
This detects furry images, mostly profile pictures, although it may be able detect any sort of furry picture (I haven't tried it, though).

# Dataset Info

This was trained on scraped pfp images from Mastodon, with some non-pfp images thrown in for "balancing" (i.e ensuring pokemon, kemonomimi (catgirls/foxgirls/etc), and normal animals weren't classified as 'furry')

**Furry images**: 551  
**Non-furry images**: 641  

# Disclaimer

Please do not ruin this by using this to harass anyone.  
This is *not* intended to be used for targeted harrassement, and I will explicitly condemn any use that attempts to do so.

If you're wondering why I made this public in the first place?  
I believe in freedom of *information* - this image classification model has various perfectly valid uses, and it's kinda useless to keep it private.

# Statistics

## Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2890884434
- CO2 Emissions (in grams): 2.8752

## Validation Metrics

- Loss: 0.175
- Accuracy: 0.933
- Precision: 0.938
- Recall: 0.938
- AUC: 0.975
- F1: 0.938

{"license": "mit", "tags": ["autotrain", "vision", "image-classification"], "widget": [{"src": "https://files.catbox.moe/72xdjy.png", "example_title": "Furry Avatar"}, {"src": "https://files.catbox.moe/22bao8.jpg", "example_title": "Furry Avatar"}, {"src": "https://files.catbox.moe/xahs5m.png", "example_title": "Normal Animal Avatar"}, {"src": "https://files.catbox.moe/6zvcpu.png", "example_title": "Normal Animal Avatar"}, {"src": "https://files.catbox.moe/gcltc9.png", "example_title": "Kemonomimi Avatar"}, {"src": "https://files.catbox.moe/w4vcoc.png", "example_title": "Kemonomimi Avatar"}, {"src": "https://files.catbox.moe/ujfzv0.png", "example_title": "Human Avatar"}, {"src": "https://files.catbox.moe/yxx1qz.jpg", "example_title": "Human Avatar"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-1.jpg", "example_title": "Normal Cat :3"}], "co2_eq_emissions": {"emissions": 2.8752228959859316}}
transformers pytorch swin image-classification autotrain vision license:mit co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #license-mit #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


This detects furry images, mostly profile pictures, although it may be able detect any sort of furry picture (I haven't tried it, though).

# Dataset Info

This was trained on scraped pfp images from Mastodon, with some non-pfp images thrown in for "balancing" (i.e ensuring pokemon, kemonomimi (catgirls/foxgirls/etc), and normal animals weren't classified as 'furry')

Furry images: 551  
Non-furry images: 641  

# Disclaimer

Please do not ruin this by using this to harass anyone.  
This is *not* intended to be used for targeted harrassement, and I will explicitly condemn any use that attempts to do so.

If you're wondering why I made this public in the first place?  
I believe in freedom of *information* - this image classification model has various perfectly valid uses, and it's kinda useless to keep it private.

# Statistics

## Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2890884434
- CO2 Emissions (in grams): 2.8752

## Validation Metrics

- Loss: 0.175
- Accuracy: 0.933
- Precision: 0.938
- Recall: 0.938
- AUC: 0.975
- F1: 0.938

# Dataset Info

This was trained on scraped pfp images from Mastodon, with some non-pfp images thrown in for "balancing" (i.e ensuring pokemon, kemonomimi (catgirls/foxgirls/etc), and normal animals weren't classified as 'furry')

Furry images: 551  
Non-furry images: 641 # Disclaimer

Please do not ruin this by using this to harass anyone.  
This is *not* intended to be used for targeted harrassement, and I will explicitly condemn any use that attempts to do so.

If you're wondering why I made this public in the first place?  
I believe in freedom of *information* - this image classification model has various perfectly valid uses, and it's kinda useless to keep it private. # Statistics ## Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2890884434
- CO2 Emissions (in grams): 2.8752 ## Validation Metrics

- Loss: 0.175
- Accuracy: 0.933
- Precision: 0.938
- Recall: 0.938
- AUC: 0.975
- F1: 0.938
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #license-mit #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Dataset Info

This was trained on scraped pfp images from Mastodon, with some non-pfp images thrown in for "balancing" (i.e ensuring pokemon, kemonomimi (catgirls/foxgirls/etc), and normal animals weren't classified as 'furry')

Furry images: 551  
Non-furry images: 641 # Disclaimer

Please do not ruin this by using this to harass anyone.  
This is *not* intended to be used for targeted harrassement, and I will explicitly condemn any use that attempts to do so.

If you're wondering why I made this public in the first place?  
I believe in freedom of *information* - this image classification model has various perfectly valid uses, and it's kinda useless to keep it private. # Statistics ## Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2890884434
- CO2 Emissions (in grams): 2.8752 ## Validation Metrics

- Loss: 0.175
- Accuracy: 0.933
- Precision: 0.938
- Recall: 0.938
- AUC: 0.975
- F1: 0.938
TAGS
#transformers #pytorch #swin #image-classification #autotrain #vision #license-mit #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Dataset Info

This was trained on scraped pfp images from Mastodon, with some non-pfp images thrown in for "balancing" (i.e ensuring pokemon, kemonomimi (catgirls/foxgirls/etc), and normal animals weren't classified as 'furry')

Furry images: 551  
Non-furry images: 641# Disclaimer

Please do not ruin this by using this to harass anyone.  
This is *not* intended to be used for targeted harrassement, and I will explicitly condemn any use that attempts to do so.

If you're wondering why I made this public in the first place?  
I believe in freedom of *information* - this image classification model has various perfectly valid uses, and it's kinda useless to keep it private.# Statistics## Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2890884434
- CO2 Emissions (in grams): 2.8752## Validation Metrics

- Loss: 0.175
- Accuracy: 0.933
- Precision: 0.938
- Recall: 0.938
- AUC: 0.975
- F1: 0.938