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Turi Create Visualisation often stuck on "Loading" screen #88

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AndrewHartAR opened this issue Dec 13, 2017 · 46 comments
Open

Turi Create Visualisation often stuck on "Loading" screen #88

AndrewHartAR opened this issue Dec 13, 2017 · 46 comments

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@AndrewHartAR
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I don't know what additional information to provide here, as it's happened in a number of different situations. With a large or very small data set, Turi Create Visualisation remains stuck on the "Loading" screen and never loads. Sometimes I can run the same code again, and it will load almost instantly with all data shown. But often, it'll not move past that initial screen. Sometimes re-running it works.

Right now I'm simply following the Image Classification and Object Detection tutorials, so not doing anything particularly advanced. This occurred when calling explore() after creating the initial cats/dogs data set, and even when slimming that data set down to just 6 images.

Let me know if you need more specifics.

@znation
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znation commented Dec 13, 2017

@ProjectDent Thanks for reporting this. So far I haven't seen this happening in general, and it seems hard to reproduce. Do you notice any patterns in when it happens, relating to any of the following? I'm trying to narrow down what might be causing it.

  • Are the SFrames being shown newly loaded (from CSV, or SFrame format), or based on the result of some computation?
  • Are they loaded from local disk or network? SSD or magnetic drive?
  • How often does it happen on different datasets? Does it always seem to happen on the same data (or with similar characteristics)?
  • How often does it happen, if done repeatedly on the same dataset? Only the first time, and every subsequent call is fast? Or is it intermittent throughout?

@znation znation self-assigned this Dec 13, 2017
@znation
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znation commented Dec 13, 2017

@ProjectDent Another thing that would be useful to know is the machine specs. Could you share RAM/CPU/etc. specifics? I suspect this may be a timing issue that happens only when a sequence of events happens in a different order than usual.

@Buza
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Buza commented Dec 14, 2017

I'm experiencing this as well. I'm using a very small and simple test dataset (<10 imgs) for object detection, and explore() originally led me to a 'loading' screen on the first ~5 tries. Oddly, now subsequent runs open no window at all. I can't recall a situation where this was working for me.

OS X 10.13.2
MBP 2017, 16GB/3.1GHz
Intel HD Graphics 630

@srikris
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srikris commented Dec 14, 2017

That's very unusual. Are these images really large?

@Buza
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Buza commented Dec 14, 2017

The largest image is 2.1M, then ~400K and a few at ~100K. I'm only trying to run it with a set of maybe 8 images total.

@srikris
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srikris commented Dec 14, 2017

We have tested on datasets with over 100K images so I'm wondering if it has more to do with the size of each image rather than the number of images. Thanks for the info. We will try and figure out what's going on here.

@JamesDale
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Same issue here, ~1.7MB Images (3024 x 4032). Works if I do a couple (say three or four photos) but any more and I get the same issue. Running on MBP 2017 (3.1Ghz,8GB,Intel Iris Plus 650).
When the images do load if I provide 3/4 of them, generally the image hover popup will get stuck on loading as well.

@znation
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znation commented Dec 15, 2017

@JamesDale, @Buza, @ProjectDent - I'm unable to reproduce this on my machine (2016 MBP) with my own data. To make a representative example that I thought would reproduce the issue, I made an SFrame with 8 rows of (jpeg) images, each in the 2 MB range.

Are any of you able to reproduce the issue with the following code (and the attached SFrame)? First, download and extract repro-88.sf.tar.gz to give a directory named repro-88.sf. Then:

import turicreate as tc
sf = tc.SFrame('repro-88.sf')
sf.explore()

If this repros for you, that means it's a machine-dependent timing issue. If it doesn't repro, then it's a dataset-dependent issue.

@JamesDale
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@znation Same thing, it's appearing to be a machine-dependent timing issue.

@znation
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znation commented Dec 16, 2017

Thanks @JamesDale! I'll try to reproduce it on a similar machine to yours.

@Buza
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Buza commented Dec 19, 2017

@znation Same result here as well.

@radikal9
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Running the code above by znation I am having the same issue (stuck on the loading screen). Specs provided in #136

@dmcgloin
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dmcgloin commented Dec 30, 2017

Can consistently reproduce this "loading" screen.

MacBook Pro (15-inch, 2016)
mac OS 10.13.2
Python 2.7.14 :: Anaconda, Inc.
Seems like it could be related to the presence of large images taken on an iPhone X.

Run 1:
12 small jpegs
Success

Run 2:
13 small jpegs + 1 iPhone X jpeg
Success

Run 3:
12 small jpegs + 10 iPhone X jpegs
FAILURE - "Loading" screen

@mwielondek
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+1 can consistently reproduce. Was able to narrow it down and find something peculiar (which works as a temporary fix):

import turicreate as tc

data = tc.image_analysis.load_images("DownloadedImages")
#data['image'].apply(lambda x: x)
data.explore()

If you uncomment the middle line and simply run an apply fn on the images column, it suddenly works. This will perhaps shine some more light on the issue for the support team.

@luto65
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luto65 commented May 22, 2018

same problem on
MacBook Pro
MacOs 10.13.3
Python 3.6.5 :: Anaconda, Inc.
using the cats/dogs sample data.

workaround of Miloszw worked perfectly !

import turicreate as tc
data =  tc.SFrame('cats-dogs.sframe')
data['image'].apply(lambda x: x)
data.explore()

@srikris
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srikris commented May 22, 2018

Thanks for reprint this gain. We'll explore a fix.

@srikris
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srikris commented May 22, 2018

@luto65 Which version of turicreate are you on? 4.3.2?

@kwade101
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kwade101 commented Jun 1, 2018

First time Turi Create user, but same issue for me. Using an SFrame, the sf.show() method is working. But sf.explore() always results in a Turi Create Visualization app launch that is stuck on "Loading". I've never gotten TC to explore my data. Thinking maybe it was a python related issue, I used conda to create both 3.6 and 2.7 environments to try it out. Still no success.

MacBook Pro (Mid 2010!)
macOS 10.12.6
turicreate 4.3.2

@srikris
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srikris commented Jun 1, 2018

Is this on the same dataset as above? If not, can you tell us if this failure is dataset dependent?

@kwade101
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kwade101 commented Jun 1, 2018

Originally, I was using the tensorflow "flowers" dataset here:
http://download.tensorflow.org/example_images/flower_photos.tgz

But after finding this bug report, I downloaded and tried the repro-88 SFrame. Still no luck. sf.explore() always hangs on "Loading".

@kwade101
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kwade101 commented Jun 1, 2018

One other note, although I don't know if it's relevant or not. The first time I attempted to run Turi Create Visualization via sf.explore(), it failed to launch at all...with an error that appears to be related to an old version of Adobe Unit Types:

osascript: OpenScripting.framework - scripting addition "/Library/ScriptingAdditions/Adobe Unit Types.osax" cannot be used with the current OS because it has no OSAXHandlers entry in its Info.plist

To fix that, a little googling suggested replacing /Library/ScriptingAdditions/Adobe Unit Types.osax with a newer version:
https://robpickering.com/adobe-type-units-error-how-to-fix-it/

I did that and then TC Visualization did launch. But that's when I hit this perpetual "Loading" issue. I don't know if there is any overlap here -- probably not -- but I thought I would mention it.

@unclenorton
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Had this with INRIA datasets first, then tried the repro-88, same thing.

Running on late 2013 rMBP, 16 GB RAM, Nvidia GT750M, macOS 10.14

@baizhenmao95
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I have encountered a similar but different problem.
If I run "data.explore()" on my PC, I could only see a blank window. And the icon of the turi create visualization is a red prohibition symbol within a rectangle.
My PC Information:
Ubuntu 17.10
Inter i3-7100
8GB
turicreate 4.3.2/5.0b1
(no GPU)

But if I run it on the computer in my laboratory, I could see the data and the images.
But there are also a question. When I use the object detection and put the cursor on the thumbnail, I could just see a some image. It's too small to see it clearly. I have no idea how to enlarge them.

This computer's information:
Ubuntu 16.04
Inter i7-7700K
16GB
turicreate 4.3.2/5.0b1
(NVIDIA GEFORCE 1080Ti,but I didn't use GPU because I have no idea on installing CUDA)

This is the first time I ask questions on github. I would feel sorry if there is any inappropriate word.
Thanks very much!

@yousifKashef
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Hi everyone,

I tried the fix posted above and it didn’t work. I’m using the beta. Is there any other way to get the visualization window to work?

@abhishekpratapa abhishekpratapa self-assigned this Jun 26, 2018
@znation
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znation commented Jun 26, 2018

Hi @baizhenmao95, thanks for letting us know. I suspect that is a separate issue from this one, so I opened a new issue to track it: #777

In the explore view, hovering with the mouse cursor over the image thumbnail should show a larger image in a tooltip. Do you see that when you hover? It's possible this is another bug, if you don't get a larger image on hover.

@znation
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znation commented Jun 26, 2018

Hi @yousifKashef thanks for letting us know - I think this is still a known issue in all versions (including 5.0b1). We're looking into it now.

@baizhenmao95
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@znation Thanks for your reply. I'm sorry that I didn't make myself clear.
I saw larger images in a tooltip, but what troubled me was the larger images still too small to see clear. I couldn't read the number of confidence coefficient clearly. I want to enlarge them discretionarily. Or if there are some ways to save the drawing bounding boxes images locally?
Thank you very much!

@znation
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znation commented Jun 27, 2018

@baizhenmao95 I see, thanks for the explanation. It seems this is a separate issue so I opened #781. As a workaround until this is fixed, please also see #340 (comment) to save the images at full size so you can open them outside of Turi Create.

@znation
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znation commented Jul 23, 2018

This issue should now be fixed with #875 and some fixes that have already gone in. Please reactivate with repro steps if this repros on Turi Create 5.0b3 or later.

@znation znation closed this as completed Jul 23, 2018
@kwade101
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Is 5.0b3 available yet?

pip install turicreate==5.0b3
Collecting turicreate==5.0b3
Could not find a version that satisfies the requirement turicreate==5.0b3 (from versions: 4.1, 4.1.1, 4.2, 4.3, 4.3.1, 4.3.2, 5.0b1, 5.0b2)
No matching distribution found for turicreate==5.0b3

@shantanuchhabra
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Hi @kwade101 , not yet, but we plan to release it early next week. We will post on this thread when we release Turi Create 5.0b3. Until we release it, feel free to clone master and build from source!

@shantanuchhabra
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shantanuchhabra commented Jul 31, 2018

Hi @kwade101 , we just released Turi Create 5.0 beta 3, you can find the wheels on the release page. Let us know if you can still repro the issue and we'll reopen it!

@yousifKashef
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yousifKashef commented Jul 31, 2018

Hi @shantanuchhabra,

I just ran the explore method and it didn't work. I got the following error message.

(venv) Yousifs-iMac:training yousif$ python prep.py
Unsupported image format. Supported formats are JPEG and PNG	 file: images/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/AcFaMi/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/AcFaMo/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/AcFaSe/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/HvBoWa/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/HvFaFl/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/HvFtPl/.DS_Store
Unsupported image format. Supported formats are JPEG and PNG	 file: images/misc/.DS_Store
sframe formed!
Materializing SFrame
(venv) Yousifs-iMac:training yousif$ 57:65: execution error: Turi Create Visualization got an error: Application isn’t running. (-600)
Got error: "The data couldn’t be read because it isn’t in the correct format." while trying to read:
{"data_spec": {"values": [{"__idx": "0","path": "images/AcFaMi/AcFaMi1.jpg","image": {"width": 22, "height": 40, "idx": 0, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 320, "width" : 207, "height" : 170, "x" : 180}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 22, "height": 40, "idx": 0, "column": "image_with_ground_truth", "data": 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"format": "png"}},{"__idx": "1","path": "images/AcFaMi/AcFaMi10.jpg","image": {"width": 30, "height": 40, "idx": 1, "column": "image", "data": 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amQ/9i6+//PSLX/d9/+zZM9LknPvkk08U03L1QWiXcZqqpt1uMytkrXWaplknhQMYI87SKvBTqJ/Lmj3WTyC+Q3Me9OY8/g8+ZDpQGhMCggAAAABJRU5ErkJggg", 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", 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", 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", 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", 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", 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@znation
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znation commented Jul 31, 2018

Thanks @yousifKashef. This looks like a different issue; I'll open a new issue for that.

@znation
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znation commented Jul 31, 2018

Opened #930.

@kwade101
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Arrrrg. Unfortunately, no, I am still experiencing the same issue with 5.0b3. Turi Create Visualization launches and says "Loading" with the spinning circle... in perpetuity. No errors.

$ python repro.py
Materializing SFrame

Mac OS Sierra, 10.12.6
MacBook Pro (15-inch, Mid 2010)
2.66 GHz Intel Core i7, 8 GB, NVIDIA GeForce GT 300M 512MB + Intel HD Graphics
python 3.6.5
turicreate 5.0b3
dataset: repro-88

repro.py:

import turicreate as tc
data = tc.SFrame('repro-88.sf')
#data['image'].apply(lambda x: x)
data.explore()

I dunno. Does this have anything to do with the age of my macbook pro and what CPU or GPU it has? I'm at a loss.

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znation commented Jul 31, 2018

Reopening since this issue seems to still repro as well for @kwade101. We'll take another look and see if we can repro on any hardware with that dataset.

@znation znation reopened this Jul 31, 2018
@nevosegal
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nevosegal commented Aug 25, 2018

I'm having the same issue

MacBook Pro (Retina, 13-inch, Mid 2014)
3 GHz Intel Core i7
8 GB 1600 MHz DDR3
Intel Iris 1536 MB
turicreate 5.0b3

import turicreate as tc

training_data = tc.image_analysis.load_images("../images")
training_data = training_data.add_row_number()

training_data.save('./training_data.sframe')

training_data.explore()

CLI reports Materializing SFrame.

There are only 5 images in my training data, one of them is 2.5MB and the rest are < 500kb. Once I removed the 2.5MB image from the directory and deleted the sFrame, I managed to go past the "Loading..." but now when I hover over an image I get the spinner forever.

@juliesoliman
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Any update here?

  • My dataset is made up of about 5,000 images, some ~18 MB.
  • Issue is still reproducible with repro-88.sf
  • Issue is fixed with repro-88.sf combined with @miloszw's workaround, but not with my real dataset and the workaround.
  • sf.show() works fine, but not sf.explore()
  • Python version: 2.7 and 3.6.5, Turicreate version: 5.4
  • Running on a Mac mini (2018), 3GHz Intel Core i5, 16 GB 2667 MHz DDR4, Intel UHD Graphics 630 1536 MB

@znation
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znation commented Apr 23, 2019

Hi @juliesoliman, I haven't been able to reproduce this issue yet but we'll keep looking into it, and if we can get a consistent repro then hopefully we'll be able to track it down. Thanks for the info!

@OCJvanDijk
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OCJvanDijk commented Nov 24, 2019

I run my scripts simply from the terminal using python test.py

Trying to run this script I get stuck in the loading screen:

import turicreate as tc

data = tc.SFrame('test.sframe')

data.explore()

But running this script it loads fine as long as I don't press Enter:

import turicreate as tc

data = tc.SFrame('test.sframe')

data.explore()

input("Press Enter to exit...")

I'm not sure if SFrame.explore() is supposed to block or the script is meant to be run in some other way, but manually keeping the process from quitting is working for me.

@znation
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znation commented Dec 2, 2019

Hi @OCJvanDijk, this is because .explore is a background thread that is meant to be used interactively (while the Python process is still running!). In the first example, your Python process exits before you can start interacting with the visualization. You can run python in interactive mode instead with python -i (which will keep it running after running the script, until you exit explicitly), or using something like ipython or jupyter notebook.

@fellowProgrammer
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@OCJvanDijk's script worked perfectly for me. I was getting the loading screen and it just would not get past it. My images are very small (not over 200KB) so I was very confused why it was never loading.

I wanted to see my bounding boxes so I replaced data.explore() with

data['image_with_ground_truth'] = \ tc.object_detector.util.draw_bounding_boxes(data['image'], data['annotations']) data.explore()

@fuomag9
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fuomag9 commented Apr 22, 2020

@OCJvanDijk's solution worked for me as well!

@unieagle
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@OCJvanDijk 's solution worked for me. So the key point is keeping the python running in background to provide data for the Visualization client. This information should put in document somewhere.

@Nahatakyan
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I'm having the same issue

MacBook Pro (15-inch, Mid 2017)
Intel Core i7 7700HQ
16 GB 2133 MHz LPDDR3
Radeon Pro 555 2 GB, Intel HD Graphics 630 1536 MB
Python 3.8.3

I have just installed the application and can't open it.

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