import numpy as np import scipy.stats as stats import pandas as pd def segment_data_with_labels(features, labels, frame_size, hop_size): result_frames = [] result_labels = [] for i in range(0, len(features) - frame_size+1, hop_size): segment = features.iloc[i: i+frame_size] if len(segment) < frame_size: break # If the segment is smaller than frame_size,...
Hello everyone, today the ICML results are out, congratulations to all those who have papers accepted here. I'm not an academic myself, but sometimes I read papers at these conferences for work, and it's really interesting. I just have a question: why do juniors have so many papers at these conferences? I thought this was something you would have to...
I am using seq2seq model for predicting or correcting spellings for the product names, I do have dataset of product names with their misspelled and corrected versions(they do contain some special chars too). I have trained that data on few epochs and see some output. But i am giving the user input, it isn't predicting as expected. Then, after training...
Dear people :) A few weeks ago someone was looking for mentees. I really loved this initiative and a lot of people already wrote him, asking if they could be his mentee. Now I want to be proactive and seek out for a mentor. :) Maybe for my background: I studied medicine and then learned coding in a coding school (42Heilbronn). I also did some course...
My training images have texts that appear in various orientations on the image. As a result, I don't know what's their original orientation since for example DBNetPP does not return the bbox angles in the corners in a natural orientation order. How can I solve this issue? I have tried other pretrained detection models, but they also does not do that,...
https://youtu.be/SOovRRz0Iuo?si=LqRxzyj-cSxLeBYM what text to speech does he use? he's been popping up on my yt feed lately. Those type of vids usually sound too robotic, but this one is actually decent. What do you think it is? submitted by /u/Inner-Wishbone-3877 [link] [comments]
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