ndarray | N-dimensional Array Datastructure on CPU and GPU | GPU library

My GUI is able to play videos automatically when selected in the QListWidget. However, instead of normal speed, the videos play very fast. I use 720p Mp4 videos as examples and are placed in a certain folder. I tried using cv2.CAP_PROP_FPS and cv2.CAP_PROP_BUFFERSIZE, but they are both not working. I am using pyqtSignal in the QThread and the convert_cv_qt function which I saw in other guides. How do I play the videos in normal speed / frame rate?

I want to create a PNG image file with palette information in Python using Pillow and/or pypng.

The input is:

1. Palette information

   ...

I am have a time series data and I am trying to build and train an LSTM model over it. I have 1 input and 1 Output corresponding to my model. I am trying to build a Many to Many model where Input length is exactly equal to output length.

The shape of my inputs are X --> (1700,70,401) (examples, Timestep, Features)

Shape of my output is Y_1-->(1700,70,3) (examples, Timestep, Features)

Now When I am trying to approach this problem via sequential API everything is running fine.

I tried following code but "numpy.ndarray' object has no attribute 'append' " this error comes I tried replace the append with other attributes , but any of those methods didnt work for me . can someone run the codes in your pc and suggest me a way to fix this.

I'm trying to slice an Ndarray a with a list b. But the behaviour is not as I would expect it. What do I have to change to get the wanted result?

Suppose I have a list that contains a bunch of numpy ndarrays (or even torch Tensors):

Based on the guide Implementing PCA in Python, by Sebastian Raschka I am building the PCA algorithm from scratch for my research purpose. The class definition is:

The data is basically in CSV format, which is a fasta/genome sequence, basically the whole sequence is a string. To pass this data into a CNN model I convert the data into numeric. The genome/fasta sequence, which I want to change into tensor acceptable format so I convert this string into float e.g., "AACTG,...,AAC.." to [[0.25,0.25,0.50,1.00,0.75],....,[0.25,0.25,0.50.....]]. But the conversion data shows like this (see #data show 2). But, when I run tf.convert_to_tensor(train_data) it gives me an error of Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray). But in order to pass the data into CNN model, it has to be a tensor, but I don't know why it gives an error! What will be the solution to it?

I have this 4D array (numpy.ndarray) that I need to save in a way that its format does not change as I save it (since it should remain unchanged), and then reuse it in my Google Colab file. I have tried saving it in different formats and when I upload it and preview it within my code, the previous format is no longer preserved even when I save it in the .npy format. I have also tried importing the date using the raw link from my GitHub repository or uploading it from my local device, but still no chance. I would appreciate your comments regarding the issue!

Further elaboration:

Here is the code that I use to generate my 4D array: