profile
viewpoint
Tommaso Bendinelli TommasoBendinelli R&D Engineer

ossamaAhmed/AML_Project_One 1

Advanced Machine Learning class @ ETH Zürich

TommasoBendinelli/bebop_autonomy 0

ROS driver for Parrot Bebop Drones 1.0 & 2.0

TommasoBendinelli/cheat_sheets 0

Some useful cheat sheets of commands I keep forgetting

TommasoBendinelli/cs-cheatsheet 0

My public note for computer science domain

TommasoBendinelli/DenseFusion 0

"DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion" code repository

TommasoBendinelli/ElasticFusion 0

Real-time dense visual SLAM system

TommasoBendinelli/generalization_grid_games 0

Games on a 2D grid that require substantial generalization

TommasoBendinelli/iiwaPy 0

A python package for controlling Kuka iiwa from an external PC

TommasoBendinelli/incremental-reading 0

Anki add-on providing incremental reading features

issue commentchrisjsewell/pytest-notebook

Can I skip specific cells in a Jupyter?

For now I will just ignore the output of those cells, but it makes running testing unnecessary heavy

TommasoBendinelli

comment created time in 6 days

issue commentchrisjsewell/pytest-notebook

Can I skip specific cells in a Jupyter?

Alright thank you! Your pluging seems really interesting, but I think this is quite an important feature. For instance with plotly graphs the difftool does not work properly, hence would be nice to skip any cell with plotly graphs inside

TommasoBendinelli

comment created time in 6 days

issue commentchrisjsewell/pytest-notebook

Can I skip specific cells in a Jupyter?

I tried by placing skip in the cell metadata but it does not work apparently

TommasoBendinelli

comment created time in 6 days

issue openedchrisjsewell/pytest-notebook

Can I skip specific cells in a Jupyter?

Hello, I would like to be able to just run specific cells? I would like to skip cells where execution time takes more than 5 sec

created time in 6 days

create barnchTommasoBendinelli/symbolic_equation_generator

branch : main

created branch time in 7 days

created repositoryTommasoBendinelli/symbolic_equation_generator

Package for generating arbitrary sets of symbolic functions.

created time in 7 days

issue commentfoambubble/foam

Focus on the autogenerate graph when clicking on a link

I have open an issue there as well

TommasoBendinelli

comment created time in 9 days

issue openedtchayen/markdown-links

How to autofocus the graph when clicking

Hello, Is there a way to autofocus the graph on the selected markdown? I have a very big graph and it is hard to find the blue dot, an autofocus option would be really nice

created time in 9 days

issue openedfoambubble/foam

Focus on the autogenerate graph when clicking on a link

Hello, I have a graph with many different bubbles. It would be possible, when clicking on a bubble to have the graph to autofocus on the selected bubble?

Best, Tommaso

created time in 9 days

startedfoambubble/foam

started time in 13 days

startedplotly/plotly.js

started time in 17 days

startedathensresearch/athens

started time in 25 days

issue commentpandas-dev/pandas

BUG: df1.values is df1_shallow_copy.values returns false

Yes, indeed, the data it is not copied (if I assign an element to a data frame also the other is affected). It is just weird that to get this counter intuitive result

TommasoBendinelli

comment created time in a month

issue openedpandas-dev/pandas

BUG:

  • [ X] I have checked that this issue has not already been reported.

  • [ X] I have confirmed this bug exists on the latest version of pandas.

  • [ ] (optional) I have confirmed this bug exists on the master branch of pandas.


Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

import pandas as pd
r = pd.DataFrame({"a": [1,2,3], "b": [3,4,5]})
shallow = r.copy(deep=False)
r.values is shallow.values

Problem description

I am making a shallow copy, hence I expect r and shallow's values to point to the same underlying data (as it is described here:https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.equals.html). Instead it is returning False

Expected Output

r.values is shallow.values should return True.

Output of pd.show_versions()

<details>

INSTALLED VERSIONS

commit : 2a7d3326dee660824a8433ffd01065f8ac37f7d6 python : 3.7.6.final.0 python-bits : 64 OS : Darwin OS-release : 18.7.0 Version : Darwin Kernel Version 18.7.0: Tue Aug 20 16:57:14 PDT 2019; root:xnu-4903.271.2~2/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : en_GB.UTF-8 LOCALE : en_GB.UTF-8

pandas : 1.1.2 numpy : 1.18.1 pytz : 2019.1 dateutil : 2.7.5 pip : 19.3.1 setuptools : 49.3.1 Cython : 0.29.14 pytest : 6.0.1 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.10.1 IPython : 7.6.0 pandas_datareader: None bs4 : 4.8.2 bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : 3.0.2 numexpr : 2.7.1 odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pytables : None pyxlsb : None s3fs : None scipy : 1.2.0 sqlalchemy : None tables : None tabulate : 0.8.7 xarray : None xlrd : None xlwt : None numba : None </details>

created time in a month

issue openedNVIDIA/MinkowskiEngine

Question: Combining Minkowski Engine with standard pytorch layers.

I would like to know if it is possible to use layers from your package with standard pytorch layers. Particularly I would like my point cloud dataset and then pass the result to the rest of my network that I have already implement in standard pytorch code.

created time in a month

startedNVIDIA/MinkowskiEngine

started time in a month

issue openedtypora/typora-issues

links to headings in other markdown texts

I have read the informative guide about links in https://support.typora.io/Links/. I would like to know if it is possible to have a link toward heading in other markdown files.

Best, Tommaso

created time in a month

startedinstadeepai/AlphaNPI

started time in a month

startedgoogle-research/realworldrl_suite

started time in a month

issue commenttypora/typora-issues

Cannot click of Iframe embedding

But why does this work if I embed the iframe into an html page? Is there any workaround?

TommasoBendinelli

comment created time in 2 months

starteddatarobot-community/symbolic-regression-python

started time in 2 months

startedlucasrowe/spoiled

started time in 2 months

startederdincmutlu/blocktrail

started time in 2 months

issue openedtypora/typora-issues

Cannot click of Iframe embedding

So I have Typora document with following embedding:

<iframe frameborder="0" style="width:100%;height:493px;" src="https://viewer.diagrams.net/?highlight=0000ff&edit=_blank&layers=1&nav=1#RzZZvb9owEMY%2FDS%2BHQkJSeDko7SbRriqTNl4ack28ObnIOJDs0%2B9CLuQfRa20ir2JfI%2FPse%2F3xI4HzjzK7rVIwgf0QQ1sy88Gzu3Atqdjj56FkJeC605LIdDSL6VRLazkH2DRYjWVPuxaiQZRGZm0xS3GMWxNSxNa46Gd9oKqPWsiAugJq61QffWH9E1YqhP7pta%2FgAzCauaRx%2FVFokrmSnah8PHQkJzFwJlrRFO2omwOqmBXcSnH3b3Se1qYhti8ZcC3TZqtH9Lke75UM%2FurDO%2Bk94nfshcq5YJ5sSavCIBPQDhEbUIMMBZqUaszjWnsQzGNRVGds0RMSByR%2BAuMydldkRokKTSR4t5%2BKbyuHaZ6CxfW7%2FAnIXQA5kLeuMwramlMwKDuASMwOqcEDUoYuW%2BbL%2FgbCk55NWZqMOl3UL8KZGKr85%2FF%2BKFbhWt%2B3TG4zVpRztHHm%2BP%2BV%2BY4vS3xNFyTcGxbI8uibeYpqme20dQKitbT8LGT0fVXKTqxCh8PoTSwSsSR3IHOzDduhT1oA9lFPtzruFwCH7l2tZ5DfYCNqlMpbBxeE%2BuDkI57SJcNpPYZoMsGUPfKPE%2F%2FIubpTK%2FN0%2B3xfG7wnE7OAH2ugXoiKiDFm11yBHR1wG4X8OTagL0zgB8rtB1SVKRpI9kZjb9hjgo1KTHGBcYXqVRHEkoGMYVbQgekzwpkku4en7kjkr6vXvOg%2FUP4FzbYbsuG8U3fhukZF%2Bz3u0BhffE59jVuj87iLw%3D%3D"></iframe>

I would like to click on the pencil that redirects me to another link in the browser. But it seems that it does not work. In Chrome instead I can click on the pencil with no issue

created time in 2 months

issue commentmentian/object-posenet

install knn fails

Not really. I was using a standard ubuntu machine.

TommasoBendinelli

comment created time in 2 months

issue openedcaltechlibrary/handprint

Segmentation fault on macOS Mojave

(env) tommasos-mbp:TestHandwriting tommaso$ handprint -s amazon-textract test-1.png ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ ┃ Welcome to Handprint, the Handwritten page recognition test! ┃ ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛ Will apply 1 service (amazon-textract) to 1 image. Will use up to 2 process threads. Starting on test-1.png Sending to amazon-textract and waiting for response ... Got result from amazon-textract. Creating annotated image for amazon-textract. /Users/tommaso/Documents/Code/CSEM_repos/TestHandwriting/env/lib/python3.7/site-packages/handprint/images.py:218: UserWarning: Starting a Matplotlib GUI outside of the main thread will likely fail. fig, axes = plt.subplots(nrows = 1, ncols = 1, figsize = (20, 20)) 2020-08-05 15:02:36.591 Python[2255:77879] ApplePersistenceIgnoreState: Existing state will not be touched. New state will be written to (null) 2020-08-05 15:02:36.623 Python[2255:77879] *** Terminating app due to uncaught exception 'NSInternalInconsistencyException', reason: 'NSWindow drag regions should only be invalidated on the Main Thread!' *** First throw call stack: ( 0 CoreFoundation 0x00007fff381f8a7d __exceptionPreprocess + 256 1 libobjc.A.dylib 0x00007fff628caa17 objc_exception_throw + 48 2 CoreFoundation 0x00007fff382125d9 -[NSException raise] + 9 3 AppKit 0x00007fff357b85ca -[NSWindow(NSWindow_Theme) _postWindowNeedsToResetDragMarginsUnlessPostingDisabled] + 317 4 AppKit 0x00007fff357b59f7 -[NSWindow _initContent:styleMask:backing:defer:contentView:] + 1479 5 AppKit 0x00007fff357b542a -[NSWindow initWithContentRect:styleMask:backing:defer:] + 45 6 _macosx.cpython-37m-darwin.so 0x0000000116d7cc40 -[Window initWithContentRect:styleMask:backing:defer:withManager:] + 80 7 _macosx.cpython-37m-darwin.so 0x0000000116d808b4 FigureManager_init + 292 8 Python 0x000000010bf1df30 wrap_init + 12 9 Python 0x000000010bee589d wrapperdescr_call + 337 10 Python 0x000000010bedfc46 _PyObject_FastCallKeywords + 358 11 Python 0x000000010bf75322 call_function + 730 12 Python 0x000000010bf6e297 _PyEval_EvalFrameDefault + 6767 13 Python 0x000000010bee01a4 function_code_fastcall + 106 14 Python 0x000000010bee0b17 _PyObject_Call_Prepend + 131 15 Python 0x000000010bf1de9e slot_tp_init + 80 16 Python 0x000000010bf1abca type_call + 172 17 Python 0x000000010bedfc46 _PyObject_FastCallKeywords + 358 18 Python 0x000000010bf75322 call_function + 730 19 Python 0x000000010bf6e297 _PyEval_EvalFrameDefault + 6767 20 Python 0x000000010bee01a4 function_code_fastcall + 106 21 Python 0x000000010bf75329 call_function + 737 22 Python 0x000000010bf6e297 _PyEval_EvalFrameDefault + 6767 23 Python 0x000000010bf75b1d _PyEval_EvalCodeWithName + 1698 24 Python 0x000000010bedfa10 _PyFunction_FastCallDict + 444 25 Python 0x000000010bee0b17 _PyObject_Call_Prepend + 131 26 Python 0x000000010bedfedd PyObject_Call + 136 27 Python 0x000000010bf6e57b _PyEval_EvalFrameDefault + 7507 28 Python 0x000000010bf75b1d _PyEval_EvalCodeWithName + 1698 29 Python 0x000000010bedfa10 _PyFunction_FastCallDict + 444 30 Python 0x000000010bf6e57b _PyEval_EvalFrameDefault + 7507 31 Python 0x000000010bf75b1d _PyEval_EvalCodeWithName + 1698 32 Python 0x000000010bedfa10 _PyFunction_FastCallDict + 444 33 Python 0x000000010bf6e57b _PyEval_EvalFrameDefault + 7507 34 Python 0x000000010bf75b1d _PyEval_EvalCodeWithName + 1698 35 Python 0x000000010bedfa10 _PyFunction_FastCallDict + 444 36 Python 0x000000010bf6e57b _PyEval_EvalFrameDefault + 7507 37 Python 0x000000010bf75b1d _PyEval_EvalCodeWithName + 1698 38 Python 0x000000010bedfd98 _PyFunction_FastCallKeywords + 212 39 Python 0x000000010bf75329 call_function + 737 40 Python 0x000000010bf6e3da _PyEval_EvalFrameDefault + 7090 41 Python 0x000000010bf75b1d _PyEval_EvalCodeWithName + 1698 42 Python 0x000000010bedfd98 _PyFunction_FastCallKeywords + 212 43 Python 0x000000010bf75329 call_function + 737 44 Python 0x000000010bf6e332 _PyEval_EvalFrameDefault + 6922 45 Python 0x000000010bee01a4 function_code_fastcall + 106 46 Python 0x000000010bee0b17 _PyObject_Call_Prepend + 131 47 Python 0x000000010bedfedd PyObject_Call + 136 48 Python 0x000000010bf6e57b _PyEval_EvalFrameDefault + 7507 49 Python 0x000000010bee01a4 function_code_fastcall + 106 50 Python 0x000000010bf75329 call_function + 737 51 Python 0x000000010bf6e27e _PyEval_EvalFrameDefault + 6742 52 Python 0x000000010bee01a4 function_code_fastcall + 106 53 Python 0x000000010bf6e57b _PyEval_EvalFrameDefault + 7507 54 Python 0x000000010bee01a4 function_code_fastcall + 106 55 Python 0x000000010bf75329 call_function + 737 56 Python 0x000000010bf6e27e _PyEval_EvalFrameDefault + 6742 57 Python 0x000000010bee01a4 function_code_fastcall + 106 58 Python 0x000000010bf75329 call_function + 737 59 Python 0x000000010bf6e27e _PyEval_EvalFrameDefault + 6742 60 Python 0x000000010bee01a4 function_code_fastcall + 106 61 Python 0x000000010bee0b17 _PyObject_Call_Prepend + 131 62 Python 0x000000010bedfedd PyObject_Call + 136 63 Python 0x000000010bfdbd01 t_bootstrap + 71 64 Python 0x000000010bfa30be pythread_wrapper + 25 65 libsystem_pthread.dylib 0x00007fff6428c2eb _pthread_body + 126 66 libsystem_pthread.dylib 0x00007fff6428f249 _pthread_start + 66 67 libsystem_pthread.dylib 0x00007fff6428b40d thread_start + 13 ) libc++abi.dylib: terminating with uncaught exception of type NSException Abort trap: 6

created time in 2 months

issue commentTranskribus/TranskribusCore

Text2Image tool returns empty transcription

Might be that the input picture format is playing a part (Although the segmentation is being performed correctly on my document document)

TommasoBendinelli

comment created time in 2 months

issue openedTranskribus/TranskribusCore

Text2Image tool returns empty transcription

Hi there! I am playing around with your tool and I tried to automatically transcribe a document of mine. Then I exported the document with the txt option and imported again to test out the Text2Image tool.

When importing the txt and images together I get lines in the trascription widget but of course they are not linked in the canvas. I then try to run the Text2Image tool with the default settings.

Unfortunately the output of the tool is an empty transcription. Is it me doing something wrong or there is an underlying issue? I tried with both English Writing M1 as base model and English Writing M2.

I also followed the same procedure with the file "English_Handwriting 0.1", where I get good results.

Best, Tommaso

created time in 2 months

startedcaltechlibrary/handprint

started time in 2 months

push eventTommasoBendinelli/incremental-reading

Tommaso Bendinelli

commit sha 0113ae348b683c58bc82583a084c1543b8efe091

trying out travis

view details

push time in 3 months

push eventTommasoBendinelli/incremental-reading

Tommaso Bendinelli

commit sha 1740993b5d8aac83fd63b4882873b44fcc0c0bc0

just try travis

view details

push time in 3 months

startedluoliyan/incremental-reading

started time in 3 months

startedlccasagrande/Deep-Knowledge-Tracing

started time in 3 months

startedUnickSoft/graphonline

started time in 3 months

issue commentfasiha/ebisu

Anki Implementation of Ebisu algorithm

Thank you for the resources, I did not know about memorise!

TommasoBendinelli

comment created time in 3 months

issue commentfasiha/ebisu

Anki Implementation of Ebisu algorithm

Thank you for the great answer and congrats again for this super repo. The code of the paper is available here https://github.com/rddy/deeptutor, although it is just a large Jupiter notebook.

I agree with you that simulating students just provided blurry confidence in algorithm performances, but apart from a real experiment, it is the best evaluation method we can get. Also, I think that although all the factors that you mention are important for improving the learning experience, I also believe that a "great" SRS algorithm can make a difference, especially for "mature" cards (i.e., cards with long-expected half-life).

My end goal would be to create an SRS algorithm based on Reinforcement Learning (it sounds a bit fancy), not only to predict the recall but also to automatically scheduling cards review. This algorithm would be, correct me if I am wrong, a bit different from Ebisu, where the recall threshold for performing the review is fixed. Ideally, the algorithm should find the optimal trade-off between maximizing recall probability and reducing the number of reviews.

Currently, I am exploring the field, although the literature is a bit scarce. Besides your repo and the mentioned paper, I am looking at the Duolingo half-life regression algorithm and this blog: https://papousek.github.io/modeling-prior-knowlegde-using-duolingo-data-set.html. Probably, you are already aware of these resources.

I have in mind to start coding in the next days by creating a reliable benchmark for evaluating the different algorithms and approaches (definitely Ebisu), similar to what the mentioned paper has done.

I would be delighted if you want to work jointly on this idea. If you are up to, we can even arrange a call to discuss the details.

TommasoBendinelli

comment created time in 3 months

startedfasiha/ebisu

started time in 3 months

more