Merge branch 'feature/divide_in_2_columns' into dev

.gitignore

@@ -0,0 +1,2 @@
+.$template.drawio.bkp
+.$template.drawio.dtmp

app.py

@@ -15,9 +15,12 @@ DATASETS = [
 MAX_N_LABELS = 5
 SPLIT_TO_CLASSIFY = 'pasta'
 
-#(image_object, classifier_pipeline)
-#def classify_one_image(classifier_model, dataset_to_classify):
-#classify_one_image(image_object, classifier_pipeline)
+COLS = st.columns([0.75, 0.25]) 
+#SCROLLABLE_TEXT = COLS[1].text_area("Conteúdo da segunda coluna", height=500)
+SCROLLABLE_TEXT = COLS[1].container(height=500)
+
+
+
 def classify_one_image(classifier_model, dataset_to_classify):
        
        
@@ -49,58 +52,79 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
      
     #dataset
     dataset = load_dataset(shosen_dataset_name,"testedata_readme")
+    #with SCROLLABLE_TEXT:
     #Image teste load 
     image_object = dataset['pasta'][0]["image"]
-    st.image(image_object, caption="Uploaded Image", width=300)
-    st.write("### FLAG 3")
     
+    SCROLLABLE_TEXT.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")
+    #COLS[1].write("### FLAG 4")
     
     #classification
     classification_result = classifier_pipeline(image_object)
-    st.write(classification_result)
-    st.write("### FLAG 5")
+    SCROLLABLE_TEXT.write(classification_result)
+    #COLS[1].write("### FLAG 5")
     #classification_array.append(classification_result)
     
     #save classification
     
     image_count += 1
-    
+    SCROLLABLE_TEXT.write("Image count")
+    SCROLLABLE_TEXT.write(image_count)  
     return image_count
 
+
+def make_template():
+    
+    tile = CONTAINER_TOP.title(":balloon:")
+    tile.title(":balloon:")
+    
+    with CONTAINER_FULL:
+        CONTAINER_TOP.title("titulo de teste dentro do container CONTAINER_TOP")
+        with CONTAINER_BODY:  
+            #COL1, COL2 = st.columns([3, 1])
+            with COLS[1]:
+                CONTAINER_LOOP.write("### OUTPUT")
+
+
 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")
     
-    ## Restart or reset your app
-    #if st.button("Restart"):
-    ## Code to restart or reset your app goes here
-    #    st.experimental_rerun()
+     
+    COLS[0].write("# Bulk Image Classification App")
+    
+      
+    #with CONTAINER_BODY:
+    with COLS[0]:
+        st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
+        st.write("Soon we will have a dataset template")
         
     #Model
-    chosen_model_name = st.selectbox("Select the model to use",  MODELS, index=0)
+    chosen_model_name = COLS[0].selectbox("Select the model to use",  MODELS, index=0)
     if chosen_model_name is not None:
-        st.write("You selected", chosen_model_name) 
+        COLS[0].write("You selected")
+        COLS[0].write(chosen_model_name)
         
     #Dataset
-    shosen_dataset_name = st.selectbox("Select the dataset to use",  DATASETS, index=0)
+    shosen_dataset_name = COLS[0].selectbox("Select the dataset to use",  DATASETS, index=0)
     if shosen_dataset_name is not None:
-        st.write("You selected", shosen_dataset_name)
+        COLS[0].write("You selected")
+        COLS[0].write(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"):
-           
+        if COLS[0].button("Classify images"):
+        
             #classification_array =[]
             classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
-            st.write(f"Classification result: {classification_result}")
+            COLS[0].write("Classification result {classification_result}")
+            COLS[0].write(classification_result)
             #classification_array.append(classification_result)
             #st.write("# FLAG 6")
-            #st.write(classification_array)   
-
+            #st.write(classification_array) 
+                  
 if __name__ == "__main__":
     main()

template.drawio

@@ -0,0 +1 @@
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