feat: reorganizar modelos em categorias e adicionar novos classificadores

- Reorganizada lista de modelos em 20 categorias por tipo de classificação
- Adicionados 22 modelos novos do Hugging Face com sufxo " << new >>"
- Atualizada função classify para remover sufxo antes de usar modelo
- Adicionado texto explicativo a destacar 22 novos modelos adicionados

---
feat: reorganize models into categories and add new classifiers

- Reorganized model list into 20 categories by classification type
- Added 22 new Hugging Face models with " << new >>" suffix
- Updated classify function to remove suffix before using model
- Added explanatory text highlighting 22 new models added

app.py

@@ -25,8 +25,8 @@ MODELS = [
             "timm/tf_efficientnetv2_s.in21k",
             "timm/convnext_tiny.fb_in22k",
             "vit-base-patch16-224-in21k",
-            "facebook/deit-base-distilled-patch16-224 new",
-            "WinKawaks/vit-tiny-patch16-224 new",
+            "facebook/deit-base-distilled-patch16-224 << new >>,
+            "WinKawaks/vit-tiny-patch16-224 << new >>,
 
             "-- Age Classification --",
             "nateraw/vit-age-classifier",
@@ -35,12 +35,12 @@ MODELS = [
             "Falconsai/nsfw_image_detection",
             "LukeJacob2023/nsfw-image-detector",
             "carbon225/vit-base-patch16-224-hentai",
-            "Marqo/nsfw-image-detection-384 new",
+            "Marqo/nsfw-image-detection-384 << new >>",
 
             "-- Aesthetic/Art Classification --",
             "cafeai/cafe_aesthetic",
             "shadowlilac/aesthetic-shadow",
-            "pixai-labs/pixai-tagger-v0.9 new",
+            "pixai-labs/pixai-tagger-v0.9 << new >>",
 
             "-- Face/Emotion Classification --",
             "trpakov/vit-face-expression",
@@ -49,22 +49,22 @@ MODELS = [
 
             "-- Food Classification --",
             "nateraw/food",
-            "BinhQuocNguyen/food-recognition-model new",
+            "BinhQuocNguyen/food-recognition-model << new >>",
 
             "-- Medical/Dermatology --",
-            "google/derm-foundation new",
-            "google/cxr-foundation new",
-            "Anwarkh1/Skin_Cancer-Image_Classification new",
+            "google/derm-foundation << new >>",
+            "google/cxr-foundation << new >>",
+            "Anwarkh1/Skin_Cancer-Image_Classification << new >>",
 
             "-- AI vs Human Detection --",
-            "Ateeqq/ai-vs-human-image-detector new",
-            "umm-maybe/AI-image-detector new",
+            "Ateeqq/ai-vs-human-image-detector << new >>",
+            "umm-maybe/AI-image-detector << new >>",
 
             "-- Deepfake Detection --",
             "not-lain/deepfake",
 
             "-- Anime/Manga Classification --",
-            "Readidno/anime.mili new",
+            "Readidno/anime.mili << new >>",
 
             "-- Human Activity Recognition --",
             "DunnBC22/vit-base-patch16-224-in21k_Human_Activity_Recognition",
@@ -79,22 +79,22 @@ MODELS = [
             "FatihC/swin-tiny-patch4-window7-224-finetuned-eurosat-watermark",
 
             "-- Car Classification --",
-            "lamnt2008/car_brands_classification new",
+            "lamnt2008/car_brands_classification << new >>",
 
             "-- Document Classification --",
-            "docling-project/DocumentFigureClassifier-v2.5 new",
+            "docling-project/DocumentFigureClassifier-v2.5 << new >>",
 
             "-- EfficientNet (timm) --",
-            "timm/efficientnet_b0.ra_in1k new",
+            "timm/efficientnet_b0.ra_in1k << new >>",
             "timm/mobilenetv3_large_100.ra_in1k",
-            "timm/mobilenetv3_small_100.lamb_in1k new",
+            "timm/mobilenetv3_small_100.lamb_in1k << new >>",
 
             "-- Experimental/Future --",
             "#q-future/one-align",
         ]
 
 def classify(image, model):
-    model_name = model.replace(" new", "")
+    model_name = model.replace(" << new >>", "")
     classifier = pipeline("image-classification", model=model_name)
     result= classifier(image)
     return result
@@ -122,6 +122,7 @@ def print_result(result):
 def main():
     st.title("Image Classification")
     st.write("This is a simple web app to test and compare different image classifier models using Hugging Face's image-classification pipeline.")
+    st.markdown(":white_check_mark: **:green[22 new models added!]** - Including Medical, AI vs Human detection, Anime classification and more.")
     st.write("From time to time more models will be added to the list. If you want to add a model, please open an issue on the GitHub repository.")
     st.write("If you like this project, please consider liking it or buying me a coffee. It will help me to keep working on this and other projects. Thank you!")