no message

app.py

@@ -15,7 +15,7 @@ DATASETS = [
 MAX_N_LABELS = 5
 
 
-def classify_images(classifier_model, dataset_to_classify):
+def old_classify_images(classifier_model, dataset_to_classify):
        
     for image in dataset:
         st("Image classification: ", image['file'])
@@ -29,62 +29,63 @@ def classify_images(classifier_model, dataset_to_classify):
     '''
     return "done"
 
-def classify(image, classifier_pipeline):
+
+
+def classify_full_dataset(shosen_dataset_name, chosen_model_name):
+    
+    #dataset
+    dataset = load_dataset(shosen_dataset_name,"testedata_readme")
+    st.write("# FLAG 2")
+    
+    #Image teste load 
+    image_object = dataset['pasta'][0]["image"]
+    st.image(image_object, caption="Uploaded Image", use_column_width=True)
+    st.write("# FLAG 3")
+    
+    #modle instance
+    classifier_pipeline = pipeline('image-classification', model=chosen_model_name)
+    #classifier_pipeline = pipeline('image-classification', model="nateraw/vit-age-classifier", device=0)
+    st.write("# FLAG 4")
+    #classification
+    classification_result = classify(image_object, classifier_pipeline)
+    st.write(classification_result)
+    st.write("# FLAG 5")
+
+      
+    
     return "done"
 
+
+
+
 def main():
     st.title("Bulk Image Classification")
     st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
     st.write("Soon we will have a dataset template")
     
-
-    '''
-        Model
-    '''
+    #Model
     chosen_model_name = st.selectbox("Select the model to use",  MODELS, index=0)
     if chosen_model_name is not None:
         st.write("You selected", chosen_model_name) 
         
-    '''
-        Dataset
-    '''          
+    #Dataset
     shosen_dataset_name = st.selectbox("Select the dataset to use",  DATASETS, index=0)
     if shosen_dataset_name is not None:
         st.write("You selected", shosen_dataset_name)
         
-
-           
-    '''
-        click to classify
-        image_object = dataset['pasta'][0]
-    '''    
+    #click to classify
+    #image_object = dataset['pasta'][0]  
     if chosen_model_name is not None and shosen_dataset_name is not None:
         if st.button("Classify images"):
             
-            classification_obj1 =[]
-            st.write("# FLAG 1")
-            
-            dataset = load_dataset(shosen_dataset_name,"testedata_readme")
-            st.write("# FLAG 2")
-            
-            #Igame 
-            image_object = dataset['pasta'][0]["image"]
-            st.image(image_object, caption="Uploaded Image", use_column_width=True)
-            st.write("# FLAG 3")
+            classification_array =[]
             
-            #modle instance
-            classifier_pipeline = pipeline('image-classification', model=chosen_model_name)
-            #classifier_pipeline = pipeline('image-classification', model="nateraw/vit-age-classifier", device=0)
-            st.write("# FLAG 4")
+            st.write("# FLAG 1")
+            classification_result = classify(shosen_dataset_name, chosen_model_name)
             
-            #classification
-            classification_result = classify(image_object, classifier_pipeline)
-            st.write(classification_result)
-            st.write("# FLAG 5")
-            classification_obj1.append(classification_result)
+            classification_array.append(classification_result)
             st.write("# FLAG 6")
-            st.write(classification_obj1)
-    
+            st.write(classification_array)   
 
 if __name__ == "__main__":
     main()