The FTP access doesn't work.

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Though I did use the upload interface on the actual website and gave it ago. I uploaded a head shot of a man. The auto keywords were reasonably accurate. I did see a few not applicable keywords. So if one does not care about a few bad keywords then this is a real time saver.

I have wondered on a separate note if it matters that photos are uploaded to stock websites with mostly accurate keywords and a few not applicable keywords. Because it seems as if the stock websites run test on which keywords on different images get a click from real users of the site. So the website learns over time which keywords on different images to either ignore or prioritize.

The photo I uploaded is a man on a green screen not smiling. See attached.

These are the results from the auto keywords
Men, People, Adult, One Person, Males, Caucasian Ethnicity, Portrait, Looking At Camera, Male Beauty, Studio Shot, Copy Space, Young Adult, Looking, One Man Only, Casual Clothing, Confidence, Human Face, Serious, Young Men, Head And Shoulders, Color Image, Only Men, Close-up, Indoors, Adults Only, Real People, Lifestyles, Front View, Smiling, Standing, Facial Expression, Green Color, Colored Background, Green Background, Beautiful, Headshot, Cheerful, T-Shirt, Blue, Masculinity, Positive Emotion, One Young Man Only, Fashion, Beautiful People, Brown Hair, Thinking, Posing, Shirt, Backgrounds

Some inaccurate keywords are - smiling, cheerful, blue, positive emotions, fashion, thinking, posing, backgrounds.

It seems all the inaccurate keywords are towards the bottom of the list, which seems to suggest the list is sorted based upon a confidence ranking. Might be easier to give the user an ability to filter out keywords that have a low confidence score. Google, Microsoft, Amazon's image recognition software all put a confidence number next to the keywords they produce. Such as Men (99), Casual Clothing (70), chair (12). In this example, anything below a 70 could probably be filtered out. 

Thanks for your attention!

The FTP access doesn't work.

"Error -203: miscellaneous error occurred while trying to login to the host"

The FTP access was temporarily suspended due to exceeding the limit of active users. We've raised the limit, so now FTP is able :)

Some inaccurate keywords are - smiling, cheerful, blue, positive emotions, fashion, thinking, posing, backgrounds.

We assume that not all keywords may be quite relevant for your photography. That's why we have implemented a convenient interface for metadata editing � and you can delete inaccurate keywords in one click.

It seems all the inaccurate keywords are towards the bottom of the list, which seems to suggest the list is sorted based upon a confidence ranking. Might be easier to give the user an ability to filter out keywords that have a low confidence score. Google, Microsoft, Amazon's image recognition software all put a confidence number next to the keywords they produce. Such as Men (99), Casual Clothing (70), chair (12). In this example, anything below a 70 could probably be filtered out. 

The confidence score may be helpful in some situations, but this can affect that users will be too strict in their approach to filtering keywords. Like in your example, clean up everything rated below 70. As a result, the effectiveness of auto-keywording will decrease, cause a low rating doesn't always mean that the keyword is unnecessary and doesn't correspond to the image.

The software should have looked at the keywords within the file instead of ignoring them.

We're working on it ;)

so, while it might do ok with simple stock images, on the unique ones, the ones where we need assistance, it fails

We experimented. We measured the sales of photos with auto keywords and keywords selected by a person. The number of sales with automatic keywords was at least 10% higher.

As we found out, this is because people are more likely to look for photos in general terms, rather than by specific names of locations and objects. As a result, the images containing general keywords received more sales than those containing original place names.

Quote from: cascoly on May 30, 2019, 13:16

so, while it might do ok with simple stock images, on the unique ones, the ones where we need assistance, it fails

We experimented. We measured the sales of photos with auto keywords and keywords selected by a person. The number of sales with automatic keywords was at least 10% higher.

As we found out, this is because people are more likely to look for photos in general terms, rather than by specific names of locations and objects. As a result, the images containing general keywords received more sales than those containing original place names.

Was that person someone who didn't know how to keyword? Software can get better with refinement, people get better with experience. I shoot a lot of the same things over and over again because I know in general they sell, but I don't actually know which image will sell because that is sort of up to the algorithm of the stock website to decide which images to serve up on the top of their search results. Your claim of 10% higher sales by auto keywords is in my opinion impossible to prove. And I've already said in an earlier post that I thought that your software was quite good, though not perfect. It lacks the nuisance understanding about the context about some photos that only the original photographer could know. Take my glacier photo, your software did not know it was from Argentina. Realistically it was impossible for your software to know, it was an iPhone photo but the GPS data was missing, I didn't take it out. So I suppose one of the editing software I used took it out. Anyway, I think your claim 10% higher sales is  silly.

Also I assume people search both in general terms and specific terms. A human keyworder who knows the context of where the photo came from would put in both types of keywords. Your software would lose sales from those who are searching with very specific terms.

As we found out, this is because people are more likely to look for photos in general terms, rather than by specific names of locations and objects. As a result, the images containing general keywords received more sales than those containing original place names.

From the agency on which I can see search terms, that's not true. Specific searches are most common, then general, then a small proportion of 'goodness knows what they wanted'. Possibly that's not true of all agencies, I couldn't possibly say.
But anyone with any sense keywords specifically and then outwards to more general terms.

Quote from: Not Today on May 31, 2019, 07:43

Was your experiment done on commercial photos only or commercial VS editorial?

I find editorial content to have more sales when it's very specific.

Our friendly photo production studio tested the algorithm on several commercial shoots.

Keywords for half of the images were selected with Everypixel DAM, for the other half with the help of distribution specialists. They have been working on keywording for many years.

At the end of the month, the sales of the images with auto-keywording were higher.

Must be not very good human keyworders. There is inherently no reason why a human wouldn't be every bit as good as software, if not a great deal better. Humans understand a lot of context that software for the moment often can't. Even if the software knew some keywords that the human didn't, the human only needs to look once at what the software did, and now the human knows too, and the human still has extra ability to understand context. What is the great promise of software driven keywording is 'speed'. Humans will never do it as fast as software. Multiply that time saving over thousand or tens of thousands of files, that is an enormous amount of time saved. Time is money, thus an enormous amount of money saved. Anyway, I think your software is great, but I also think it is silly for you to say your software keywords are better than human keywords. 

�.

Our friendly photo production studio tested the algorithm on several commercial shoots.

Keywords for half of the images were selected with Everypixel DAM, for the other half with the help of distribution specialists. They have been working on keywording for many years.

At the end of the month, the sales of the images with auto-keywording were higher.

even if it was 1 month after acceptance AND assuming equal quality, acceptance rate and salability , that's not much of a test, esp'ly if sales were only 10% difference --  that could easily be explained by random events