Can I use PyTorch tensors instead of NumPy arrays while working with scikit-learn? I tried some methods from scikit-learn like train_test_split and StandardScalar, and it seems to work just fine, but is there anything I should know when I’m using PyTorch tensors instead of NumPy arrays? According to this question on https://scikit-learn.org/stable/faq.html#how-can-i-load-my-own-datasets-into-a-format-usable-by-scikit-learn : numpy arrays or scipy sparse matrices. Other
Tag: numpy
How to get multiple images from Flask request object at once in case of Content-Type:multipart/form-data?
I’m supposed to get multiple image files from the requests, but I can’t find a way to split a byte string request.files[key].read() properly to make np.ndarrays out of them. Answer files[key] gives only one object which has name=key in HTML, and .read() gives data only for this single file. So there is no need to split it. If you have
Find center of blocks of ones in an 2d array
Lets assume I have the following array and want to get the center of each block of ones, so that I can get the following array: I already thought about using means or convolutions, but I couldn’t think of a really simple solution. One in efficient solution that I found is: Answer This is a little less inefficient, since no
How can I select top k rows based on another dataframe in python?
I have data as follows. Users are 1001 to 1004 (but actual data has one million users). Each user has corresponding probabilities for the variables AT1 to AT6. I would like to select the top 3 users for each choice based on the following data. In the output, top1 to top3 are the top 3 users based on probability for
Pandas: Unable to merge on two date columns
I have two dataframes that look like: df1: df2: Both date columns have been made using the pd.to_datetime() method, and they both supposedly have <M8[ns] data types when using df1.Date.dtype and df2.Date.dtype. However when trying to merge the dataframes with pd.merge(df,hpi,how=”left”,on=”Date”) I get the error: ValueError: You are trying to merge on object and datetime64[ns] columns. If you wish to
get first 2 characters of each index in array in python
I am trying to access the first two letters of each index in a numpy array in python: I have read previous forum of the error “‘int’ object is not subscriptable , I know it;s not a string, but for my work it’s better to be numpy.array or if anyone suggest me with another thing, please help, Here is my
shrink and enlarge contour image with Python OpenCV
I have an image with an object like below: I can detect the contour and get a mask with only ball region, but my ROI is the edge region, that means I need a bigger and a smaller mask which combine to get this: so my question is: how can I shrink/enlarge the mask of contour around contour’s center? Answer
Zipping two np.array into array
Im trying to combine following two np.arrays into a single array: The combination array must look like this [[i, pred, boxes],…]: I tried doing it this way, but it unfortunately didn’t work: Is there a way to do this? I tried other means but those tries were even worse. Answer Try hstack:
TypeError: cannot concatenate object of type ”; only Series and DataFrame objs are valid
I have a list of 10 dataframes named d0, d1, d2,…d9. All have 3 columns and 100 rows. I want to merge all dataframes so that I can have 3 columns and 1000 rows and then convert it into an array. The above code throws error: I used the solution suggested in pd.concat in pandas is giving a TypeError: cannot
Apply threshold for numpy.ndarray
I have a model predictions type of numpy.ndarray The predictions looks like where the first value of inner array corresponds to 0 class and the second value corresponds to 1 class. For this y_pred i need to apply FNR threshold 0.21552509277542697, which i also calculated. That is the efficient numpy way to do it ? The result should be in