I've created a public labeling job so people could help me label objects on 50+ images using 8 different classes.
This job is finished, but I'm still unable to run the training job I've created.
Here's how the job is set up:
Algorithm: built-in object detection
Input data configuration:
Data source: S3
URI: the manifest url generated by the labeling job On S3
I'm getting this error message: "Missing image files in train channel".
Shouldn't it get the images path from the manifest?
What am I missing?
It's a little difficult to diagnose without some additional information (basically the entire request you're making to the CreateTrainingJob API or, if you're using the AWS SageMaker console, the training job definition).
This is probably the most relevant resource as a starting point: https://aws.amazon.com/blogs/machine-learning/easily-train-models-using-datasets-labeled-by-amazon-sagemaker-ground-truth/. You might also find it worthwhile to read through https://docs.aws.amazon.com/sagemaker/latest/dg/augmented-manifest.html.
It could be any number of things, but my hunch is that it has something to do with the configuration of the training job you're trying to create, e.g., the S3DataType has to be "AugmentedManifestFile," the InputMode has to be "Pipe", etc. All these are described in the above links.
Related
I am trying to train two models on Watson VR. One is for object (details) recognition within a picture. The other is to estimate the class object.
I have been able to prepare the classes of object for both models.
However, it seems I have multiple issues with training and I am now stack. I have found a similar post in Stack Overflow but it relates to data size and type; my data are all in .jpg format and all dataset is below 250 MB.
Classifier:
The classifier is the one that gives me more issues.
Firstly, I have tried to train the model but then the server went down. The day after I have found the model "trained" but with errors. I basically restarted by preparing again the classes.
All classes have at least 10-12 pictures (10 is minimum required). When I click on "Train Model" I receive the following error:
In the dashboard I am given explanation of the failed training:
Data size was originally about 241/250 MB, now it is 18.4/250 MB. I am not sure what brought the change.
Thank you for the help!
Thanks for providing the screenshots, that is very helpful!
It says your "DrinksClassifier" is in a failed state. It's best to delete that collection from Studio, and start over. Make sure you have at least 10 examples of each class... the lower screenshot seems to show it didn't find any examples for "AgedCoffee".
I am building a web application where the users can create reports and then upload some images for the created reports. Those images will be rendered in the browser when the user clicks a button on the report page. The images are confidential and only authorized users will be able to access them.
I am aware of the pros and cons of storing images in database, in filesystem or a service like amazon S3. For my application, I am inclined to keep the images in the filesystem and paths of the images in the database. That means I have to deal with the problems arising around distributed transaction management. I need some advice on how to deal with these problems.
1- I believe one of the proper solutions is to use technologies like JTA and XADisk. I am not very knowledgeable about these technologies but I believe 2 phase commit is how automicity is achieved. I am using MySQL as the database, and it seems like 2 phase commit is supported by MySQL. Problem with this approach is XADisk does not seem to be an active project and there is not much documentation about it and there is the fact that I am not very knowlegable about the ins and outs of this approach. I am not sure if I should invest in this approach.
2- I believe I can get away with some of the problems arising from the violation of ACID properties for my application. While uploading images, I can first write the files to disk, if this operation succeeds I can update the paths in the database. If database transaction fails, I can delete the files from the disk. I know that is still not bulletproof; an electricity shortage might occur just after the db transaction or the disk might not be responsive for a while etc...I know there are also concurrency issues, for instance if one user tries to modify the uploaded image and another tries to delete it at the same time, there will be some problems. Still the chances for concurrent updates in my application will be relatively low.
I believe I can live with orphan files on the disk or orphan image paths on the db if such exceptional cases occur. If a file path exists in db and not in the file system, I can show a notification to the user on report page and he might try to reupload the image. Orphan files in the file system would not be too much problem, I might run a process to detect such files time to time. Still, I am not very comfortable with this approach.
3- The last option might be to not store file paths in the db at all. I can structure the filesystem such that I can infer the file path in code and load all images at once. For instance, I can create a folder with the name of report id for each report. When a request has been made to load images of the report, I can load the images at once since I know the report id. That might end up with huge number of folders in the filesystem and I am not sure if such a design is acceptable. Concurrency issues will still exist in this scheme.
I would appreciate some advice on which approach I should follow.
I believe you are trying to be ultra-correct, and maybe not that much is needed, but I also faced some similar situation some time ago and explored also different possibilities. I disliked options aligned to your option 1, but about the 2 and 3, I had different successful approaches.
Let's sum up first the list of concerns:
You want the file to be saved
You want the file path to be linked to the corresponding entity (i.e the report)
You don't want a file path to be linked to a file that doesn't exist
You don't want files in the filesystem not linked to any report
And the different approaches:
1. Using DB
You can assure transactions in the DB pretty much with any relational database, and with S3 you can ensure read-after-write consistency for both new objects and upload of new objects. If you PUT an object and you get a 200 OK, it will be readable. Now, how to put all this together? You need to keep track of the process. I can figure 2 ways:
1.1 With a progress table
The upload request is saved to a table with anything need to identify this file, report id, temp uploaded file path, destination path, and a status column
You save the file
If the file safe fails you can update the record in the table, or delete it
If saving the file is successful, in a transaction:
update the progress table with successful status
update the table where you actually save the relationship report-image
Have a cron, but not checking the filesystem, but checking the process table. If there is any file in the filesystem that is orphan, definitely it had been added to the table (it was point 1). Here you can decide if you will delete the file, or if you have enough info, you can continue with the aborted process triggering the point 4.
The same report-image relationship table with some extra status columns.
1.2 With a queue system
Like RabbitMQ, SQS, AMQ, etc
A very similar approach could be done with any queue system instead of a db table. I wont give much details because it depends more on your real infrastructure, but just the general idea.
The upload request goes to a queue, you send a message with anything you may need to identify this file, report id, and if you want a tentative final path.
You upload the file
A worker reads pending messages in the queue and does the work. The message is marked as consumed only when everything goes well.
If something fails, naturally the message will come back to the queue
In the next time a message is read, the worker can have enough info to see if there is work to resume, or even a file to delete if resuming is not possible
In both cases, concurrency problems wont be straightforward to manage, but can be managed (relying on DB locks in fist case, and FIFO queues in second cases) but always with some application logic
2. Without DB
To some extent a system without a database would be perfectly acceptable, if we can defend it as a proper convention over configuration design.
You have to deal with 3 things:
Save files
Read files
Make sure that the structure of the filesystem is manageable
Lets start with 3:
Folder structure
In general, something like one folder for report id will be too simple, and maybe hard to maintain, and also ultimately too plain. This will cause issues, because if we have a folder images with one folder per report, and tomorrow you have less say 200k reports, the images folder will have 200k elements, and even an ls will take too much time, same for any programing language trying to access. That will kill you
You can think about something more sophisticated. Personally like a way that I learnt from Magento 1 more than 10 years ago and I used a lot since then: Using a folder structure following first outside rules, but extended with rules derived extended with the file name itself.
We want to save a product image. The image name is: myproduct.jpg
first rule is: for product images i use /media/catalog/product
then, to avoid many images in the same one, i create one folder per every letter of the image name, up to some number of letters. Lets say 3. So my final folder will be something like /media/catalog/product/m/y/p/myproduct.jpg
like this, it is clear where to save any new image. You can do something similar using your reports id, categories, or anything that makes sense for you. The final objective is to avoid too flat structure, and to create a tree that makes sense to you, and also that can be automatized easily.
And that takes us to the next part:
Read and write.
I implemented a similar system before quite successfully. It allowed me to save files easy, and to retrieve them easily, with locations that were purely dynamic. The parts here were:
S3 (but you can do with any filesystem)
A small microservice acting as a proxy for both read and write.
Some namespace system and attached logic.
The logic is quite simple. The namespace lets me know where the file will be saved. For example, the namespace can be companyname/reports/images.
Lets say a develop a microservice for read and write:
For saving a file, it receives:
namespace
entity id (ie you report)
file to upload
And it will do:
based on the rules I have for that namespace, and the id and file name will save the file in this folder
it doesn't return the physical location. That remains unknown to the client.
Then, for reading, clients will use a URL that uses also convention. For example you can have something like
https://myservice.com/{NAMESPACE}/{entity_id}
And based on the logic, the microservice will know where to find that in the storage and return the image.
If you have more than one image per report, you can do different things, such as:
- you may want to have a third slug in the path such as https://myservice.com/{NAMESPACE}/{entity_id}/1 https://myservice.com/{NAMESPACE}/{entity_id}/2 etc...
- if it is for your internal application usage, you can have one endpoint that returns the list of all eligible images, lets say https://myservice.com/{NAMESPACE}/{entity_id} returns an array with all image urls
How I implemented this was with quite simple yml config to define the logic, and very simple code reading that config. That allowed me to have a lot of flexibility. For example save reports in total different paths or servers or s3 buckets if they belong to different companies or are different report types
I'm currently working on a web application which generates daily error (and non error) logs.
The current system outputs a log per task to a text file, and outputs critical errors as well as "start" and "finish" type messages to an email account.
The current workflow is as follows: scour the email box for errors, then go and find the .txt file to look at the associated errors and find the cause.
There are around 30 txt files split across about 5 servers.
This system was set up before me, but I'm looking for any advice on how to deal with the situation.
I have control of the script forming the error logs so can do pretty much anything - but I'm lost where to start: I'd considered some kind of web facing dashboard tool, maybe output the files to RSS or something?
Are there any external or internal tools I should be using?
Of course you may use the SQL Server Reporting Services or review this comparison table, there are some packages which may support SQL Server but they may be overwhelming for your task.
It's not really clear what your problem is or what you want to do, but if I understand correctly, your biggest problem is that some messages are logged to a log file but others are sent by email. Therefore, there is no single location that has all error messages in it and that makes analysis and troubleshooting difficult.
The best solution would be to use a logging framework that supports multiple logging destinations (file, DB, email) and severities. That would allow you to specify a configuration like "all errors are logged to a text file and critical ones are also sent by email", so you can ensure that you have everything in one place for general analysis but critical errors are also handled with priority.
You didn't mention what programming language you use, but assuming it's .NET-based then log4net and Enterprise Library are two common frameworks and there are many questions about them here on SO. Googling should give you a good idea of the pros and cons for your situation. If you're using a different language then you can look for the equivalent package: log4j (Java), logging (Python) etc.
Over the last few weeks we have repeatedly failed on doing a complete backup of the data store using the datastore admin tool. We thought the issues had to do with quota errors we were running into so we switched our application from a free to a paid app and we still have problems.
Each time we are attempting to back up to the blobstore and what occurs is that the process never finishes. We see the backup in our Pending Backups list but it never actually completes. We only have a total of 43MB of data right now so we don't see it as a data transfer problem. Looking at our default Task Queues it shows that we have two pending tasks one is a call to /_ah/mapreduce/controller_callback and another is a call to /_ah/mapreduce/worker_callback
The worker_callback racks up its retry count and the only error clue we have is on the Previous Run tab it shows the last http response code to be 500. There is no error message, nothing shows up in our error logs, it just keeps trying over and over again.
We've been able to narrow the backup problems to a specific entity kind for a particular namespace but we can't figure out why that entity kind is failing whereas the others are not. The major difference is the entity kind has a large number of embedded entities, but if the app engine is able to read / put those entities we can't understand why it seems to be having problems backing it up. The particular namespace that the error occurs in has the largest data stored for that entity kind compared to the other namespaces we have setup.
We think if we can see what error is occurring in the worker_callback we may be able to figure out why the backup is failing, or what is wrong with our data that's preventing the backup. Is there something we need to setup / enable through settings / configuration files to give us more detailed information on the backup? Or is there some other avenue we should explore to figure out how to investigate/fix this problem?
I should mention we are using the Java SDK as well as Objectify V3 to work with the data store. We are also backing up data to the Blobstore.
Thank you.
Well with the app engine team's help we figured what the problem was and we worked around the issue. I want to give details in case anyone else runs into this problem.
From issue 8363 the app engine team indicated that from their logs they could see that the map reduce failed because of the large number of properties that our entity kind had. The specific entity kind that was causing the failure had a large number of variable properties that was generating errors when map reduce tried to write out a schema. They indicated that the solution on their end was to ignore entities that were like this in the backup to make it so the backup worked successfully.
What we did to work around the issue and make the backup work was change how we told objectify to store out data. The large number of properties were being created due to our use of the #embedded keyword on a HashMap() class member field. Since the embedded keyword breaks down classes into individual components it was generating a large number of properties. We switched the member field to be #serialized and then ran a conversion process to make it use the new serialized property. This made the backup / restore work again.
You can read more about the differences between embedded and serialized on objectify's website
snielson, would you mind opening an issue on our Public issue tracker here. Remember to add your Application ID so we can further debug this specific scenario.
Thanks!
I'm stumped and need some ideas on how to do this or even whether it can be done at all.
I have a client who would like to build a website tailored to English-speaking travelers in a specific country (Thailand, in this case). The different modes of transportation (bus & train) have good web sites for providing their respective information. And both are very static in terms of the data they present (the schedules rarely change). Here's one of the sites I would need to get info from: train schedules The client wants to provide users the ability to search for a beginning and end location and determine, using the external website's information, how they can best get there, being provided a route with schedule times for the different modes of chosen transport.
Now, in my limited experience, I would think the way to do that would be to retrieve the original schedule info from the external site's server (via API or some other means) and retain the info in a database, which can be queried as needed. Our first thought was to contact the respective authorities to determine how/if this can be done, but this has proven to be problematic due to the language barrier, mainly.
My client suggested what is basically "screen scraping", but that sounds like it would be complicated at best, downloading the web page(s) and filtering through the HTML for relevant/necessary data to put into the database. My worry is that the info on these mainly static sites is so static, that the data isn't even kept in a database to build the page and the web page itself is updated (hard-coded) when something changes.
I could really use some help and suggestions here. Thanks!
Screen scraping is always problematic IMO as you are at the mercy of the person who wrote the page. If the content is static, then I think it would be easier to copy the data manually to your database. If you wanted to keep up to date with changes, you could then snapshot the page when you transcribe the info and run a job to periodically check whether the page has changed from the snapshot. When it does, it sends an email for you to update it.
The above method could also be used in conjunction with some sort of screen scaper which could fall back to a manual process if the page changes too drastically.
Ultimately, it is a case of how much effort (cost) is your client willing to bear for accuracy
I have done this for the following site: http://www.buscatchers.com/ so it's definitely more than doable! A key feature of a web scraping solution for travel sites is that it must send you emails if anything went wrong during the scraping process. On the site, I use a two day window so that I have two days to fix the code if the design changes. Only once or twice have I had to change my code, and it's very easy to do.
As for some examples. There is some simplified source code here: http://www.buscatchers.com/about/guide. The full source code for the project is here: https://github.com/nicodjimenez/bus_catchers. This should give you some ideas on how to get started.
I can tell that the data is dynamic, it's to well structured. It's not hard for someone who is familiar with xpath to scrape this site.