1st test

app.py

@@ -49,11 +49,12 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
      
     #dataset
     dataset = load_dataset(shosen_dataset_name,"testedata_readme")
-    #Image teste load 
-    image_object = dataset['pasta'][0]["image"]
-    st.image(image_object, caption="Uploaded Image", width=300)
-    st.write("### FLAG 3")
-    
+    with col2:
+        #Image teste load 
+        image_object = dataset['pasta'][0]["image"]
+        st.image(image_object, caption="Uploaded Image", width=300)
+        st.write("### FLAG 3")
+        
     #modle instance
     classifier_pipeline = pipeline('image-classification', model=chosen_model_name)
     st.write("### FLAG 4")
@@ -72,35 +73,38 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
 
 def main():
     st.title("Bulk Image Classification DEMO")
-    st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
-    st.write("Soon we will have a dataset template")
+    col1, col2 = st.columns([3, 1])
     
-    ## Restart or reset your app
-    #if st.button("Restart"):
-    ## Code to restart or reset your app goes here
-    #    st.experimental_rerun()
-        
-    #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
-    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)
+    with col1:
+        st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
+        st.write("Soon we will have a dataset template")
         
-    #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_array =[]
-            classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
-            st.write(f"Classification result: {classification_result}")
-            #classification_array.append(classification_result)
-            #st.write("# FLAG 6")
-            #st.write(classification_array)   
+        ## Restart or reset your app
+        #if st.button("Restart"):
+        ## Code to restart or reset your app goes here
+        #    st.experimental_rerun()
+            
+        #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
+        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]  
+        if chosen_model_name is not None and shosen_dataset_name is not None:
+            if st.button("Classify images"):
+            
+                #classification_array =[]
+                classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
+                st.write(f"Classification result: {classification_result}")
+                #classification_array.append(classification_result)
+                #st.write("# FLAG 6")
+                #st.write(classification_array)   
 
 if __name__ == "__main__":
     main()