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I think demo dataset infrastructure would be useful.
I made a PR proposal for napari here: https://github.com/napari/napari/pull/3580 (it's based on scikit-image: they use [pooch](https://www.fatia…
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In general, **Augraphy** is trying to simplify the process of creating synthetic realistic datasets using only ground truth documents.
Often, training data is not accompanied by clean ground truth …
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## Description
In 8.5 we introduced a new tab to document the available field to create a package policy programmatically, a simplified package policy API
Unfortunately this is not working…
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What you wrote is very helpful for my work. Can you share your environment configuration and data design？ Thank you
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Second paragraph ~
>But there is more to machine learning than just solving discriminative tasks. For example, given a large dataset, without any labels, we might want to **learn a model** that co…
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Hi,
I've been tinkering around with supercluster and deck.gl to visualize large datasets. I'm using synthetic dataset of a 600 by 600 grid to test performance and wanted to better visualize/underst…
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Thanks for your great implementation of Tensorflow LPRNet!
Unfortunately, training on my own synthetic german license plate data does not give me good results so far. I have 10k images and trained …
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# References
+ [Introduction To Autoencoders In Machine Learning](https://youtu.be/NZ97-lFEUq8)
+ [Convolutional autoencoder for image denoising](https://keras.io/examples/vision/autoencoder/)
+ [B…
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When generating synthetic tracks, if a storm makes landfall, re-emerges over ocean, and then makes a second landfall that lasts one hour, the wind speed abruptly re-strengthens to the original storm's…
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```
import torch
import glob
import json
import numpy as np
import os
from tqdm import tqdm
from pathlib import Path
from .ray_utils import get_ray_directions
from .color_utils import read_…