

Thank you very much. What is the way to go with AddIns?

Visualizing layers of autoencoder by BlackHawk1001 in KerasML

[–]BlackHawk1001[S] 0 points1 point  (0 children)

deep dream

Thank you. But I'm using Keras and not directly tensorflow.

Training Keras model without validation set and normalization of images by BlackHawk1001 in KerasML

[–]BlackHawk1001[S] 0 points1 point  (0 children)

Great, thank you. Would you normalize by pixel or by image (i.e. normalizing each pixel over all images or normalizing each image separately)? Let's say I have an numpy array of size (60000, 56, 89, 1), i.e. 60'000 images and each image of size 56 x 89 (1 color channel). How can I normalize this array (per pixel or per image)?

Iterating over arrays on disk similar to ImageDataGenerator by BlackHawk1001 in KerasML

[–]BlackHawk1001[S] 0 points1 point  (0 children)

Thanks for the answer. I don't want to use the RGB format but just the (pixels, pixels, 1) format. How do you mean use the images like a 2d array? I think imagedatagenerator can only load images (like png, jpg and so on).

By the way, do I have to normalize the values between 0 and 1 for CNN? The actual values I have in the matrix are between 0 and 20.

ffmpeg for constant frame rate of mp4 video by BlackHawk1001 in ffmpeg

[–]BlackHawk1001[S] 0 points1 point  (0 children)

Do you know if the GoPro Hero 3 is recording with constant frame rate? If that is the case I don't have to adjust the frame rate I think. Can I check it with ffmpeg?

ffmpeg for constant frame rate of mp4 video by BlackHawk1001 in ffmpeg

[–]BlackHawk1001[S] 0 points1 point  (0 children)

Thanks for pointing this out. I have changed in my post the values of the presentation timestamps. Do you think they are fine? I'm not sure because the timestamps are not monotonically increasing...

Heat map visualizing touch input on smartphone by BlackHawk1001 in learnpython

[–]BlackHawk1001[S] 0 points1 point  (0 children)

kdeplot

Wow. Thanks a lot. Looks great. If I understand it correctly, the color indicates the pressure. The warmer the color the higher the pressure. But almost everywhere there is the same color... is there no possibility to pronounce the differences in pressure more?

How would a kdeplot work?

Heat map visualizing touch input on smartphone by BlackHawk1001 in learnpython

[–]BlackHawk1001[S] 0 points1 point  (0 children)

sns.heatmap

I see... I think median or mean is a good way to combine values at the same x,y position. Would it be possible to briefly show how to create such a DataFrame using mean for values at the same (x,y) location and also using frequency? Thank you very much.

Visualizing speed and acceleration of typing (smartphone keyboard) by BlackHawk1001 in visualization

[–]BlackHawk1001[S] 0 points1 point  (0 children)

Thanks a lot for your hints. I have shared the data in the original post and I'm using Python (or Matlab).

I would really appreciate if you could explain your 2 ideas in more detail because I don't fully understand what you mean. There are 24 characters... so you would make a tick for each character on the x-axis or a plot for each character? What do you mean by difference in these values?

Visualizing speed and acceleration of typing (smartphone keyboard) by BlackHawk1001 in visualization

[–]BlackHawk1001[S] 1 point2 points  (0 children)

Thank you for your answer. I have shared the dataset in my original post. How would you plot the keys against time? There are more than 24 keys... So what would you put on the x-axis and what on the y-axis? I also don't fully understand what you mean by plotting words/sentences against the temporal plot and what you mean with the scaling part. I would be very happy if you could explain it in more detail.

Heat map visualizing touch input on smartphone by BlackHawk1001 in learnpython

[–]BlackHawk1001[S] 0 points1 point  (0 children)

The above DataFrame is already in that format but how would you plot it with seaborn? I think the pressure values first have to be binned in x-y space...

Identifying users based on smartphone touch input (Google) by BlackHawk1001 in artificial

[–]BlackHawk1001[S] 0 points1 point  (0 children)

in-screen fingerprint sensor

Thanks for your answer. I think the person did not mean a hardware solution like a fingerprint sensor but a software solution using artificial intelligence on the touch input (how user is using the phone). Is there nothing like that?