Update README.md

README.md

@@ -173,7 +173,48 @@ Performs poorly on cluttered background.
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/9UJJdjJ34avY5MmNDVKjS.png)
 
+## Anime Art Scoring
+A classification model trained to assign a percentile group based on human preference, instead of trying to directly assign a "quality" label.  
+Dataset was composed of about 100k images aged from 1 to 2 years on Danbooru (newer and older images were not used). That limits data to images that were sufficiently viewed and rated, while not being overly exposed due to age, nor underexposed.  
+Scores were used and split into percentile groups, each 10%.  
 
+Main interest in making this one was to find out if there is a significant discoverable correlation between scores and image quality.  
+Here are my custom charts:  
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/CYJOjJUp-pVhVUCYSDyhb.png)
+
+(top100 is second class due to alphabetical sorting, but for margin acceptance chart it was re-sorted)  
+
+From this chart, considering there are 10 classes in total, i found weak-to-modest correlation between scores and upper half of chart, negative correlation with middle-low part, weak for low, and moderate for lowest.  
+  
+What does that mean?  
+
+It means that there is meaningful correlation between scoring of people relative to features of art in question, but there is no meaningful correlation between art that is scoring neutrally.  
+Negative scoring (top80-100) has moderate correlation, which suggests that there are some uniform negative features we can infere.  
+Top60 class is very interesting, because it presents no correlation between provided images, even in top-3 accuracy(it performs at near-random selection in that case(10%)).  
+That suggests that there is no feature correlation between art being not noticed, at least not the one YOLO was able to find.  
+
+We can reasonably predict art that will end up in top of the chart by human score, but we are not able to predict middle-of-the line art, which would constitute majority of art in real case.  
+We can predict low quality based on human preference reasonably well, but far from ideal.  
+
+Margin acceptance charts - A top-1 accuracy, but with margin of class acceptance(1, 2 and 3(starts with -1, then adds +1 and then -2 class)(it/s not +-1-3 as naming suggests))  
+This allows us to see how well are classes correlate. If we see significant increase relative to first chart, that means that second best prediction was selected as top-1.  
+We can also see extended correlation trend across classes. We once again can see that middle classes have very low correlation and accuracy, suggesting no meaningful features.  
+That kinda suggests to me that there is no reason for art that ended up in middle of dataset to be there, and it would end up higher or lower in perfect world.  
+
+Top10-40 correlates very well, and that can be used for human preference detection. Funny note on that: **bigger the breasts - better the score**.  
+And i wholeheartedly support that notion.  
+NSFW art in general will have higher preference score, well, what an unexpected outcome, amirite? Dataset was composed ~50/50% from Danbooru/Safebooru(safebooru.donmai.us), so it's not due to overrepresentation of NSFW.  
+That is also why you should not use scores for quality tagging, but if you are looking for a thing to maintain high compatibility with current anime models - be my guest.  
+Correlation between bottom scores(that you'd use for low quality/worst quality) is weaker, so be conservative with that.  
+
+Bigger model and data will likely see more correlation, but from quick test of just running larger variation did not lead me to better performance.  
+
+| Model                       | Target                |Top-1 acc/(w/ margin(1/2/3))|Top-2 acc|Top-3 acc|Classes        |Dataset size|Training Resolution|
+| --------------------------- | --------------------- |---------|---------|---------|---------------|------------|-------------------|
+  | [Anzhcs Anime Score CLS v1.pt]()| Anime illustration |0.336(0.467/0.645/0.679)|0.566|0.696|10(top10 to top100)|~98000        |224|
+
+Additionally, i will provide a script for tagging your datasets with that, if you want - placeholder
 
 ### Support
 If you want to support me, feel free to donate on ko-fi: