Update app.py

app.py

@@ -7,9 +7,6 @@ from gradio_client import Client
 import base64
 import datetime
 
-if 'blur_option' not in st.session_state:
-    st.session_state.blur_option = True  
-
 # Initialize Gradio client
 client_nsfw = Client("https://ozoneasai-falconsai-nsfw-image-detection.hf.space/--replicas/0fyhj/")
 
@@ -19,7 +16,7 @@ if 'page' not in st.session_state:
 
 # Initialize blur option as a toggle
 if 'blur_option' not in st.session_state:
-    st.session_state.blur_option = st.checkbox("NSFW画像にBlurをかける", value=st.session_state.blur_option, key="blur_toggle")
+    st.session_state.blur_option = st.checkbox("NSFW画像にBlurをかける", value=True, key="blur_toggle")
 
 # Lists to store Gradio predictions, good values, timestamps, and file paths
 gradio_nsfw_predictions = []
@@ -27,6 +24,11 @@ good_values = []
 timestamps = []
 file_paths = []
 
+# Function to get Gradio NSFW prediction
+def get_gradio_nsfw_prediction(image_path):
+    result = client_nsfw.predict(image_path, api_name="/predict")
+    return result["label"]  # Assuming the label is the prediction result
+
 # Define the function to generate a download link for a file
 def get_binary_file_downloader_html(file_path, label="Download"):
     with open(file_path, 'rb') as f:
@@ -35,12 +37,7 @@ def get_binary_file_downloader_html(file_path, label="Download"):
     href = f'<a href="data:file/csv;base64,{b64}" download="{os.path.basename(file_path)}">{label}</a>'
     return href
 
-# Function to get Gradio NSFW prediction
-def get_gradio_nsfw_prediction(image_path):
-    result = client_nsfw.predict(image_path, api_name="/predict")
-    return result
-
-# Inside the save_uploaded_files function, after getting the Gradio predictions
+# Function to save uploaded files and get Gradio predictions
 def save_uploaded_files(uploaded_files):
     if not os.path.exists("temp"):
         os.makedirs("temp")
@@ -50,7 +47,7 @@ def save_uploaded_files(uploaded_files):
         with open(file_path, "wb") as f:
             f.write(uploaded_file.getbuffer())
         
-        # Get Gradio predictions
+        # Get Gradio NSFW prediction
         gradio_nsfw_prediction = get_gradio_nsfw_prediction(file_path)
         
         # Extract good value confidence
@@ -90,7 +87,7 @@ def display_images(images):
 
         # Check if index is within the range
         if i < len(gradio_nsfw_predictions):
-            gradio_nsfw_prediction = gradio_nsfw_predictions[i]
+            gradio_nsfw_prediction = gradio_nsfw_predictions[i][1]  # Accessing the prediction result from the tuple
             timestamp = timestamps[i]
 
             st.write(f"**Prediction for {os.path.basename(file_path)} (NSFW):** {gradio_nsfw_prediction}")
@@ -112,13 +109,12 @@ def display_images(images):
                         os.remove(file_path)
                         st.experimental_rerun()
 
-if 'uploaded_files' not in st.session_state:
-    st.session_state.uploaded_files = None
+# Main part of the Streamlit app
+st.title("ファイルアップロードと共有")
 
 uploaded_files = st.file_uploader("ファイルをアップロードしてください", type=["jpg", "png"], accept_multiple_files=True)
 
 if uploaded_files:
-    st.session_state.uploaded_files = uploaded_files
     save_uploaded_files(uploaded_files)
 
 files_per_page = 20
@@ -146,13 +142,7 @@ st.write(f"現在のページ: {st.session_state.page}")
 
 current_page_files = paginate_files(file_paths, st.session_state.page, files_per_page)
 
-sort_column = st.selectbox("並び替えオプション", ["timestamp", "good"])
-ascending = st.checkbox("昇順", value=True)
-st.session_state.sort_option = {"column": sort_column, "ascending": ascending}
-
-if sort_column == "timestamp":
-    current_page_files.sort(key=lambda x: timestamps[file_paths.index(x)], reverse=not ascending)
-
+# Display images with predictions and options
 display_images(current_page_files)
 
 # Blurのトグルを更新
@@ -165,17 +155,11 @@ if st.button("CSVに保存"):
         csv_writer = csv.writer(csv_file)
         csv_writer.writerow(['ファイル名', 'NSFWの予測', 'Goodの値', '作成時間'])
         for i, file_path in enumerate(file_paths):
-            gradio_nsfw_prediction = gradio_nsfw_predictions[i]
-            good_value = good_values[i]
-            timestamp = timestamps[i]
-            csv_writer.writerow([os.path.basename(file_path), gradio_nsfw_prediction, good_value, timestamp])
+            csv_writer.writerow([os.path.basename(file_path), gradio_nsfw_predictions[i][1], good_values[i], timestamps[i]])
 
     st.markdown(get_binary_file_downloader_html(csv_filename, label="CSVをダウンロード"), unsafe_allow_html=True)
 
-with open("gradio_predictions.txt", "w") as f:
-    for prediction in gradio_nsfw_predictions:
-        f.write(f"{prediction[0]} (NSFW): {prediction[1]}\n")
-
+# ファイルを一括ダウンロード
 if st.button("ファイルを一括ダウンロード"):
     zip_filename = "files.zip"
     with zipfile.ZipFile(zip_filename, "w") as zipf: