Comments (46)
OCJvanDijk
commented on June 23, 2024
10
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.
from turicreate.
mwielondek
commented on June 23, 2024
3
+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.
from turicreate.
dmcgloin
commented on June 23, 2024
2
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
from turicreate.
znation
commented on June 23, 2024
1
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.
from turicreate.
nevosegal
commented on June 23, 2024
1
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.
from turicreate.
znation
commented on June 23, 2024
@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?
from turicreate.
znation
commented on June 23, 2024
@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.
from turicreate.
Buza
commented on June 23, 2024
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
from turicreate.
srikris
commented on June 23, 2024
That's very unusual. Are these images really large?
from turicreate.
Buza
commented on June 23, 2024
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.
from turicreate.
srikris
commented on June 23, 2024
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.
from turicreate.
JamesDale
commented on June 23, 2024
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.
from turicreate.
znation
commented on June 23, 2024
@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.
from turicreate.
JamesDale
commented on June 23, 2024
@znation Same thing, it's appearing to be a machine-dependent timing issue.
from turicreate.
znation
commented on June 23, 2024
Thanks @JamesDale! I'll try to reproduce it on a similar machine to yours.
from turicreate.
Buza
commented on June 23, 2024
@znation Same result here as well.
from turicreate.
radikal9
commented on June 23, 2024
Running the code above by znation I am having the same issue (stuck on the loading screen). Specs provided in #136
from turicreate.
luto65
commented on June 23, 2024
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()
from turicreate.
srikris
commented on June 23, 2024
Thanks for reprint this gain. We'll explore a fix.
from turicreate.
srikris
commented on June 23, 2024
@luto65 Which version of turicreate are you on? 4.3.2?
from turicreate.
kwade101
commented on June 23, 2024
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
from turicreate.
srikris
commented on June 23, 2024
Is this on the same dataset as above? If not, can you tell us if this failure is dataset dependent?
from turicreate.
kwade101
commented on June 23, 2024
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".
from turicreate.
kwade101
commented on June 23, 2024
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.
from turicreate.
unclenorton
commented on June 23, 2024
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
from turicreate.
baizhenmao95
commented on June 23, 2024
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!
from turicreate.
yousifKashef
commented on June 23, 2024
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?
from turicreate.
znation
commented on June 23, 2024
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.
from turicreate.
baizhenmao95
commented on June 23, 2024
@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!
from turicreate.
znation
commented on June 23, 2024
@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.
from turicreate.
znation
commented on June 23, 2024
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.
from turicreate.
kwade101
commented on June 23, 2024
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
from turicreate.
shantanuchhabra
commented on June 23, 2024
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!
from turicreate.
shantanuchhabra
commented on June 23, 2024
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!
from turicreate.
yousifKashef
commented on June 23, 2024
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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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 914, "width" : 381, "height" : 295, "x" : 498}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 1, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "2","path": "images/AcFaMi/AcFaMi11.jpg","image": {"width": 30, "height": 40, "idx": 2, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 1361, "width" : 926, "height" : 666, "x" : 1517}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 2, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "3","path": "images/AcFaMi/AcFaMi12.jpg","image": {"width": 30, "height": 40, "idx": 3, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 738, "width" : 1018, "height" : 974, "x" : 615}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 3, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "4","path": "images/AcFaMi/AcFaMi13.jpg","image": {"width": 60, "height": 40, "idx": 4, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 230, "width" : 546, "height" : 443, "x" : 274}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 60, "height": 40, "idx": 4, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "5","path": "images/AcFaMi/AcFaMi14.jpg","image": {"width": 30, "height": 40, "idx": 5, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 750, "width" : 829, "height" : 774, "x" : 611}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 5, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "6","path": "images/AcFaMi/AcFaMi15.jpg","image": {"width": 30, "height": 40, "idx": 6, "column": "image", "data": "iVBORw0KGgoAAAANSUhEUgAAAB4AAAAoCAIAAABmcd1FAAAKHklEQVRIiVWTu4+l2VXF997n9T3vvXWrqqunZ8aNsccD2AYhrCGwECECByMnyMRk/gssOXBITE7gAAmEJXAKmUWChAMEFswg2tM9U9VdVd237uN7ndc+m6BNwAqWVvTTCtbCVy9fOFcBIRFprRGRsAgoABCR6EPOGUqQlBMkZs45p5SYGQUAQBM0TbXf3Su3EhGCfHPIr66/+OV//4eGkmMMVdMQobwVIkAholJKSpFFOHPJKXOMMYQQRKSUAkVEpKn0zfWdbdfJ+4LJVdu//vFfPn36pZef3+jEUBmFiEQkAv8Hx5RSZs6Fc8w555hi9tO0zDmHlEopDEWMMSA0zpMrJufctu2PfvQXt7cvN5vN5zd3+Orl585o5SwiImIp8jYws5+XZVkAIAQfl+NhXJbpwFxiDMwMgKtaHU7HujsXLojwVz/+u+fPn3/lq18ex/Gb3/hdDYVBOwAAAJG3LpyRGZi5lBJjiDEex+W0P0zzcVkW5syJNcBkERGn+R5JnN3+4hf/eXl5/tFHf/DZZ5987cNf19Y4BA0AAAgAiCgFAQpzeqsQwjBN4zju97v9w2ufcwohx7Tq6hijtjUiNk3zgx/+4PHjRx9//N2f/eyffv+jby9z0mgVESEKggKAnItSCgCYObPEnEKKyzLvdrvbu5fDMKSUUogoeRoeUFWkZwCg4+o7f/wnX/+db/70H37ywYcfKIUhjlqrWhmNKCJCgERQQIC5FCilcBZm9j4cj8fr62ulVM45LL6qDRYJPCilCuibm+umaf7+J397fnlxsb2IyWtw2jirtRZhRBQuqBBLyZQBoJTCzCHEYRgO+5MUTCVNS0DO43EBbQEAlXnx/NrY6tX9F+++/97V1VUuWZJYBo2ImhSAEmHQBECZJUp6ew1AnuZ5HIfD/jbl8MjhRQXD5M/PVkbjtMxxmX/ta+uqaobJcPTG3y0T/fuzF+++9z7K21n8aiGSc354ePjHn/7N55/+/PWbh223IsUFQGJGKiI4TVPfrY7jUBmLiHOIq6oS5MLY1DZErpw2Ch8O4/9D//D7fypxwYKB8zxNReRsszmdTlqTiGgkANjv9/WqS5FbY7Q11pnog7U2x1RKMU7HmI0x2S+YWRSVP//uHyJHjtw0DSIO82StbdsWUmLmJUdtnJRCUpaYjDHzad6sml+VQiFUnLMyKoSgta6qqmRW3/v4j77/Z9/hFBCJlPHRL8EDQOfcbr/3KRUAzoQEKSUgWuagtVmGedp7pZEIU8o5chEIIRmrU8whhsSg7v7nX63SdVNNy2iMERERnqcApBBJkcqJiVBiRClWqdqaFDKRqvuKEJUmLhlAFyiAWLIYq7hgjFFjEV3Rw37fNk2MXmutkVbrJk6+rh2CaEW55LarNClGwYI1QQ6lqqosMcxsa8vMkNEozSXlTAoxY9YKLaAyygoAKZcTayiEqq6dQqpaG2O0YI22hfnRZvvwsDeuto1OLJWyZxtbfIyZUWNeQmDMhbU2MYL68pNtZYEUSSkE5IzSSjlj2rbRliDxuusRoKtr41whQE1N3Ritcgp922pU1hn2eb1Zb8+3U5igKAExxmpnBFE5DYRKka6cZSkxpNpYIgzgV20HLSCic24YjpKK6KKUXq/XXduuu3Z32K/a5ngcjz529Wrv91wCEanf+/ApiSjEuq4cKRJwxq77PsawWnd93SLidt2t1g0AaiV9VwNj7SwKklbLPNW1ffN6//Xf/q1pmpd5IqRSgMiqb331cV3buqraShvjVm3XNW3lsK37i/W2FG+UU5aUsgilazopsu43ueS+a4fTqXZNEaxdtXvzoI0CwGma265b/KSJdF3XlqQxrdFgK2uMEaawRIala1sEdXa+iSEgGhFpuvphPzTOhujffXy1Pw2VqY/pNMxTiEkp5eqaiIi0bgw21vS10VoTmbq2IlDVbXIpZy4ETWuC9znnpmmGYQCApjVaO7PMsw9nq372oaqqENL59iIK39+9AU2aFG23FxbN6TC2rsMS01K6umGWunHO2LPt2jmHiF3XWaXW6/V6va6M0wjn5+d935OxMeTzzdm66y+vHo3jGEJILLaqCYv0fdu2ddM6a/qua5Y5GEJZ4nbTl5B2b/ZakICJiJMnLkop55z3Pubw7PkLVPTwZr8sy6ef/FeJse1qDj6loM/PttbpdV/FIJfn69Po33m8lYLzPLdt23X9ZnuWpYQQKJemW6fZt1UdckopvXP1ZFkWFjpOgy6wOTuLIfgQ/RKHYSAuiwEgjc6Z3eFhe97GGAFLZZ2f/TxPBaFpmlKKaSqllOv74/E4DAMR3d7ezpOvtc057aZpGMbFh8QyR79abXTihNqkMCfI733p/eP+oWsaLKpubb9ZH4+npmmm08miYs5t26XZby8vrr94OS8pSXHOPfvixRKyT7OIhBRRkXH1OIxkrWPm03FSRnPwq64joot3rpRG9rEUbpxLKT1+dG6MdVU1+Hmapu35pm66eZ5HH/v1NqS83W6H+cglphAtoQirb//muyGl7dk6R7i8PEssfdszxxgjEhit5hiBxcfIKQMikl6iV+QYsRSZ5/n61Z0x5ng8CUPtGsF8GpZp8rTdPk6MiND0dhpG8T5zTJFdsz4OA4K2DFqrtm1N3XCBWtsY8+G0H06H6OPhsDfGHI/76IOInE6nGEQRKWvo7s3OKm1NHRbfrlftqq+qKuVwc/3ZqmtAiWobXRufvFZYOAUOT55cFQZjjEIEUIh4dXUFpHLOiXOIcY6BCuvtemUdxrRsz1chhK6q/bwwp7N+JWjyknOem0qLbbq23b/ZhRyvv7gDIExyGkdRFOd5t9sprZFICabMJaUiQj6M4zhNPkavDofDMk4ppdo1xhhja+2ICr95fUgxHo/Hdd9fXj4CSZt1f7vb7Xa7pnY+MJI9TbP3kVkKc8lstFbfeHpRNbVwAkyrsw0oUECjX3KM3Wo1T4NrGmNUU5vTfl+sOT6c6qY/nU73969n5oeHfQSY5oUINeoixVpC0gSivvUbTwugMCukqnYitNsfnzx5PM4zQFn1fUlZGF/ev15tznJM//bps0pJymW9PvM+jPMyzcsvb14haihsjNIKmZmUUh8+3eaQYmaRQoAl8zyN8xIU6Wmaz1Yr3TQs6JxafNbaPL58VDgdjtPzl7cvbm6z8OITKWO0RgJA4Fy0orp2NC9BW5e5nOYgXFLOSK5tmsD+/Pzs2YvndzfX83TIWUD4/v7+k8+ee4bnt69nvxQk72PIafdwEsFpid5HUSKCt3dH9cHVoyWMGaBvm7Skvm+YU2BfGOdpZi6odQx5GMfrl9dFynwa//lfft533TDNnEJIKWa+3x3bRoeUFh8rayPD48sz9ZX3zpmjJuO0IqKH0xE1+mmBgtZVdVMtY7h5dX+zO7x7dXF9s59SJIVc8rIEv0RfSgxZlCIEEWzqRms1zsEo/b8VEgFgxjN+igAAAABJRU5ErkJggg", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 729, "width" : 767, "height" : 520, "x" : 963}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 6, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "7","path": "images/AcFaMi/AcFaMi16.jpg","image": {"width": 50, "height": 40, "idx": 7, "column": "image", "data": "iVBORw0KGgoAAAANSUhEUgAAADIAAAAoCAIAAAAzED4bAAAO5UlEQVRYhUVYyY4lWVK16V6f3nsRkRmZFZVZc3V1U91AIzZIIMQGCSQW7JFY8B98BR/DErFnxQI13V1DZnXlGNMb3f0OZsbCsxJfuPzKXe5Xfo4dO8fw3//tX2OMJc21VsDITe/uXiYWb9on4+k6NhI4HveHs/PLw3GMoTRhNespqPV9f3u7ffvyh48//2K3O8a2EoZ1vzafcvJaZiICgJxz0zTEYBgZJqMGLFMBQENE94ocVRWsmhk6qCoBwDRNtRoii4hXJQcALIXH42tEbJtNKUkiH/e7wCVIm+vp8aOnzAwAMcarq6vD4aA2a6XN5hw8l2S11n61NsBSStM0IYScc60VPAZCNEVSd1Ut7l5rdXczMzNVVVVxd6FQtMTYpGIsDkjMBIZetY3heLhvu7WWgwRKeTwcDiJi6VnVmfmCGTZXT+6vX6/6dvPg0f7+9TzPeRrXm/N5PLUxxtUwTZMZNG1PRGBupWI1Q1c1ESYiK9XMwNxU0R3dSVWJCGM7q4cQEAK4ICJzaJt+miZEn+djjDL0F6TN2dkZEYlI3/dmtt3dvXz+zaMPP9qP6fk3v3G1swePzh48ZGYiqrVO02ReAeuyNDM3NqPlJbVqrRURAQAARAQREZHAvFpxzY10ZlZrRgjEsdZqBO4aYg+GU8rPf/ymXcl2d992jQT74udfH+ZjE4fYdN/97jcCvtmsS+HD7ljU5lTdMaVC6EyNVnTH5fOuyQHcCcCZGZiJiJk4REdyRGQmpErAQYgjg01N0zgkDH1s+5TS+cMrnw9t3zBS261DaJrYbu93KcP33/yenIB8O6U2xP3uJlWudthsNvNpjF0kgq7rzTHlkwhpya42jUdEJoZiubobghOagTtZLWDKQoSJQuwc2BRLHRfeiYhZLunklu+uXx+TT4eJmYdh2O9GRGzb9pRhHEdE7LruV1//WSnp8tFj8RRCWDh+uLtR1aUMEQIRISIRNU2DiDlnpoiI7o6KZvYOX3cAMIhkFRGU2MWJKDJzKSUgcWwAA4UYhFDsuL3L40gES0GthmaeRxGZxuN33/7Po6sPnn7ycWjbNjb76xf72zerYYMAWhOTidDySazFzBRKbFtmDkTk7tVRq2tF94VhiCjLLVMEV3dVQGlad0fz1WqV80yOjjSszhBCM4TQxM16ePPieTkeJ27dvWvjXGq5Oc7ZWtT1xXk79aGJeTyZAQAqGZOwSbYqEkpJIYSSEhG4g3llxMAMAEXVDBiRFhouJWAGmtN0PKT50AjnaQyhCYghrKRdu0Appeu6m5ubL37xi4dPPmnbdpqmtm1FpJY5T4dmtQohuPv+7r7v+9VqBQCay3waVXVBUETMjIjcmKlZ9O/9QdUQkdydmU2rSAxNL4xdN4BRVgCWnKbJcJz21zd/UNWS9frtyxhlt7vv+9ahnJ0/PN7voCh5+fSznx0Ok2WNMTJCzbq73zKBIKBpzXNNuZRCDmjuiESkqq61qKq7ASCiEZiZuLu7L1AuuDIzNZ0EAGzQpBiaGcdHboyeQgiqera53N3dgkvTNIKrau5m19fXFxfr7fX1PM992zQkHppSZ2Bi5qp5TnNoBiIBsNDyNG6JSbOLyFIfIQQFQESSECQEYgntpu83AGRVkSknG4/TlN2tonovMh/uUBOHSBLu7u72+yMA9n3/5sWrNtA8++X5g3SYNt3w9MMnlxeXucwhcowR3BGxbVZts2JAA1LwUgpDsAIc5N2/IAIAZgZGKtVLdQJ0CPN8lBCAXIRSyU0bmBE1hSZmrVdPnzhGcw5h5SCGYI7T4QAcqpzXUgaJ0aWMgJmm7Rgg5N3RU/JavOQ8JxEBAC2JHKwmA+fAAISMyO/EFhFBjf/lH/+OiKzWdrgwTURIRKWUEGIQZuGmW4/HfTXPh3tuBwEE12kcx1nr7pokNnF9++Z1lP7Nyzs01zSncby7fts1Tc1pzhMjorkiVa1t26pqrVUthxAB3Mx52ZODmSFArZVKKYjIsRkPNxgikbijUBOEJDRpPKVpS6EFc+nOUD0rkgREfLxulOThw5+9ePN6vX50tn64v77f7uFwP5OHp08/1lqmwxScUStIQEQC3O+3pSQi0OJpmksqrlXVzNzRF/tARNT3KwByxxDQrRIREamNSDKdZkOKq8eutW0CMlFAFoOa0PAw1sDy7NV3Hz3+ggBf3R6G5vLy4y9V6Mmf/nL48tOC0K5Xh8NBHaspkiND0wzA5IRtN7g7SSAJAKSl1jm7KgC4A+WcF8GY52w5TdO0+J5cRvOMiPNxx2SIOM8zKB4Oh/1+X8t02l4PZw/ONxePL9edtHqaf/1Xf326vuUz+fbm+nb/v+HhsHvxMiLP8/ye1O5l8QhLtwGApQEsfW9ZAoC4a86ZiEIIasnU3VWVVs2aAuQ6gbvKUOtxNTRNHKoXchai2ezmzdvN+eX3L9+MP76usfvv//yP5FOz9udv/+uTK2O4YEbzjNzVnBSUg5iZtJ2ZOSiHiIhE4I5E5Iu7YWQRckd3RAnSxDaeM8FqGIZhvT/ejuXgHHOqNW1N5xhke3+bxrxabUopGyxfff3LX/35X7zc5V/8xV+WSjIMfd2X27uvf/55+SFP3/6BohixmVXNiwVFRK0TAUtsJfbArqpWi6oCMUkgZFPnf/6HvxURq1pLATC3XHJK8x4pIKPXWsrU90OaVC2bgqoR+831TQG+uX77/Le/S/vbTRv9uDvevJ532zKnu2++54qf//pPXr96JkPvITZdj0IkorUiAWJABHcQAXRAAGZeUF7g5n/6+79xNyImopxnAEdqWAJicFMAcodcat9HKyrSiYh5uXhw6bTO4/j46sPTnA7bfQX9+OkVl7K7u4Nax3Qcx723gdoQVisFJ0I3i1EcGNHBFLyAAwAQEzEyMbCxEIDJYoOAyQGQ3CyU+dh0LUmPxJpLCMHMcipWHFzn051wV8u8u7sNw2a/3z84X5/e3qU8l3kaQWndodHZ+kI2nbYCwWutXd9XzcurQmxTSug/yRUAgBMxOi4ODAAoxpZI0JwB26bHICwtO46Hm3G/O50OJc9D22025ygcBEoqj588LenUr1cM9cH5UHNqVu3Vp1evj9ujTbxiPutqF2Ad1w82zXpNBEi+NFNHNrMYIzNzaJCDCDOzmTk6mKOb/ORnzN1LSW3bMsXqp6LUtO1qtbm/udZST/udepBA0/HUduvrVz+O49gFefrkyX57uN1vN8PmdDokm5shSOzbjitgsWnOUwgERKUUiTG2bQVjRnABMld1d0Uzr0QEjgBEJAgseTqaWexWiD7Ps9uxGS73dy/cTWtt+nUad7VWR67V+r7fPPjg++9//+mnn16/evn8+fMp22o4c5jHeXx89VixsIF5QvM2thKCcAtYF3TMjARUlZDfuRp3AF+UzO3dBSJSaDuK7O6laK1A7Pvty9isVxcfVMWmb4bNRQZqmiZIV41++O63m34Yj6cppXmcPnn6Qa671aqjQFOeYtOY1GbVS9uE2MbQOyECI7BIRKpQQVUBKzIjOi1JhwICIxGLIBEyCgCYudVTE0NRA49hCWtaUfX65Q+Ewd1Pc9pIud/unJrT4QgYumH14dOPSpo/++yz037fDisAUPWhX5eagkDTnrk7aSYSNHUtyAHABcWrOxWAd+bd3UUEmACAHACYVDFIg+QpT6Z0GveILm1XSlFVxpWIpJTE8yTr80cfrs82xe3Jpx+K0H6/vbm5OZ1OiNithm41LNpTSgGAWpNZWej7zrEAvCs0InAJIbxntrsjCIIsz1CtszRtCANi0w7xbPMAkdkrkxrmzaYPxKDGMdy//t4tlzxfXFy8efUaHRiJBdqIBWq77gpUbkWtxBjbbggcwRdOKwC4ITkBAElEDhQbxxYokDQoArxEIXEndCMAOJ1Otda2bctYc64OMxGllEIIFOWQUn9+bs4Pnn5RjPe7sdoEABWQm5bYnJrQx9vb65SmlCaIooyq+t5wLr/nXTzksCwXWUdEkUjYIjTv0xgRUdeeo3kxzzlzkFKnYX2ZanH3aS63t/eBELQ2TTi9fREQHZI4rta9k6FABdwfbnXObZS+6ZkJFBgQmaoVJAIAJ3ZiYAltRyRmUKu5u7kjRQdyICRRN0dAZkei3f4GEQOxSASAbnV52t0ebm/bbiUiMcr5o6uLR5+Mp93m4tFXf/Szrut+fPPq+vatW3ErkZp22Dx4dOWG7opIpaRlRmXECKDqS4dmEWKutS5pYlGHhWoiZFbRAR28uhsKQkAIiHY6nZqmKfMdxYthYDNbr9f7/d7z6fr+2YdXH+22p+++fdY2K4TQrSJzSLlUhiHGcRxjjCJiXpl7ArSa1LHWGmN8T+olQbxTKUeid0WweKxl0EVLl1Q/EUOtte/7Ytp1F5Fc4d0QTKT94fW2Xz2sLtu7t13XPX78uB3C2dmZam4aWXVdSsnMpOkVWLhFCABQDQmAQjRHQCTmdyXGAYVRmAMt+2OOC6UcBIDezUGG9VmexpRKznm1Wh2Pe0OKUTRNJU8XFxeMuUzl5Hfd2cMf/vCMCC4vH5/G/cXFxd3dnXm9fPDo/v5+wUUQtSZybIIYIAGgLcA4UkAAZ0JEQASvBo6IpgC42NMKAAYIppJSChKJRFVTSjnnph/G4z5I1/WdGgOF4zTjmB4++kjrjKDTuMsF3PYiUivknEVkObs7eHAYaw1AjIhMVIwlCKgtOXnBlMDfKxkimNkSJxHRAQgUcs4ppXEcmzh03cCwKLxut9vd4aRJg8BmfZ7Gfd+t1EyNEdI0zSFEQkwpqep6vbaShdihsGyAiN3JzKGyAAAUUwpiXpCMBRBEnRwFAIAQCAHRAdTMEEiRQjMsI8NpPqg6kVxcXFw8fLQ62wiWx198Weq0O25/+cdfpjy5OzN88vFXRes059D0jrIZVtN0kiYqwbA6L1rd3dE4EMJiUjSG3rwsrczdATWEAAAQ0B3Rf+K+qxkQQp3H/bItYDKrzAgkKSV3j83w4pvffPHVr4ZhePbsGVkOIXz++eeGeb35oOnWaZ7V8n6/XRRSVed5fqeT3IAz4iKt8n7AsWxr8Vg/gfj/JamqpUz/BxcJYRK5eg0aAAAAAElFTkSuQmCC", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 172, "width" : 303, "height" : 318, "x" : 287}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 50, "height": 40, "idx": 7, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "8","path": "images/AcFaMi/AcFaMi17.jpg","image": {"width": 71, "height": 40, "idx": 8, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 170, "width" : 365, "height" : 328, "x" : 346}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 71, "height": 40, "idx": 8, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "9","path": "images/AcFaMi/AcFaMi18.jpg","image": {"width": 30, "height": 40, "idx": 9, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 650, "width" : 580, "height" : 425, "x" : 1049}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 9, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "10","path": "images/AcFaMi/AcFaMi19.jpg","image": {"width": 30, "height": 40, "idx": 10, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 663, "width" : 506, "height" : 394, "x" : 1022}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 30, "height": 40, "idx": 10, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "11","path": "images/AcFaMi/AcFaMi2.jpg","image": {"width": 80, "height": 40, "idx": 11, "column": "image", "data": "iVBORw0KGgoAAAANSUhEUgAAAFAAAAAoCAIAAADmAupWAAAYdElEQVRogQXBOa+uWXYQ4DXtvd/hm865Y91ut2kMWEBGQEbMH8AkDpBAQpAQopb4L2QgTEAEyBKRAYtJQlhYMlgeqK7qunXvGb7pnfaw1uJ58OX3/iVoQWrEEVNfjSXPHhICA0DNq1B1PfPu11yB0mjzKwh74wYu3syuqlFCD2LUNOwebs//r0sfiUBg/fxlOeyQKZKXsmE34Pb6FRED2Yz7jpvuj6YYZGw64bZyHKm9YnpTMkmsXgm7SA5lySFgg7UthY3adm7p57HfrN5o+Kj5IghgKOPbli9a1rLleHy0uui0dg/v9f4MEH1bw/uPhG2BdfJqAALVaV2t5TJfTBe13J3eOe8IT9aClbnVRanDeJAxEUMtdyss7p5nrR2grLfn0H1T1qu9ftc8jmGGOhOrGgDltTb+8KnEcLckkQoKTbeIDu3OZe12e5YO6NBa45TNDIbkjrXOUF7rtrijIKRPv87pIcYC9xcJI1EWEX19gmHQeqnLTddVUMiw3a5O2u7PDRAktX64v3wm2L2h00fQpmi1TDCOsN91p59626wudXkFXzAe+PiO4oP0eyb17cXM0Ihk7N//Wji9BdolUQxdCEefnuPhBP3OuWG/p/2Hdl3VaT1/Rc/5/MrWEQEL2nxxDLY4iCjKcr67rxUMhtFLk+GxLTfpRzTf/fQ3mZlyM95vP/zS2Dyfm8TsqDm39dqG/fzDt6rVQ5BxD57LdiUSoH1KPRG16bOMPXDA83/8F6qZh4+6fkbew/ZsBsoY4wnT6G1mbByPJd/RGx8+tfuztxWqytDlZZb+6Ntr6B5MBXTWtlqpRAf0pZUFlGnfo/naEpRzYJLxZOVVl2Z5jo+ffFug1VoUd0M8HNqW3Z3KzIePbguGnedr3L2tl3MrtVI7vPl5vXxd842RJKS8bhSQYtLbpCEQoV5r9ya1akxR8wVSb0tVatgA8sy7Bzz/p39l+Q4UAJWHPSxTk96Xq9aZ9u+jAMmj6jUMb9ULrtnJrW01l7TfI3fQimr15Yz9x1xfexlKnmAtpS59egtJIXC5XC3GMBygIuQzh8Fqs20zzwDk3dHzVcq2kPfDKaWUW3VK3tbI4kzgHjmsy707fdxevoKgEwJHNNTlHndjnm7r+SuGxBA8ChFAjKlmhdCIJEVvKghLrmVjfPm9f+4aY9ergK93KwXjAHUFdxA2a6wNDwMsiI8/wbZS3czIXbFlVQ37d0ieoaPpiwTAOG7Xz6yoceQ4+HpGWJZSaQEKAgDh4Z2+3Hzcg919vVE6pMjgXKa7U+O48/kVdycl1uoighAKNsmzGjQtrGzoIcVaqwsRESz3onx4fJhfv0DqYwjzsnTjrl3v1rZCkXQLu1N6+JneP5ey8i/+/t9lEm3Na5H9e0qdlStAjyIYkwwnV7SGCKsRQFNQN8vuWY2Qqbx+CxxheYbUt9IgdkQEHNC9LVfCALgj0K4PEKTNd2ECUgzBKVor2KYlN61AaSjL3UJwZEdAIinuDJlDe/5OYjLEwFGtQCkB0dCBGQAgRKz3zcDmiftdKZVZ8u1HGI+ijmjH/Zvb64vXO7jhPBHYqmVCcnSz6YtOL/3Dz3C/I1Z09fuLg4TuiA3gdiVhj867Bzm8J1Z2pf0HCB149e3i5WbrXPJiSt6yxFNuMwSnfmdwACWPfRx2SALr67rcYkqw+0QcJUGZntPpA2GQkBqziCy6qiJPlzQeTISIkLGtmXbjsm3tPlEuqtqqg6XIRMMOlpu7tjzF3VtuKx0OZrTOZ9mNyKZF5eEtoYJpK/MZUw/D6CTrlz+B2xc3gZKdnEKt6xPv3rkISu9qWq+er07BZYh9JNOW9hR2dDgCC0MGXVhE63k4fKjhASRVbRb2nfSvXz5DKa3yvt/V+0L1Hg5voetIV7AMdW2mAcncuT8CVuoD1nv+8iNQqJjC6QClxTDK4WhJwnDAdXaxlhdkAxZfm621btlxgPtz6zoV6glMC0TappXcnViIxOaFPVCrcXyDIGybh0jxAcCNe7PiZl5utszKJ/OAVqHdS6ut3CP3IGxbjvsDygOGVAyEIL/+UrYXAo7JkXL37tg/fNN9+JlCtumCKW3bVucXUYA337RpbnG/leq1lJxhveh9s9eXXCQ8Ptpy99uPu4dfC4Gr1LwtJSNsM3TBjIK6t1TdhmOKfURhs63FYRRgCEtZwdnqFoj5F//otwmjUQMS5EEx2vpKjOauFKksEEbS1csqQlqjokC9CJHxo3thN5LBdErDziutf/zfIfWgLXSjEcjhfZtWwVrdIb1Rg4aHvN3C+MCo1goFjCzep258pNiJZYnAIdUCgk3RQwgYg5YEHQJbOV/KcouH0dYldghGHkfQMlsX4Fa3xnGoeWNXgRXDMC9X3eD4zW/0XG/el9uNvG4QXDhp27ze2CfYvwOO1mo3PuLhwOAgezl8aLQHLzEgy4H6N1y/dsd3hJ01xe6Upwt1nfzG35QQ0MCXM9qq88a7h2ZIwJBfdHqFdkl51dvT51sBQqSOUiea8rToekUZHcQ9BDbreilZlQklti9oINRhCiGNWrT/+JfrvKqb3V7ZW69n1RDHY5kv0gWKfeN97DuZXvvDmJ/+ZL5tva6IGa//5d84ZMizq3n/BsrVXZHJaI86YTMKOy+zJ8FWrBJLNKow7GJ3rLcnkEDqphUk+XpDcgt7bGuFMIyH7eWLRGruafcAEuvXX+L4SN41q1DX+vLVhygIxBH7fv3yIyNSIN4fcLXqWyMSxWbNy0xEDZhrdkM5HHNZQwjmTkR5WYMkhmLE4dPP2/d/trU18G5++dXhtK9hV7c5ctfqsjXA6//498YZpgV4sPKK0AE5OHE/gLd2/wrywOLaXHrG0Fk1vd8ogkvi3RudnqTbO0aKna6vSA6btuXZJBINvN/B5anljUJsuucxxjzPa+4eProtVkHnSecn3j34dkeTHInREB2RmaWVAoFt27g/6vl7CNhoMIRyOXfHh+OHT9PzF1UQhtaaXNb65h2t1wpmp5/J8sttNQl7LVMqVw69ha7VFc//7d+moddWynrDWjFELxOBGQo6GXeExfLdFTj1EofGEb1xOuXXb2M/VEVED9I7KMDQ8o/YHXSeSRDbtl7P3cOnts0xdtN338bhnYrEwPX+w7Tg8cP7OZeEHsfe18WIwKzFAW1lAwhsJYOEdp+m+bIbT83teHq8nJ+iewYDICJhIxnjttzNCFFFBOJQ72fLdxnfMXO9PVn3QLr1/aje+J/9k79naqpGhF436SJwj7KHemvuhiRaOHUAybmvzam8wHIJpyNR5w5sm7WiztnN20wSoU7C7CVTjHF8w4qtrbrOWoDaKl6NI8YTkFDa73enOjxYXjB2GAYrE3pB9uZARIRgahRCL2wKthVOoCwFGTgEBfOC7MCplXWkZHWB+JBvn/d/6a9Trfn6Kq4tjDCd49jdn142S+S1ERtBltRTN5iS5YW6zsKezMSzEpicWpkFVbBRGvndzzWrEWmphcd4+oRpiK0SCVL0xltzCOzUr/fnphuax8NH6eOyUW3uZfYofdfhOrdtmr/78wgdIwFAVULpUfah79E07k6mFbasHNLxEA/H1QgU2u3c8uZ9jw4YuvL64rVd5vO0lTo/9d1h+aM/bFvu98dNhtD1C3heAvQHv3/mf/oP/g5IBxxdMyJJ7B0AYaq5pv3etSGhEZEkny/Ggch1XRjQvFlRgqLbivnaykZoKB1Jwnora+mGjgx8WywOOl3cLGED01oDE/Djez69KbeLDSecrp7PykzeSJLbhq16CzkXFJTAYIrI+0/v4L6GGLVpnV8YwKBFsIwcSYMX2T36/Y6itDs4trIw2lqWCbuOxRpCB0wsASNJ6MDZ3bWtGFJt3B/eet1ofGsYkZSgUAqBo2OE4ajVkLtwelu3BWOvoZOUlMTzWeuKgv3+odTgcY/jY7v+edsW8DC9/EhEtL0AeZ5v8/P3Rjyst/T2SDyK1jQeq4M201Jbm1JKwj1IwE3V7fyn32pVqBa6NB4+sANCnEoLaLbUJUNt5kFqgeXHX9lctL4C4WaAUybajSE1Apz/73+25d7qQiEFGU1rnr6G/uBBsBYzAACCVvPGMiCYA0GdKPatNeeIWtibUQAgU3B7IUWOR6/rcj8LZaZHJcfXS02P+bv/IwYydHR8i0Pc/bW/NX3/Z+HlZfONMDa7U5dqrd3Yl+xYt2iWyTkGq63NK3U91TvtTq1UZq6mukwYRK93ikwkHiQC1VrrcoP+4HmrGphrkORQzFBbJr18AW7UPbhCmS+W73z62La7N9c2Q3ly12I9gXFHWldH4f1PnKPE5E0xdNWFjaDeBVz4bcWDu5swcEfxiEncoPUJXr8bup5icBR//pLeftPWJ7r+UHGp083LHGMMDgMRtBDuV9RmXYrkbb5jSpxiqA1tbaVK6lpZVDUrWKkYgnkrpjjltXkDx2FX77eaM8Gm9+wdW+xrrXw68i/+0W9bMyZmQgpdMw3MHHrNd5CEvLOyEaNT4OE9YuHhYMsLEHl1qzesOT28rbUBBXB31djvSBC0chTiPShRuUo3ajpO12e4zvPluT7f8p/97/Kn/xNWr6BOO5yfq1nc77Z5JlgzsgGNY6y881pKnjDEUjPIHkpFz8h7VickLQ12nSuUdcPj0cDL/SIcXZWZ3/yNv335/EfuGIWdKXjE+x/+ri136t6Cbu4KbsTRBaCRO0FMnmdCb3kiFGiVEua1hJB491DnVbiWtbpDHDtw1u0FLToCAHhMOk3gjqgw3dSyqMw//pJuZamznScnNJHDx29a6EhCHAYYI4SxljuvGSVUgjafuw+fVIGteM6tP6JlLHr48HD+7jtzbA6Y13h8M99y4FVVY4zbVjigr6WVQqUOnz6u0wquRkjgIsdvbPretFDXEceGqjmDq+vs81fXxfIdQ0RERTIz3r3xYedloSBWnfd7GdnZIUZIRyWTrvd8ri8/snjsB28r7jqO+80aH94ViX0/qqCiW8n1dpc2JUGSuF6vKfaJhR8/GKOAH95800kQhoyIhlAWKnNgnF4vDbjrBiXBZvn8A9Es4x617h8/QKsNa9gd4c1IvSwvl1aqIrQt8y/+8W9Zc6BEEepy58hmAakhmvPo1JiDuUPdOPUyHkpz2i6ojSObC+8fKQiGrpqEurk2SZ01dWvqJmVu2jAGwciP7/Tph1I21Klkb7lhF1ESpS5Vn64vysjpYVuf52UegofQt1qYULvYxejhoFBwy9T11+tLHHePx9MGvk63kHpX81KhVun66eWZU+zCfskTrS2bWdUY2IjQXVrWmLIFthbS2G9mBEVi71mh3QFY7eZ8cGjbtoW8ec0kjqeflNtXCV6XFwbTWn3Y1W6H92fEiA46vu05A4C1QqANoD39qvW7w8N7Or5/vd4dsK1zh2pCSz+E40+kZPSSHj+ty3lz5G1VyxUEp3bRFzLD9BD7MufcjQeW/vL6Oew/pWEU51oW3j20+VLSMXBpra3JgjkGSc3kL/6sfvdtnm+h73H+499Hy6VZCKFenjx1IYTWMqLouqCrIxMJEXNMOj2B9Dy+Xa9PMfUUEyJayUbs7oINZFRkuF2JSmuNjN2zthWcEbHcbszUqq/PX1MfQQKR5OtLAwYvIklvyz5I+/hBVWXs6pbRFIVVFbRIGrhaE/SyWhza63N6OFWn5T6BZ8tr4l1+Ofc/+6bcFySttWIu2O3K/cwhEIAC8y/+4W9B6NEK1MyHN9ga6GZoiMysInv0AmqODtbMCYi0zQhgqgSGw86d2ZuWCTG4VmwFA6kLAVQv3I02T8ZO6QhxBFPumMMeAyi4W+bxKCHlocN1C4e9ocvhoegGSGk8Pf7sN9pybd763clVFclMPUNeL+aO4K1sLFLmmswoRXDNywxx0HWW/aOz6zpTN7B680DCeP/D3/Vy8+a8e6DYl7rYtrIFCqbVwHN891fy8y+pFgQ2b8SxbROhexoBzFqROMTTe8Cg09mtcSdmsW0Xbxg6LtcLx6TzlQihFguj1xZi59bm64uAbwhacjd27bqCbm4SHo407Otyi9C2kkPcYZC2raE7Tq/fMzNZUkEzE880dtt1ov60/HBxuQckSr2lWK8XAwciXzciqrWiGg8HvP/B7wI7AAIyoqNwLU7mmF8gnsyzbZtTH0Jo81fXFeShO7wvT9+3xCGEZiRhcFuZWcZT0cHLK5J4ntyb5wWHB7ufKQxWFyyXJgfRWpdLVdgdH3PZtBkAiK6L0fFwqtfr0rRPqWxLOOytZAt7yq/u6I4eQgQothkcQCd371KaXp+NguZFVcnMuoHR0F3dfd0U0Wt1QATI5xe8/a9/Z2YcyQtClOYtIGH/rq1n1qI+kUYA8uJEYF4xnez2JKf37f7qIaG5d6G1Frve6gTZBFTrhOEE0hkotQpmul0odiUvvm3YRZGDlXtZ5nB8u61rgOa1OEvWJqC4KQXpjh3J4zq9sJe0e7hf57aeexLfHdy1rVdtQOaA2hSo67ZLJjTu/fblzCm+PT083WfYZhr6siywFYwR20auC5DocpU+eJmkVWtZr7/CsqATW695q9Mz+lba1ax5PVuXNL+6AOiCAUKKnLPdz5EHkkTDEccPxr1DsfVcywVTj3Fo85m7nXQ7qlrrBDx0h2/ydIlDMjMaTyKDqIYQeNyt9/P05WW9v6rW6jRvM+iU0lgksIsWRRBkqlpzc2SGZenfPqrq66+esJnw8HK9vPn4U4hBc/vwm38VoDGKKuL1v/5rp8aU1FHS6OWm3QPVO6qhjO7e8s3nZ6eeBMB6s4XSiCESSbtP4c37Nr8YJ46BFGtZqYvYkDiAu7vr9MSU3BHAlnmOg6AptGLbFk7vtWHdzsycq3lbQ3c0vbYth7QXXytECSkbYb0DCDOXUnSdue9RjW3bcjbg2O9aLm2ba3HA1qarVji8f8iFWHy9T01Xjnt4udi+I4RAvGulMnrLs27g12+ziboUO7sApCN3H3SZLS+tPIfdsbWml69luVNM2/3MCIEIlyZdH8djDHsC1Dq5rTq9uEVVRUQ5nIZdL0plmaB71NTp/UZB3QQoYV1j7NwW4j1QN8/3XAkAKOwii3Q7aFW17g8PHHuhPee1QDRVka7Nd0PgHo3V3cFTenz/+u2Xtk45ZzcM6Q20ksnVDac/+A8OqsvdiBkVSACggQUM6BVitGK+zhSTzYvS4iBEhNKTeQuE5pY1dOzcEXdqm0QEjdYUAOrtRWIA5LZObquEAUNXlrnVLQ6DlU1zAQnbmoeHN+XyFA+HqpH1yv24XG4JVTn0h09eryXP7r3ZopJo2wzByoyIMuzKvLb5TkMq0wyZl/mKWs0MsLFIi4nV19uZ40D9gK+//zteNxoOAEjWlB2MCYz6o9eCtkLoCbjp7FkhX90Q+530yY19u9j4gA29LCijbxfaH327g/RgBdtmw3tBytNnph64ExG7vVYwaNlNOZ3K8lJbCwJIkeNx1cb53FpDhhgGTuP85UdI1MfUePT75xZGmc9l2OXzU0L24QBaqEQNuW3ZwFuphmm9/EiYWCCXOzYBYSuVCLZ1xtff/x3p95ZnsALdDrYrpqOVFWKHWoAiozpH0wwuuFWHCgDqOfWn1korG3Ig0wYcJHnbsDsQq9fmrl436oaWAcCJjYHrPEMfA1KtFXRx6o2T3j+bASJaK+H4kzzdA+VWHQKHIFYbIea8cs0Yewxxu74M+8ftci2UxUwRQMFNoG7zPAFA3hoAeMu6lbA/lLwAYVsLRSQy9TIhMO7eMSQMo5kxIyNQ2kMMVRFKwWZeN40IWJEIAeb5rrkQMDugDADm1KAbPc+A4kzOyTzomlmAuFHsmxtEUXVLOzDMW3U1m549vQEAAhOgev2OdWWJHFjrVpsjd7R7C9ho2NVtNa0ppfvlJcYIhVp16R5t25xUayUi08zMdZvNzAkdTUtTBFfTvAmFQa0Yuai5O5Cgu5YNKYGeQTGEaCBmAGbs5t0IqwNHIQwhtW3VPBvV0A9uFay09StCA1Q3QxmIghZFQVsujKOjA1J9/RUNxyCPvt4AgG9P3oV1u6R4Que2TOYbxx02I7028KpbDAMAUDeUskl/lNt1xciRreL8/FlV4/3Fh1OcDfqd15Zz2uZJxjR/eYn7vs0bMGyzSq0aY6/lrlo4kHpQrWyGLbsLdEEVqRZnjsOj6YZVPShDUHUAAAkEjLhZyQCAQvHxL/g6WUX1JnozQxlPXgtg2HQJWnh3CPuf1i2H0rIQHd7QtjbniKSlNp2Htz+t0y3fn/o3vy7dQ75/0bqtTQNSwm1bFl8neXwrgOvrF4UkvcC0Ver0egkhtS0jIoNK4PX1HlLc1jtiqqCo9v8BDuMxrQJTjkYAAAAASUVORK5CYII", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 508, "width" : 1104, "height" : 949, "x" : 1049}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 80, "height": 40, "idx": 11, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "12","path": "images/AcFaMi/AcFaMi20.jpg","image": {"width": 53, "height": 40, "idx": 12, "column": "image", "data": "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", "format": "png"},"label": "AcFaMi","annotations": [{"type" : "rectangle", "coordinates" : {"y" : 239, "width" : 321, "height" : 293, "x" : 369}, "label" : "AcFaMi"}],"image_with_ground_truth": {"width": 53, "height": 40, "idx": 12, "column": "image_with_ground_truth", "data": "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", "format": "png"}},{"__idx": "13","path": "images/AcFaMi/AcFaMi21.jpg","image": {"width": 59, "height": 40, "idx": 13, "column": "image", "data": "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
from turicreate.
znation
commented on June 23, 2024
Thanks @yousifKashef. This looks like a different issue; I'll open a new issue for that.
from turicreate.
znation
commented on June 23, 2024
Opened #930.
from turicreate.
kwade101
commented on June 23, 2024
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.
from turicreate.
znation
commented on June 23, 2024
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.
from turicreate.
juliesoliman
commented on June 23, 2024
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
from turicreate.
znation
commented on June 23, 2024
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!
from turicreate.
znation
commented on June 23, 2024
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.
from turicreate.
fellowProgrammer
commented on June 23, 2024
@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()
from turicreate.
fuomag9
commented on June 23, 2024
@OCJvanDijk's solution worked for me as well!
from turicreate.
unieagle
commented on June 23, 2024
@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.
from turicreate.
Nahatakyan
commented on June 23, 2024
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.
from turicreate.
Related Issues (20)
- TuriCreate not saving nor exporting in Google Colab HOT 1
- Install turicreate on Google colab HOT 1
- Is the image similarity example broken for CoreML?
- Turi Create installation on anaconda virtual environment HOT 1
- issue seaborn
- GraphLab Create requires a license to use in linux HOT 1
- SFRAME problem and turicreate HOT 3
- Can you continue training ObjectDetector model?
- Object detection - Segfault after a large number of iterations
- available data sets in turicreate
- Mac M2 model.export_coreml('.mlmodel') Unable to export model HOT 1
- TuriCreate still doesn't work on M1 using rosetta terminal HOT 7
- While training object_detector in colab randomly Using CPU/GPU to create model.
- Trying to create a model on a larger dataset - Loss stuck at the same number and not moving, resulting model predictions detect nothing
- Support Python 3.9 HOT 1
- pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
- Simple Image Classification Model gives different confidence level (Between Coreml UI and iOS App)
- pip dependency conflicts: conda-repo-cli 1.0.20 requires nbformat==5.4.0, but you have nbformat 5.7.3 which is incompatible. HOT 1
- AttributeError: module 'numpy' has no attribute 'typeDict' HOT 1
- Cannot install and import TuriCreate HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from turicreate.