Update app.py

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from transformers import pipeline, AutoModelForImageClassification, AutoImageProcessor
+from transformers import pipeline
 import torch
 from PIL import Image
 import numpy as np
@@ -17,20 +17,19 @@ def load_models():
     # Carregando modelos específicos para feridas
     wound_classifier = pipeline(
         "image-classification",
-        model="stevhliu/wound-classification",  # Modelo específico para classificação de feridas
+        model="stevhliu/wound-classification",
         device=0 if torch.cuda.is_available() else -1
     )
     
     tissue_classifier = pipeline(
         "image-classification",
-        model="viktorcikojevic/wound-tissue-type",  # Modelo para classificação do tipo de tecido
+        model="viktorcikojevic/wound-tissue-type",
         device=0 if torch.cuda.is_available() else -1
     )
     
     return wound_classifier, tissue_classifier
 
 def preprocess_image(image):
-    # Normalização e pré-processamento da imagem
     if isinstance(image, np.ndarray):
         image = Image.fromarray(image)
     image = image.convert('RGB')
@@ -49,14 +48,13 @@ def classify_wound(image):
     # Classificação do tipo de tecido
     tissue_results = tissue_classifier(processed_image)
     
-    # Formatando resultados da classificação de feridas
+    # Formatando resultados
     wound_formatted = []
     for result in wound_results:
         label = WOUND_TYPES.get(result['label'], result['label'])
         score = result['score']
         wound_formatted.append((label, score))
     
-    # Formatando resultados da classificação de tecidos
     tissue_formatted = []
     for result in tissue_results:
         label = result['label'].replace('_', ' ').title()
@@ -65,7 +63,7 @@ def classify_wound(image):
     
     return wound_formatted, tissue_formatted
 
-# Criando a interface do Gradio
+# Interface Gradio
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
     # 🏥 Classificador Especializado de Feridas
@@ -77,8 +75,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         with gr.Column():
             input_image = gr.Image(
                 label="Upload da Imagem",
-                type="pil",
-                tool="select"
+                type="pil"
             )
             submit_btn = gr.Button("Analisar Ferida", variant="primary", size="lg")
         
@@ -121,16 +118,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         inputs=input_image,
         outputs=[wound_output, tissue_output]
     )
-    
-    # Exemplos
-    gr.Examples(
-        examples=[
-            ["image1.jpg"]
-        ],
-        inputs=input_image,
-        outputs=[wound_output, tissue_output],
-        cache_examples=True
-    )
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch()